[ { "id": "boffi-2024-bagginghook", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/197699", "title": "BaggingHook: Selecting Moving Targets by Pruning Distractors Away for Intention-Prediction Heuristics in Dense 3D Environments", "date": "2024", "abstract": "Selecting targets in dense, dynamic 3D environments presents a significant challenge. In this study, we introduce two novel selection techniques based on distractor pruning to assist users in selecting targets moving unpredictably: BaggingHook and AutoBaggingHook. Both are built upon the Hook intention-prediction heuristic, which continuously measures the distance between the user's cursor and each object to compute per-object scores and estimate the intended target. Our techniques reduce the number of targets in the environment, making heuristic convergence potentially faster. Once pruned away, distractors are also made semi-transparent to reduce occlusion and the overall difficulty of the task. However, their motion is not altered, so that users can still perceive the dynamics of the environment. We designed two pruning approaches: BaggingHook lets users manually prune distractors away, while AutoBaggingHook uses automated, score-based pruning. We conducted a user study in a virtual reality setting inspired by molecular dynamics simulations, featuring crowded scenes of objects moving fast and unpredictably, in 3D. We compared both proposed techniques to the Hook baseline under more challenging circumstances than it had previously been tested. Our results show that AutoBaggingHook was the fastest, and did not lead to higher error rates. BaggingHook, on the other hand, was preferred by the majority of participants, due to the greater degree of control it provides to users, leading some to see entertainment value in its use. This work shows the potential benefits of varying the types of inputs used in intention-prediction heuristics, not just to improve performance, but also to reduce occlusion, overall task load, and improve user experience.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 5365, "drupal_id": null, "orcid_id": "0000-0003-4579-2606", "website": null, "firstname": "Paolo", "lastname": "Boffi", "searchname": "Paolo Boffi", "is_teacher": false, "name": "Paolo Boffi", "publications": [ "boffi-2024-bagginghook" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=5365", "__class": "Author" }, { "id": 5366, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Alexandre", "lastname": "Kouyoumdjian", "searchname": "Alexandre Kouyoumdjian", "is_teacher": false, "name": 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"searchname": "Alexandre Kouyoumdjian", "is_teacher": false, "name": "Alexandre Kouyoumdjian", "publications": [], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "boffi-2024-bagginghook", "field_id": "lecturer", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=5368", "__class": "Author" } ], "location": "Orlando, FL", "pages": "11", "pages_from": "913", "pages_to": "923", "research_areas": [], "keywords": [ "Algorithms", "AR/VR/Immersive", "Human-Subjects Qualitative Studies", "Human-Subjects Quantitative Studies", "Interaction Design", "Mobile", "Specialized Input/Display Hardware" ], "weblinks": [], "files": [], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2024/boffi-2024-bagginghook/", "__class": "Publication" }, { "id": "Alharbi_2021", "type_id": "journalpaper_notalk", "tu_id": 300116, "repositum_id": "20.500.12708/138522", "title": "Nanotilus: Generator of Immersive Guided-Tours in Crowded 3D Environments", "date": "2021-12-09", "abstract": "Immersive virtual reality environments are gaining popularity for studying and exploring crowded three-dimensional structures. When reaching very high structural densities, the natural depiction of the scene produces impenetrable clutter and requires visibility and occlusion management strategies for exploration and orientation. Strategies developed to address the crowdedness in desktop applications, however, inhibit the feeling of immersion. They result in nonimmersive, desktop-style outside-in viewing in virtual reality. This paper proposesNanotilus---a new visibility and guidance approach for very dense environments that generates an endoscopic inside-out experience instead of outside-in viewing, preserving the immersive aspect of virtual reality. The approach consists of two novel, tightly coupled mechanisms that control scene sparsification simultaneously with camera path planning. The sparsification strategy is localized around the camera and is realized as a multiscale, multishell, variety-preserving technique. When Nanotilus dives into the structures to capture internal details residing on multiple scales, it guides the camera using depth-based path planning. In addition to sparsification and path planning, we complete the tour generation with an animation controller, textual annotation, and text-to-visualization conversion. We demonstrate the generated guided tours on mesoscopic biological models -- SARS-CoV-2 and HIV viruses. We evaluate the Nanotilus experience with a baseline outside-in sparsification and navigational technique in a formal user study with 29 participants. 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"field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Plank_Pascal_2015_HVP", "field_id": "supervisor", "ordernum": 2 }, { "publ_id": "plank-2017-sldg", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "puenguentzky-2014-ht", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "raidou_vcbm14", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "rasch-2016-imgses", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "rautek-2009-vmv", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Reisacher_Matthias_CPW", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "sbardellati_ba_2018", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "sifuentes-2018-crowd", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "sorger-2017-thesis", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "textures-3d-printing", "field_id": "supervisor", "ordernum": 2 }, { "publ_id": "Thurner-2005-IVR", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "vad_2015_phd", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Viola_Ivan_2013_HQ3", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Viola-05-Smart", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "viola-2007-ort", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Viola-Pondering-2017", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "vis-foa", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldin-2017-thesis", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Wihann_2017", "field_id": "supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=171", "__class": "Author" } ], "doi": "10.1109/TVCG.2021.3133592", "first_published": "2021-12-09", "journal": "IEEE Transactions on Visualization and Computer Graphics", "open_access": "yes", "pages_from": "1", "pages_to": "16", "research_areas": [ { "id": "BioVis", "drupal_id": 4127, "name": "Biological Data Visualization", "short_abstract": "In this research area, we develop new visualization techniques to support biologists in data analysis and create visualizations to disseminate scientific discoveries in biology.", "abstract": "In modern biological research domain experts have to deal with complex and large data collections and simulations. Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n", "website": "https://www.cg.tuwien.ac.at/research/area/BioVis", "teaser": { "name": "teaser.png", "path": "research_area:BioVis", "type": "image/png", "size": 16330957, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/BioVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "amirkhanov-2019-manylands", "byska-2019-mdfc", "cellVIEW_2015", "cmolik-2020-tvcg", "Dietrich_1", "dietrich-2016-viseq2", "Ehlers_PhD", "ehlers-2025-ait", "eschner-2023-ims", "eschner-blur-2022", "Escribano_2017", "Furmanova_2018", "Gehrer-2017", "Gehrer-2017-molmach", "glinzner-2016-tex", "Halladjian_2020", "kapferer-2017-godot", "klein_2017_IM", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koch-2018-sso", "Kolesar-Fractional-2016", "kolesar-ivan-2014-polymers", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kozlikova-Visualization-2016b", "Krone2016VABC", "Kugler_2019", "lemuzic_2015_timelapse", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lipp-2017-mgpu", "lipp-2017-vulkan", "Manczarski-2016", "manylands_award", "Miao_2019", "miao_inria_2017", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-xmas-card-2016", "Mitterhofer_2017", "nguyen_2020-covid", "Nowak_2020", "raidou_2019_springer", "raidou_shonan167", "raidou2018visualflatter", "rasch-2016-imgses", "Reisacher2016", "rinortner_susanne-2019-vpicc", "Sarkis_2021", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2013-neuromap", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "stappen_2017_animatedcomic", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "trautner-2018-imd", "unger-2019_vcp", "vad_2015_phd", "vad_viktor-2017-WVE", "vad-2016-bre", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "waldin-2019-ccm", "waldner-2014-af", "Weissenboeck_2019", "wu-2017-dagstuhl", "wu-2018-metabo", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg" ], "projects": [ "BioNetIllustration", "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=BioVis", "__class": "ResearchArea" }, { "id": "IllVis", "drupal_id": 4131, "name": "Illustrative Visualization", "short_abstract": "In this research area, we develop rendering methods that are inspired by scientific illustrations, in order to make complex biological information more intuitive to understand and more pleasant to read.", "abstract": "Scientific illustration is concerned with researching ways in which complex biological and medical data can be abstracted in order to convey a desired information that would otherwise be impossible or hard to retrieve from the original data. Illustrators apply such techniques, for instance, to present non-important parts of an organ in a simplified way, while using detailed representations to put the focus of attention on a region where a tumor might be situated.\n\nTo identify such meaningful visual abstractions for visualization, their effectiveness for human perception and cognition has to be assessed, and they have to be formalized in order to make them applicable in rendering algorithms. In this project, we try to advance the understanding of procedural visual abstraction of complex physiological processes that describe the complex machinery of biological life.", "website": "https://www.cg.tuwien.ac.at/research/area/IllVis", "teaser": { "name": "teaser.jpg", "path": "research_area:IllVis", "type": "image/jpeg", "size": 34861, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/IllVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "antes-2026-maa", "Antonini2020", "Balabanian-2010-IIV", "Balduz_01", "Bayat_2019", "Bechtold2020", "Birkeland-2012-IMC", "brandstaetter_01", "bruckner-2005-ICV", "bruckner-2006-ICE", "bruckner-2007-STF", "bruckner-2008-IIV", "bruckner-2010-HVC", "bruckner-2010-IFC", "cellVIEW_2015", "Chen-Information-2016", "Deutsch-2018", "Dhanoa_2021", "Dhanoa2024", "dietrich-2016-viseq2", "donabauer_2019_1", "eg-tut2005-iv", "eschner-2023-ims", "Essler2022", "gangl-2018-gpsart", "Gehrer_Daniel_CUI", "Gehrer-2017-molmach", "gerl-2006-vhi", "Gogel2020", "Groeller_2011_IPV", "Groeller_2016_I3", "Groeller_2016_I6", "Groeller_2016_I7", "Groeller_2016_I8", "Groeller_V1_2020", "groeller-2006-ivt", "groeller-2007-fci", "groeller-2008-irs", "Groeller-2010-IFI", "gruber-2025-vps", "Halladjian_2020", "haushofer-2018-skinning", "Heim_2020", "horvath-2018-ism", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "Knapp_2017_CVR", "Koeppel2020", "kolesar-ivan-2014-polymers", "Konev-FCV2018", "Koszticsak-2017-ewt", "Kouril_2017_11", "kouril-2020-hyperlabels", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "kroesl_x_card_2017", "Lackner_2022", "Langer_Edith_IR1", "lawonn-2018-illvisstar", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "LeMuzic_2016_PhD", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "Leutschacher_2022", "ludwig-2012-MT", "Manczarski-2016", "Matusich-2017-01", "Mautner 2020", "Mayr-2017-1", "Melo_2018_11", "Meusburger_2020", "Miao_2019", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao2018Dimsum", "Michl_2017_CSV", "mindek-2015-mc", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-2019-mci", "mindek-xmas-card-2016", "Moellinger_Christian_IDE2", "Niedermayer_2018", "Ortner_PhD", "Ortner2020", "pahr-2021-vologram", "Panayotov", "patel_daniel_2007_IRSD", "Pauschenwein_2022", "Peter_2012_AIV", "plank-2017-sldg", "prost-2016-molecule", "purgathofer-2008-cgi", "Radwan-2017-Occ", "Rautek-2007-SLI", "Rautek-2008-IDS", "Rautek-2008-VF", "Reichinger_2016", "Reichinger_Fuhrmann_2016", "Reisacher_Matthias_CPW", "Reisacher2016", "Riegelnegg_2019", "rippl-2023-atg", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "schindler_2020vis", "schmidlehner2021", "scholz_2021", "Schrempf_2020", "schultes_lampi", "seyfert-2017", "sikachev-2010-ill_vis_vol_ren", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "Spechtenhauser_Florian_2016", "stappen_2017_animatedcomic", "Stoll2020", "sturl_2016_dynlabels", "Swoboda2020", "szabo_patrik-2022-tour", "takahashi-2019-acdt", "Thomas-2018", "TR-186-2-07-08", "Troidl_2021", "Troidl_2022", "tut-eg-2006", "tut-siggraph-2006", "tut-vis-2006", "tut-vis-2007", "Unger2020", "Vasileva_2022", "Viola_Ivan_2013_SVA", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "viola-evr", "Viola-Pondering-2017", "Viola-vistutillustrativevis", "Waldin_Nicholas_2016_Colormaps", "waldin-2019-ccm", "Waldner_2017_11", "Wihann_2017", "Woschizka_2021", "wu-2019-bmc", "wu-2019-report", "Zaufel_2021", "zechmeister2020", "Zeng_2021", "Zusag-2017-Bach" ], "projects": [ "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=IllVis", "__class": "ResearchArea" }, { "id": "VR", "drupal_id": 4126, "name": "Virtual Reality", "short_abstract": "

In this area, we focus on user experiences and rendering algorithms for virtual reality environments, including methods to navigate and collaborate in VR, foveated rendering, exploit human perception and simulate visual deficiencies.

", "abstract": "

In this area, we focus on user experiences and rendering algorithms for virtual reality environments, including methods to navigate and collaborate in VR, foveated rendering, exploit human perception and simulate visual deficiencies.

", "website": "https://www.cg.tuwien.ac.at/research/area/VR", "teaser": { "name": "teaser.jpg", "path": "research_area:VR", "type": "image/jpeg", "size": 191119, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/VR/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend", "vis" ], "publications": [ "adolf-2019-jug", "Alharbi_2021", "antes-2026-maa", "Bayer_Alexander_2021_FTiVR", "Erhardt_2025_Scutes", "gall-2025-marv", "Goellner_2019-ABC", "gramegna-rfr", "hladky-2022-QS", "huber-2025-eed", "huber-2025-esl", "Kan_Peter-2021-MDPI", "kan-2019-dli", "Kathi-2018-VRB", "Kovacs_2020", "Kroesl_2020_11_09", "kroesl-2019-MoD", "KROESL-2020-SVI", "kroesl-2020-XREye", "Luidolt-2020-DA", "luidolt-2020-lightperceptionVR", "medeiros-2023-gwf", "Mirzaei_Mohammadreza_2020-EVR", "Mortezapoor2021ssc", "panfili-2019-VAVR", "perl_oskar_2021_DVR", "pirch_2021_VRN", "podkosova_2022_bimflexi-vr", "Prossenitsch_2019-1", "reimer-2020-CBG", "reimer-2021-CVR", "Schoenauer_2020_POI", "schuller_reichl-2019-avt", "Sebernegg2020", "sorger-2021-egonet", "Sprung_2021", "Vasylevska2020VRB", "Vonach021", "walchhofer_ar_flowmaps", "walchhofer-tso" ], "projects": [ "BimFlexi", "d4322", "d9275", "EU U-CREATE", "EvaluARte", "MARG", "Superhumans" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=VR", "__class": "ResearchArea" } ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "Image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 540, "image_height": 273, "name": "Alharbi_2021-Image.JPG", "type": "image/jpeg", "size": 46269, "path": "Publication:Alharbi_2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Alharbi_2021/Alharbi_2021-Image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/Alharbi_2021/Alharbi_2021-Image:thumb{{size}}.png" }, { "description": null, "filetitle": "Paper", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Alharbi_2021-Paper.pdf", "type": "application/pdf", "size": 14837965, "path": "Publication:Alharbi_2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Alharbi_2021/Alharbi_2021-Paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/Alharbi_2021/Alharbi_2021-Paper:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "vis", "drupal_id": 1354, "name": "Visualization Group", "website": "https://www.cg.tuwien.ac.at/group/Visualization-Group", "projects": [ "ADAPT", "AngioVis", "Animated Cell Tab development", "AutARG", "avr", "BioNetIllustration", "COMRADE", "d10027", "d10162", "d10164", "d10206", "d10214", "d10413", "d10450", "d10489", "d4328", "d4335", "d4534", "d9275", "d9282", "d9522", "d9555", "d9671", "d9951", "deskollage", "diagvis", "exvisation", "Illustrare", "illvisation", "KASI", "ManyViews", "NeuroViewer", "ProcessIllVis", "ProKeyAnim", "PVG", "Scale-VS", "Scenario Pool", "Semantic Steering", "Sim-CT", "Smart-CT", "Smile Analytics", "ViMaL", "VISAR" ], "research_areas": [ "BioVis", "IllVis", "InfoVis", "MedVis", "NetVis", "Perception", "VisMat", "VR" ], "publications": [ "2013_Viola_Ivan_2013_MTS", "2015-image-coll", "2017-kouril-illcell", "2019-ic", "AA2020", "aigner-2025-vhv", "alacruzECR2004", "alacruzVisSym2004", "Alharbi_2021", "Alsallakh_2012_RCW", "alsallakh-2009-iva", "altendorfer-2008-vts", "amabili2021", "amirkhanov_2012", "amirkhanov_2012heur", "amirkhanov-2011", "amirkhanov-2014-ama", "amirkhanov-2018-withteeth", "amirkhanov-2021-diss", "amirkhanov2010AMA", "ammer-2008-lst", "An-2018-CHI", "AndreUrsits_2013_APP", "antes-2023-vhv", "Antonini2020", "arbesser_ba_2023", "Artner-2004-Hig", "Artner-2005-Hig", "Artner-2005-Thesis", "audioflow", "Auzinger_Mistelbauer_2013_CSR", "balabanian-2007-ant", "balabanian-2008-hvv", "Balabanian-2010-IIV", "Balabanian-2010-PSDSV", "Balduz_01", "Basch_2011_ATA", "Bauer_David_2018", "Bauer_Johannes_2014_IWB", "bauer-2015-cbfd", "Bayat_2019", "bayer-2015-gapaot", "bbeer-2013", "Bechtold2020", "Beer_2011_DVE", "Beham_Michael_PSC", "beham-2014-cupid", "bernhard-2006-dvrcta", "bernhard-2014-GTOM", "bernhard-2016-gft", "Bernold_2019", "bernold-2019-epr", "bhore-2021-issac", "birkeland_aasmund_2014_pums", "Birkeland-2012-IMC", "BirsakHanzl-2009", "boeroendy-2022-uio", "boesch_2014_browserHistoryVis", "borgo-2013-gly", "borondy2022", "bouzari-thesis", "bramberger-3pv", "Brandorff-08-OV", "brandorff-2009-erv", "brandstaetter_01", "brandstaetter-2007-vosd", "Brandstaetter2020", "Braunsperger-2025_bsc", "breitenecker-2020-bct", "bront-2023-svo", "brucker-2010-RES", "Bruckner_Stefan_2015_VAS", "bruckner-2004-EVV", "bruckner-2005-AIV", "bruckner-2005-ATI", "bruckner-2005-ICV", "bruckner-2005-vid", "bruckner-2005-VIS", "bruckner-2006-EVV", "bruckner-2006-ICE", "bruckner-2007-EDF", "bruckner-2007-STF", "bruckner-2008-IIV", "bruckner-2008-IVV", "bruckner-2009-BVQ", "bruckner-2009-IVV", "bruckner-2010-HVC", "bruckner-2010-IFC", "bruckner-2010-ISM", "bruckner-2010-SES", "Bruckner-2012-VEA", "buerger_raphael_2006_3dpoly", "Buerger-2007-cmv", "Buerger-2007-eurovis", "buerger-2007-star", "bugnar-esk-2021", "burns-2007-fea", "bydlinski-2015-gapaot", "byska-2019-mdfc", "Cai_2018", "Caic2021", "Carata_2011_IVE", "carbesser-2013", "casellato-2016-pkg", "cellVIEW_2015", "cizmic-2018-evd", "cmolik-2020-tvcg", "Cornel_2020", "Cornel_Daniel_2015_VOC", "Cornel2016CFM", "coto-2005-MAC", "Cruz-thesis", "Csebfalvi-2002-FPVF", "Csebfalvi-2002-SBICG", "Csebfalvi-2002-Smo", "Csebfalvi-2012-IOM", "Csuk_2011", "daae-lampe-2010-dif", "dataset-christmastree", "dataset-present", "dataset-stagbeetle", "Deutsch-2018", "Dhanoa_2021", "dhanoa-2025-ave", "Dhanoa2024", "Diehl_2015", "Diehl_2021", "Diehl-2017-Albero", "Dietrich_1", "dietrich-2016-viseq2", "diss-thesis-bratislava", "diss-thesis-magdeburg", "diss-thesis-siegen", "djuric-2020-wvo", "donabauer_2019_1", "donabauer-2015-asc", "draeger-2005-chain", "dworschak-2016-szcm", "dworschak-2016-szcm", "dworschak-2024-aml", "Eckelt_2017", "Eckelt_2018_01", "Edi_2019_10_01", "edlinger-2018-vwr", "eg-tut2005-iv", "Ehlers_PhD", "ehlers-2023-iro", "ehlers-2024-mmm", "ehlers-2024-vgs", "ehlers-2025-ait", "Eichner2022", "eitler-2024-sos", "eiweck-hnv-2021", "ellhotka-2025-ipo", "emsenhuber-2008-vhd", "erler-2025-lidarscout", "eschner-2023-evl", "eschner-2023-ims", "eschner-2025-ide", "eschner-blur-2022", "Escribano_2017", "Essler2022", "EuroVis2018-ShortPapers-Karall", "EuroVis2018-ShortPapers-Reiter", "facial2004", "Fechter_2011_DBS", "filipovic-2014-dect", "FISCHL-2012-CTASEG", "fmistelbauer-2014-ad", "fmistelbauer-2014-adict", "Ford-2012-HRV", "fourousan2021", "freiler-2008-ste", "fritz-2009-ieq", "Froehler_Berhnard_2015_ESM", "froschauer-2009-iod", "Fruehstueck_Anna_2015_DOM", "fuchs_raphael_2007_par", "fuchs_vhml", "fuchs-2008-del", "fuchs-vortex", "furmanova_2020", "gadllah_2016", "Gadllah_Hani_2016", "gall_2016", "Gall_2017", "gall_alexander_2016BA", "gall-2025-marv", "Gall2020", "Gall2021", "gangl-2018-gpsart", "Ganglberger-2022-cg", "ganglberger2019", "Ganuza", "Ganuza_2015", "Ganuza_MJ_2015_AVe", "Ganuza_ML_2015_ISA", "Ganuza-2017-IVCSGM", "Gavrilescu_2011_VGP", "gavrilescu-2008-vsc", "gavrilescu-2009-postrend", "Gavrilescu-2010-CIE", "Gehrer_Daniel_CUI", "Gehrer-2017", "Gehrer-2017-molmach", "georgiev-2019-cbg", "gerl-2006-vhi", "geymayer-2017-std", "Gietl_2020", "Gillmann2021", "glanznig-2009-LAMC", "glinzner-2016-tex", "goel-2024-rdr", "Gogel2020", "gostler-2015-3dp", "grammatikaki-2025-htr", "grammatikaki-thesis", "grimm-2004-arefined", "GRIMM-2004-FDMX-P", "grimm-2004-memory", "GRIMM-2004-PPC", "grimm-2004-volume", "Groeller_2011_CVC", "Groeller_2011_CW", "Groeller_2011_GBC", "Groeller_2011_HP", "Groeller_2011_HSU", "Groeller_2011_IPV", "Groeller_2011_IVP", "Groeller_2011_NR", "Groeller_2011_NSM", "Groeller_2011_VCD", "Groeller_2011_VSD", "Groeller_2011_VSD", "Groeller_2011_VSD", "Groeller_2011_VSS", "Groeller_2012_KAV", "Groeller_2012_VBP", "Groeller_2012_ViV", "Groeller_2012_VV", "Groeller_2014_CaQ", "Groeller_2014_CQV", "Groeller_2014_CV", "Groeller_2014_RWA", "Groeller_2014_STC", "Groeller_2014_UPS", "Groeller_2014_VND", "Groeller_2016_I2", "Groeller_2016_I7", "Groeller_2016_I8", "Groeller_2016_P2", "Groeller_2016_P4", "Groeller_2016_P6", "Groeller_2016_P7", "Groeller_2021_11", "Groeller_2021_BVM", "Groeller_2021-10", "Groeller_Edi_2013_TVC", "Groeller_Edi_2013_VCQ", "Groeller_Edi_2013TVCK", "Groeller_Edi_VKA", "Groeller_Eduard_2014_THS", "Groeller_Eduard_2014_TSP", "Groeller_Eduard_2014_UCT", "Groeller_Eduard_2015_SMV", "Groeller_Eduard_2015_TCU", "Groeller_V1_2020", "Groeller_V2_2020", "Groeller_V3_2020", "Groeller_V42020", "Groeller_V5_2020", "groeller-2004-efficient", "groeller-2004-imp", "groeller-2004-sci", "groeller-2005-dia", "Groeller-2010-CVC", "Groeller-2010-IFI", "Groeller-2010-IVVI", "Groeller-2011-HSH", "Groeller-2017-ARTORW", "Groeller-2017-AVC", "Groeller-2017-IVAMCS", "Groeller-2017-PTPMD", "Groller_2021-12-03", "Gronde_2008", "Grorller-2010-IVV", "grossmann_2019_pelvisrunner_poster", "Grossmann_MA", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", "grossmann-thesis", "gruber-2025-vps", "Gruenauer-2011-CAT", "Gschwantner_2011_AMQ", "gundacker-2020-wlm", "Gurbat_2011_SBS", "gusenbauer-2018", "gusenbauer-2018", "gusenbauer-2018-P", "gutekunst_2019", "Hadwiger-2002-Fas", "haidacher_2010_statTF", "haidacher-2004-FVV", "haidacher-2005-MND", "haidacher-2007-idr", "haidacher-2008-vcbm", "haidacher-2011-MSM", "haidacher-2011-phd", "haidacher-2011-VAM", "Hainoun2019", "Halladjian_2020", "hanzl-2011", "hartl-2008-vcd", "hartmann-2005-adv", "haushofer-2018-skinning", "Heim_2020", "Heim_2021", "Heim-2017", "heim-2024-accustripes", "heim-gall-2020-dde", "heinzl_2006_RSDVCDM", "heinzl-2006-rep", "heinzl-2008-sam", "Heinzl2021", "Herghelegiu-2012-BPV", "herzberger-2023-swv", "herzberger-2024-roh", "Hirsch_Christian_2015_ABL", "Hladuvka-2002-Exp", "hladuvka-2002-exploiting", "Hochmayr_Manuel_2015_PSE", "hochmayr_manuel-2011-VoRMD", "Hochpoechler_2016_VR", "horvath-2018-ism", "hromniak-2019-vcn", "huber-2025-eed", "Iijima-2020-iV", "indirectBiasLanguageModels-2023", "irendorfer-2024-uat", "irger-2023-ves", "Ismail-2018", "jank-2022-cbf", "Kanitsar-2002-CPR", "Kanitsar-2003-Adva", "Kanitsar-2003-Dem", "Kanitsar-2004-Dia", "Kanitsar-thesis", "kapferer-2017-godot", "Karall2017CVAB", "Karall2018_2", "karimov-2013-vivisection", "karimov-2015-HD", "karimov-2016-GIVE", "karimov-2016-SD", "keglevic_schulz-2011-MB", "Kehrer-2008-hyp", "Kehrer-2010-mom", "kehrer-2011-vai", "kehrer-2012-mod", "kehrer-2013-IVA", "kehrer-2013-SBC", "Kehrer-2013-STAR", "Kehrer-2014-CSD", "kerbl-2024-ah3", "kimmersdorfer-fancyMaps-2023", "Kinkelin_2009", "Kinkelin-2011-VR", "Klaus2024", "Kleber-2004-TFE", "klein_2017_IM", "klein_2019_MSA_Poster", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "Klein_Tobias_2015TIV", "klein-thesis", "Knapp_2017_CVR", "knapp_michael_2004_MAS", "knapp-2004-semi", "koch_bernhard_2018-1", "koch-2018-sso", "koehle-2013-sgv", "koeppel-2021", "Koeppel2020", "Kohlmann-2007-EBV", "kohlmann-2007-livesync", "kohlmann-2008-lse", "kohlmann-2009-cp", "kohlmann-2009-lssl", "kolesar-ivan-2014-polymers", "Kolter_2021", "komon-2025-dco", "komon-2025-webigeo", "komon-2025-webigeo", "komon-kimmersdorfer-2025-weBIGeo", "Konyha_2013_IVA", "korpitsch_thorsten-2019", "korpitsch-2020-cescg", "Korpitsch-2020-wscg", "korpitsch-2021-lov", "Koszticsak-2017-ewt", "Kouril_2017_11", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2018-LoL", "kouril-2018-LoL", "kouril-2020-hyperlabels", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kovacs_PhD", "krakhofer-2015", "Krone2016VABC", "kuehschelm-2005-adv", "Kugler_2019", "Kuroko-2020-iV", "Labschuetz_Matthias_2015_JIT", "Labschuetz_Matthias_2016_AHD", "Labschuetz_Matthias_2016_JIT", "Labschuetz_Matthias_2016_JITT", "Lackner_2022", "LaCruz2004", "Ladstaedter-2009-sim", "Langer_Edith_IR1", "Langer_Maximillian_DMV", "Laschober-2018", "lawonn-2018-illvisstar", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "LeMuzic_2016_PhD", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lemuzic-mindek-sorger-cgfcc", "Leutschacher_2022", "li-2019-gdc", "lie-2009-cri", "lipp-2017-mgpu", "lipp-2017-vulkan", "lippeck-2022-mna", "liu-2014-ac", "lkoell-2014", "ludwig-2012-MT", "Machegger2018DTI", "magg-2021-dva", "magg2021", "mahler-2021-mdar", "major-2010-mrf", "malan_fluoro", "malik-2007-FP", "malik-2009-CVFA", "malik-thesis", "Manczarski-2016", "Marek06", "Maricic_2013_VFE", "martorell2022", "maruyama-2019-iv", "Masopust_2018", "Masterthesis-Viola", "Matkovic_Kresimir_2015_", "matt-2023-vae", "matt-2024-cvil", "matt-2025-scv", "matt-masterthesis", "Mattausch-2003-ISL", "Mattausch-2003-SIE", "Mattausch-2003-Str", "Matusich-2017-01", "Mautner 2020", "Mayr-2017-1", "mayr-2021-wec", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "Mazza_2020", "Mazza_2021_05", "meka-2024-lpi", "Melo_2018_11", "Meusburger_2020", "Miao_2015_VCBM", "Miao_2019", "Miao_Haichao_2015_VQC", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_plitvice_2018", "miao_thesis_2019", "miao_tvcg_2017", "miao_tvcg_2018", "miao_tvcg_2018", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "Michl_2017_CSV", "mindek_peter-2012-visgroupproj", "mindek_peter-2014-cs_kaust", "mindek-2013-cs_cvut", "mindek-2013-csl", "mindek-2013-pel", "mindek-2014-mcs", "mindek-2014-vivi_cvut", "mindek-2015-mc", "mindek-2015-mctalk", "mindek-2016-utah-talk", "mindek-2017-dsn", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-2019-mci", "mindek-thesis", "mistelbauer_2013_SIV", "Mistelbauer_2021", "Mistelbauer_Gabriel_2015_NHR", "Mistelbauer_Gabriel_2016", "mistelbauer-2010-pvv", "mistelbauer-2012-cr", "mistelbauer-2012-ssv", "mistelbauer-2013-cfa", "mistelbauer-2015-abvv", "Mitterhofer_2017", "mizuno-2019-eurovis", "Mlejnek_2004_PF", "Mlejnek_2005_AOEPF", "Mlejnek_2006_MVOA", "Mlejnek-2004-Int", "Mlejnek-2004-ITVAC", "Mlinaric-2015-MT", "Moellinger_Christian_IDE2", "moerth_eric-2016-3DF", "moerth-2018-tpose", "monitzer_2008_FluSi", "Morar_2012_ISB", "Muehlbacher_diss_2018", "mueller-2009-ivs", "Muigg_2011_ISI", "Muigg_2011_VC", "Muigg-2008-four", "muigg-2012-svr", "musleh-2024-conan", "muth-2026-clouds", "Neumann-2002-Fea", "nguyen_2020-covid", "Niedermayer_2018", "Novotny_2013_ASVD", "Nowak_2020", "Nowak_2021", "Oancea_2018_1", "Oancea_Stefan_2016_VOT", "Oancea2018OAK", "oeltze-2013-tut", "opitz-2009-cvv", "Ortner_PhD", "Ortner2020", "Pahr_PhD", "pahr-2021-vologram", "pahr-2024-ieo", "pahr-2024-squishicalization", "pahr-2025-holographs", "pahr-2025-nodkant", "Pahr2020", "Pajer_2012_VoM", "Panayotov", "papantonakis-2024-rmf", "Parzer_2013_IIG", "patel_2009_MC", "patel_daniel_2007_IRSD", "patel-2008-tsa", "patel-2009-evr", "patel-2011-PEA", "Pauschenwein_2022", "Peter_2012_AIV", "Pezenka-2016-MT", "Pfahler_David_2015_IPI", "Pfahler-2016-MT", "PH-2011-LDS", "phd-viola", "Philipp_Hochhauser_2023", "Pilizar_-2020-bachelor", "piringer-2009-hds", "Plank_Pascal_2015_HVP", "plank-2017-sldg", "PMI_AR_2012", "pointner_simon-2020", "polatsek-2018-stv", "polatsek-2018-stv", "Pramerdorfer-2011-PAV", "preim-2009-sve", "Presch_2020", "Priselac2021", "puehringer-2009-sbm", "puenguentzky-2014-ht", "Purchase-2020-gd", "raidou_2018_bladderrunner", "raidou_2019_pelvisrunner", "raidou_2019_preha", "raidou_2019_springer", "raidou_2020Onc", "raidou_EuroVis15", "raidou_eurovis16", "raidou_miccai16", "raidou_pingu2020", "raidou_previs2021", "raidou_RO2019", "raidou_shonan167", "raidou_slicedice", "raidou_star2019", "raidou_vcbm14", "raidou_vis14", "raidou_vis15", "raidou_visgap2020", "raidou2018_rv3", "raidou2018visualflatter", "raidou2019_prsps", "rasch-2016-imgses", "Rau08", "Rautek_Peter_2014_TUC", "Rautek_Peter_2014_VSA", "rautek-2005-dvr", "Rautek-2007-O3D", "Rautek-2007-SLI", "Rautek-2008-IDS", "Rautek-2008-kav", "Rautek-2008-VF", "rautek-2009-vmv", "RAUTEK06", "Rautek06Vis", "Rautek06VMLS", "rautek2010", "Red_Andreas_2015_FFT", "Reh_Andreas_VoP", "reh-2013", "reina-2020-mtv", "Reisacher_Matthias_CPW", "Reisacher2016", "Reiter_2009_IXIA", "Reiter2017CVAP", "Rezk06Vis", "Ribicic_2012_SUS", "Ribicic_2012_VAS", "Ribicic-2010-CRS", "Riegelnegg_2019", "rinortner_susanne-2019-vpicc", "rinortner_susanne-2019-vpicc", "Rippberger_2019", "rippl-2023-atg", "ritzberger-2010-nar", "Ropinski-2012-UBT", "rozana-2026-vcfd", "rraidou_clinical", "rraidou_EG17", "rraidou_phdbook", "rsabin-2013", "ruiz-2008-OVR", "ruiz-2008-SEV", "samoul-2019-cnp", "Sanjin_Rados_RV", "Sarkis_2021", "Sbardellati-2019-vcbm", "Sbardellati-2019-vcbm", "sbardellati-2021-eveos", "scharsach-2005-adv", "Schernthaner-2017-MCP", "schindler_2020vis", "Schindler-2022-eurovis", "schindler2020", "schleicher-2011-VLSC", "Schmidlehner_Sandra_SbC", "schmidlehner2021", "schmidt-2011-mt", "schmidt-phd", "schmidt-phd", "schoellhuber-2008-asc", "scholz_2021", "Schrempf_2018", "Schrempf_2020", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "schuh-2018-mesh-blending", "schultes_lampi", "Schulze_Florian_2013_CMI", "schwankl-2013-smis", "seyfert-2017", "shakhova-2023-atp", "sietzen-2019-wnn", "sietzen-2019-wnn", "sietzen-2021-perturber", "sietzen-2022-vacnnr", "sietzen-ifv-2019", "sifuentes-2018-crowd", "SifuentesGangl2017FIS", "sikachev_peter_2010_STLCI", "sikachev_peter-2011-dfc", "sikachev_peter-2011-incshad", "sikachev_peter-2011-metavis", "sikachev_peter-2011-protovis", "sikachev-2010-DFC", "sikachev-2010-ill_vis_vol_ren", "Sippl_Sebastian_EFG", "smiech-2018-tei", "Smisek_Michal_A3D", "Sollboeck_2011_FSS", "sollboeck-2011", "Solteszova-2009-VQN", "solteszova-2010-MOS", "Solteszova2016", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "sorger-2019-odn", "sorger-2021-egonet", "Soros_AVN_2011", "Soros-AV-2010", "Spechtenhauser_Florian_2016", "spegel-gruenberger-2020", "Spelitz2020", "spoerk-2010-hpgpu", "Stabel_2012_UDM", "stappen_2017_animatedcomic", "Staudacher_2022", "staudacher_florian-2016-topo3d", "stehno-2011-RVD", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "STEINLECHNER-2019-ICT", "StickmanMax-shoetta-kampfer", "stoff-2025-pvu", "stoff-concepMap-2021", "StrakaVis2004", "stritzel2022", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "suntinger-2008-etet", "suntinger-2008-tet", "Swoboda_Nicolas_VIT", "Swoboda2020", "szabo_patrik-2022-tour", "szabo-thesis", "takahashi-2019-acdt", "tekaya-2025-amo", "tekaya-2025-amo", "termeer-2006-000", "termeer-2007-covicad", "termeer-2008-scmr", "termeer-2008-vis", "termeer-2009-cvc", "termeer-2009-scmr", "textures-3d-printing", "thesis-kronsteiner", "thesis-tekaya", "Thomas-2018", "Thurner-2005-IVR", "toth-2007-ndd", "TR-186-2-05-01", "TR-186-2-05-02", "TR-186-2-05-03", "TR-186-2-05-04", "TR-186-2-05-06", "TR-186-2-05-07", "TR-186-2-05-08", "TR-186-2-06-01", "TR-186-2-06-02", "TR-186-2-06-03", "TR-186-2-06-04", "TR-186-2-07-02", "TR-186-2-07-03", "TR-186-2-07-04", "TR-186-2-07-05", "TR-186-2-07-06", "TR-186-2-07-07", "TR-186-2-07-08", "TR-186-2-07-10", "TR-186-2-07-11", "TR-186-2-07-12", "TR-186-2-08-01", "TR-186-2-08-02", "TR-186-2-08-03", "TR-186-2-08-04", "TR-186-2-08-05", "TR-186-2-08-06", "TR-186-2-08-07", "TR-186-2-08-08", "TR-186-2-08-10", "TR-186-2-08-11", "TR-186-2-08-12", "TR-186-2-08-14", "TR-186-2-09-01", "TR-186-2-15-03", "TR1862162", "Tramberger_2018", "Tramberger2017BCS", "Trautner_Thomas_2014_VAE", "trautner-2018-imd", "trautner-2018-imd", "travnicek-2017-thm", "Trenkwalder-2004-MAR", "tretyak-2025-tacmedvr", "Troidl_2019", "Troidl_2021", "Troidl_2022", "turner-aso", "tut-eg-2006", "tut-siggraph-2006", "tut-vis-2006", "tut-vis-2007", "tweebo-2014", "ulschmid-2024-reo", "ulschmid-2025-apc", "unger_2017", "unger-2019_vcp", "Unger2020", "unterguggenberger-2024-fropo", "usul-thesis", "vad_2015_phd", "Vad_Viktor_2015_RVV", "vad-2016-bre", "vaico", "varchola_andrej-2012-fetoscopic", "Vasileva_2022", "Vasileva-2018", "vessel2003", "Viola_2013_IDV", "Viola_Ivan_2013_CAI", "Viola_Ivan_2013_D3D", "Viola_Ivan_2013_DC", "Viola_Ivan_2013_GS", "Viola_Ivan_2013_HQ3", "Viola_Ivan_2013_RMA", "Viola_Ivan_2013_RSb", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_DAC", "Viola_Ivan_IIP", "Viola_Ivan_UVP", "Viola_Ivan_VDP", "Viola-05-Smart", "Viola-2003-GPU", "Viola-2003-Har", "viola-2003-hbn", "Viola-2003-NON", "viola-2004-gbf", "Viola-2004-GPU", "viola-2004-har", "viola-2004-har2", "viola-2004-idv", "viola-2004-imp", "Viola-2004-ImpX", "Viola-2004-ImpX2", "viola-2005-imp", "viola-2006-FoA", "viola-evr", "Viola-Pondering-2017", "viola-popular-article-2006", "Viola-vistutillustrativevis", "vis-foa", "VisWeek-Tutorial-2012-Uncertainty", "vitruvian_2019", "voglreiter-2023-tro", "Vucenovic_2022", "vucini_2006", "vucini_2008_rnp", "vucini_2009", "vucini_erald-2007-FRI", "vucini-2009-phd", "vucini-2011", "Wagner_032017", "walchhofer_ar_flowmaps", "walchhofer-tso", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "Waldin_Nicholas_2017_FlickerObserver", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2017-thesis", "waldin-2019-ccm", "waldin-2019-ccm", "Waldner_2017_11", "Waldner_2017_11", "waldner-2013-facetCloudsGI", "waldner-2013-ubiWM", "waldner-2014-af", "waldner-2014-ghi", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "waser_2011_VSD", "Waser-2010-WL", "webGPU_aggregateVis-2023", "weiner_2011", "Weissenboeck_2019", "Weissenboeck_2019_PhD", "weissenboeck-2014", "Wihann_2017", "wolf-2023-cc", "wolf-2024-jhd", "Woschizka_2021", "wu-2017-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-shonan", "wu-2018-story", "wu-2019-bmc", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-smwp", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg", "wu-2021", "wu-2021-vi", "xmastree2002", "xmastree2005", "ymca", "YOGHOURDJIAN2019", "Zambal-2003-SWA", "zambal-2005-3dact", "Zaufel_2021", "zauner-2013-svkinect", "zechmeister2020", "Zeng_2021", "Zhu-2014-flowvis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Workgroup&id=vis", "__class": "Workgroup" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Alharbi_2021/", "__class": "Publication" }, { "id": "kouril-2021-molecumentary", "type_id": "journalpaper", "tu_id": 300120, "repositum_id": "20.500.12708/138523", "title": "Molecumentary: Adaptable Narrated Documentaries Using Molecular Visualization", "date": "2021-11-25", "abstract": "We present a method for producing documentary-style content using real-time scientific visualization. We introduce molecumentaries, i.e., molecular documentaries featuring structural models from molecular biology, created through adaptable methods instead of the rigid traditional production pipeline. Our work is motivated by the rapid evolution of scientific visualization and it potential in science dissemination. Without some form of explanation or guidance, however, novices and lay-persons often find it difficult to gain insights from the visualization itself. We integrate such knowledge using the verbal channel and provide it along an engaging visual presentation. To realize the synthesis of a molecumentary, we provide technical solutions along two major production steps: (1) preparing a story structure and (2) turning the story into a concrete narrative. In the first step, we compile information about the model from heterogeneous sources into a story graph. We combine local knowledge with external sources to complete the story graph and enrich the final result. In the second step, we synthesize a narrative, i.e., story elements presented in sequence, using the story graph. We then traverse the story graph and generate a virtual tour, using automated camera and visualization transitions. We turn texts written by domain experts into verbal representations using text-to-speech functionality and provide them as a commentary. Using the described framework, we synthesize fly-throughs with descriptions: automatic ones that mimic a manually authored documentary or semi-automatic ones which guide the documentary narrative solely through curated textual input.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "overview", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 943, "image_height": 399, "name": "kouril-2021-molecumentary-overview.png", "type": "image/png", "size": 224541, "path": "Publication:kouril-2021-molecumentary", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/kouril-2021-molecumentary/kouril-2021-molecumentary-overview.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/kouril-2021-molecumentary/kouril-2021-molecumentary-overview:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 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"karimov-2013-vivisection", "klein_2019_MSA_Poster", "klein_2019_PGG", "klein_2019_PMP", "koch_bernhard_2018-1", "kouril-2021-molecumentary", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lemuzic-mindek-sorger-cgfcc", "Miao_2019", "mindek_peter-2012-visgroupproj", "mindek_peter-2014-cs_kaust", "mindek-2013-cs_cvut", "mindek-2013-csl", "mindek-2013-pel", "mindek-2014-mcs", "mindek-2014-vivi_cvut", "mindek-2015-mc", "mindek-2015-mctalk", "mindek-2016-utah-talk", "mindek-2017-dsn", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-2019-mci", "mindek-tedx", "mindek-thesis", "mindek-xmas-card-2014", "mindek-xmas-card-2016", "nguyen_2020-covid", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "TR-186-2-15-03", "wu-2021", "wu-2021-vi", "xmas-2012" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "bayer-2015-gapaot", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "bydlinski-2015-gapaot", "field_id": 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"gall-2025-marv", "Gall2021", "Ganuza", "Ganuza_2015", "Ganuza_MJ_2015_AVe", "Ganuza_ML_2015_ISA", "Ganuza-2017-IVCSGM", "Gavrilescu-2010-CIE", "Gillmann2021", "Glaeser-1997-EVG", "Glaeser-1998-AFa", "Glaeser-1998-Eff", "Glaeser-1999-Fas", "glanznig-2009-LAMC", "Grimm-2003-CPU", "Grimm-2003-HYP", "grimm-2004-arefined", "GRIMM-2004-FDM", "GRIMM-2004-FDMX", "GRIMM-2004-FDMX-P", "grimm-2004-memory", "GRIMM-2004-PPC", "grimm-2004-volume", "Groeller_2011_CVC", "Groeller_2011_CW", "Groeller_2011_GBC", "Groeller_2011_HP", "Groeller_2011_HSU", "Groeller_2011_IPV", "Groeller_2011_IVP", "Groeller_2011_NR", "Groeller_2011_NSM", "Groeller_2011_VCD", "Groeller_2011_VSD", "Groeller_2011_VSS", "Groeller_2012_KAV", "Groeller_2012_VBP", "Groeller_2012_ViV", "Groeller_2012_VV", "Groeller_2014_CaQ", "Groeller_2014_CQV", "Groeller_2014_CV", "Groeller_2014_RWA", "Groeller_2014_STC", "Groeller_2014_UPS", "Groeller_2014_VND", "Groeller_2016_I1", "Groeller_2016_I2", "Groeller_2016_I3", "Groeller_2016_I4", 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"TVCG_information_for_authors.pdf", "ext": "pdf" }, "date_from": "2021-11-15", "date_to": "2021-11-15", "doi": "10.1109/TVCG.2021.3130670", "event": "IEEE Vis 2022", "journal": "IEEE Transactions on Visualization and Computer Graphics", "lecturer": [ { "id": 1383, "drupal_id": 1132, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/DavidKouřil", "firstname": "David", "lastname": "Kouřil", "searchname": "David Kouřil", "is_teacher": false, "name": "David Kouřil", "publications": [ "2017-kouril-illcell", "Alharbi_2021", "dvdkouril_xmas_card_2018", "Halladjian_2020", "koch_bernhard_2018-1", "Kouril_2017_11", "kouril_2022_paper", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2018-LoL", "kouril-2020-hyperlabels", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Miao_2019", "mindek-2017-marion", "mindek-2017-virtualcell", "Sarkis_2021", "wu-2021", "wu-2021-vi" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": 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large data collections and simulations. Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n", "website": "https://www.cg.tuwien.ac.at/research/area/BioVis", "teaser": { "name": "teaser.png", "path": "research_area:BioVis", "type": "image/png", "size": 16330957, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/BioVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "amirkhanov-2019-manylands", "byska-2019-mdfc", "cellVIEW_2015", "cmolik-2020-tvcg", "Dietrich_1", "dietrich-2016-viseq2", "Ehlers_PhD", "ehlers-2025-ait", "eschner-2023-ims", "eschner-blur-2022", "Escribano_2017", "Furmanova_2018", "Gehrer-2017", "Gehrer-2017-molmach", "glinzner-2016-tex", "Halladjian_2020", "kapferer-2017-godot", "klein_2017_IM", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koch-2018-sso", "Kolesar-Fractional-2016", "kolesar-ivan-2014-polymers", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kozlikova-Visualization-2016b", "Krone2016VABC", "Kugler_2019", "lemuzic_2015_timelapse", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lipp-2017-mgpu", "lipp-2017-vulkan", "Manczarski-2016", "manylands_award", "Miao_2019", "miao_inria_2017", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-xmas-card-2016", "Mitterhofer_2017", "nguyen_2020-covid", "Nowak_2020", "raidou_2019_springer", "raidou_shonan167", "raidou2018visualflatter", "rasch-2016-imgses", "Reisacher2016", "rinortner_susanne-2019-vpicc", "Sarkis_2021", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2013-neuromap", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "stappen_2017_animatedcomic", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "trautner-2018-imd", "unger-2019_vcp", "vad_2015_phd", "vad_viktor-2017-WVE", "vad-2016-bre", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "waldin-2019-ccm", "waldner-2014-af", "Weissenboeck_2019", "wu-2017-dagstuhl", "wu-2018-metabo", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg" ], "projects": [ "BioNetIllustration", "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=BioVis", "__class": "ResearchArea" }, { "id": "IllVis", "drupal_id": 4131, "name": "Illustrative Visualization", "short_abstract": "In this research area, we develop rendering methods that are inspired by scientific illustrations, in order to make complex biological information more intuitive to understand and more pleasant to read.", "abstract": "Scientific illustration is concerned with researching ways in which complex biological and medical data can be abstracted in order to convey a desired information that would otherwise be impossible or hard to retrieve from the original data. Illustrators apply such techniques, for instance, to present non-important parts of an organ in a simplified way, while using detailed representations to put the focus of attention on a region where a tumor might be situated.\n\nTo identify such meaningful visual abstractions for visualization, their effectiveness for human perception and cognition has to be assessed, and they have to be formalized in order to make them applicable in rendering algorithms. In this project, we try to advance the understanding of procedural visual abstraction of complex physiological processes that describe the complex machinery of biological life.", "website": "https://www.cg.tuwien.ac.at/research/area/IllVis", "teaser": { "name": "teaser.jpg", "path": "research_area:IllVis", "type": "image/jpeg", "size": 34861, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/IllVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "antes-2026-maa", "Antonini2020", "Balabanian-2010-IIV", "Balduz_01", "Bayat_2019", "Bechtold2020", "Birkeland-2012-IMC", "brandstaetter_01", "bruckner-2005-ICV", "bruckner-2006-ICE", "bruckner-2007-STF", "bruckner-2008-IIV", "bruckner-2010-HVC", "bruckner-2010-IFC", "cellVIEW_2015", "Chen-Information-2016", "Deutsch-2018", "Dhanoa_2021", "Dhanoa2024", "dietrich-2016-viseq2", 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"dworschak-2024-aml", "Eckelt_2017", "Eckelt_2018_01", "Edi_2019_10_01", "edlinger-2018-vwr", "eg-tut2005-iv", "Ehlers_PhD", "ehlers-2023-iro", "ehlers-2024-mmm", "ehlers-2024-vgs", "ehlers-2025-ait", "Eichner2022", "eitler-2024-sos", "eiweck-hnv-2021", "ellhotka-2025-ipo", "emsenhuber-2008-vhd", "erler-2025-lidarscout", "eschner-2023-evl", "eschner-2023-ims", "eschner-2025-ide", "eschner-blur-2022", "Escribano_2017", "Essler2022", "EuroVis2018-ShortPapers-Karall", "EuroVis2018-ShortPapers-Reiter", "facial2004", "Fechter_2011_DBS", "filipovic-2014-dect", "FISCHL-2012-CTASEG", "fmistelbauer-2014-ad", "fmistelbauer-2014-adict", "Ford-2012-HRV", "fourousan2021", "freiler-2008-ste", "fritz-2009-ieq", "Froehler_Berhnard_2015_ESM", "froschauer-2009-iod", "Fruehstueck_Anna_2015_DOM", "fuchs_raphael_2007_par", "fuchs_vhml", "fuchs-2008-del", "fuchs-vortex", "furmanova_2020", "gadllah_2016", "Gadllah_Hani_2016", "gall_2016", "Gall_2017", "gall_alexander_2016BA", "gall-2025-marv", "Gall2020", "Gall2021", "gangl-2018-gpsart", "Ganglberger-2022-cg", "ganglberger2019", "Ganuza", "Ganuza_2015", "Ganuza_MJ_2015_AVe", "Ganuza_ML_2015_ISA", "Ganuza-2017-IVCSGM", "Gavrilescu_2011_VGP", "gavrilescu-2008-vsc", "gavrilescu-2009-postrend", "Gavrilescu-2010-CIE", "Gehrer_Daniel_CUI", "Gehrer-2017", "Gehrer-2017-molmach", "georgiev-2019-cbg", "gerl-2006-vhi", "geymayer-2017-std", "Gietl_2020", "Gillmann2021", "glanznig-2009-LAMC", "glinzner-2016-tex", "goel-2024-rdr", "Gogel2020", "gostler-2015-3dp", "grammatikaki-2025-htr", "grammatikaki-thesis", "grimm-2004-arefined", "GRIMM-2004-FDMX-P", "grimm-2004-memory", "GRIMM-2004-PPC", "grimm-2004-volume", "Groeller_2011_CVC", "Groeller_2011_CW", "Groeller_2011_GBC", "Groeller_2011_HP", "Groeller_2011_HSU", "Groeller_2011_IPV", "Groeller_2011_IVP", "Groeller_2011_NR", "Groeller_2011_NSM", "Groeller_2011_VCD", "Groeller_2011_VSD", "Groeller_2011_VSD", "Groeller_2011_VSD", "Groeller_2011_VSS", "Groeller_2012_KAV", "Groeller_2012_VBP", "Groeller_2012_ViV", "Groeller_2012_VV", "Groeller_2014_CaQ", "Groeller_2014_CQV", "Groeller_2014_CV", "Groeller_2014_RWA", "Groeller_2014_STC", "Groeller_2014_UPS", "Groeller_2014_VND", "Groeller_2016_I2", "Groeller_2016_I7", "Groeller_2016_I8", "Groeller_2016_P2", "Groeller_2016_P4", "Groeller_2016_P6", "Groeller_2016_P7", "Groeller_2021_11", "Groeller_2021_BVM", "Groeller_2021-10", "Groeller_Edi_2013_TVC", "Groeller_Edi_2013_VCQ", "Groeller_Edi_2013TVCK", "Groeller_Edi_VKA", "Groeller_Eduard_2014_THS", "Groeller_Eduard_2014_TSP", "Groeller_Eduard_2014_UCT", "Groeller_Eduard_2015_SMV", "Groeller_Eduard_2015_TCU", "Groeller_V1_2020", "Groeller_V2_2020", "Groeller_V3_2020", "Groeller_V42020", "Groeller_V5_2020", "groeller-2004-efficient", "groeller-2004-imp", "groeller-2004-sci", "groeller-2005-dia", "Groeller-2010-CVC", "Groeller-2010-IFI", "Groeller-2010-IVVI", "Groeller-2011-HSH", "Groeller-2017-ARTORW", "Groeller-2017-AVC", "Groeller-2017-IVAMCS", "Groeller-2017-PTPMD", "Groller_2021-12-03", "Gronde_2008", "Grorller-2010-IVV", "grossmann_2019_pelvisrunner_poster", "Grossmann_MA", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", "grossmann-thesis", "gruber-2025-vps", "Gruenauer-2011-CAT", "Gschwantner_2011_AMQ", "gundacker-2020-wlm", "Gurbat_2011_SBS", "gusenbauer-2018", "gusenbauer-2018", "gusenbauer-2018-P", "gutekunst_2019", "Hadwiger-2002-Fas", "haidacher_2010_statTF", "haidacher-2004-FVV", "haidacher-2005-MND", "haidacher-2007-idr", "haidacher-2008-vcbm", "haidacher-2011-MSM", "haidacher-2011-phd", "haidacher-2011-VAM", "Hainoun2019", "Halladjian_2020", "hanzl-2011", "hartl-2008-vcd", "hartmann-2005-adv", "haushofer-2018-skinning", "Heim_2020", "Heim_2021", "Heim-2017", "heim-2024-accustripes", "heim-gall-2020-dde", "heinzl_2006_RSDVCDM", "heinzl-2006-rep", "heinzl-2008-sam", "Heinzl2021", "Herghelegiu-2012-BPV", "herzberger-2023-swv", "herzberger-2024-roh", "Hirsch_Christian_2015_ABL", "Hladuvka-2002-Exp", "hladuvka-2002-exploiting", "Hochmayr_Manuel_2015_PSE", "hochmayr_manuel-2011-VoRMD", "Hochpoechler_2016_VR", "horvath-2018-ism", "hromniak-2019-vcn", "huber-2025-eed", "Iijima-2020-iV", "indirectBiasLanguageModels-2023", "irendorfer-2024-uat", "irger-2023-ves", "Ismail-2018", "jank-2022-cbf", "Kanitsar-2002-CPR", "Kanitsar-2003-Adva", "Kanitsar-2003-Dem", "Kanitsar-2004-Dia", "Kanitsar-thesis", "kapferer-2017-godot", "Karall2017CVAB", "Karall2018_2", "karimov-2013-vivisection", "karimov-2015-HD", "karimov-2016-GIVE", "karimov-2016-SD", "keglevic_schulz-2011-MB", "Kehrer-2008-hyp", "Kehrer-2010-mom", "kehrer-2011-vai", "kehrer-2012-mod", "kehrer-2013-IVA", "kehrer-2013-SBC", "Kehrer-2013-STAR", "Kehrer-2014-CSD", "kerbl-2024-ah3", "kimmersdorfer-fancyMaps-2023", "Kinkelin_2009", "Kinkelin-2011-VR", "Klaus2024", "Kleber-2004-TFE", "klein_2017_IM", "klein_2019_MSA_Poster", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "Klein_Tobias_2015TIV", "klein-thesis", "Knapp_2017_CVR", "knapp_michael_2004_MAS", "knapp-2004-semi", "koch_bernhard_2018-1", "koch-2018-sso", "koehle-2013-sgv", "koeppel-2021", "Koeppel2020", "Kohlmann-2007-EBV", "kohlmann-2007-livesync", "kohlmann-2008-lse", "kohlmann-2009-cp", "kohlmann-2009-lssl", "kolesar-ivan-2014-polymers", "Kolter_2021", "komon-2025-dco", "komon-2025-webigeo", "komon-2025-webigeo", "komon-kimmersdorfer-2025-weBIGeo", "Konyha_2013_IVA", "korpitsch_thorsten-2019", "korpitsch-2020-cescg", "Korpitsch-2020-wscg", "korpitsch-2021-lov", "Koszticsak-2017-ewt", "Kouril_2017_11", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2018-LoL", "kouril-2018-LoL", "kouril-2020-hyperlabels", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kovacs_PhD", "krakhofer-2015", "Krone2016VABC", "kuehschelm-2005-adv", "Kugler_2019", "Kuroko-2020-iV", "Labschuetz_Matthias_2015_JIT", "Labschuetz_Matthias_2016_AHD", "Labschuetz_Matthias_2016_JIT", "Labschuetz_Matthias_2016_JITT", "Lackner_2022", "LaCruz2004", "Ladstaedter-2009-sim", "Langer_Edith_IR1", "Langer_Maximillian_DMV", "Laschober-2018", "lawonn-2018-illvisstar", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "LeMuzic_2016_PhD", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lemuzic-mindek-sorger-cgfcc", "Leutschacher_2022", "li-2019-gdc", "lie-2009-cri", "lipp-2017-mgpu", "lipp-2017-vulkan", "lippeck-2022-mna", "liu-2014-ac", "lkoell-2014", "ludwig-2012-MT", "Machegger2018DTI", "magg-2021-dva", "magg2021", "mahler-2021-mdar", "major-2010-mrf", "malan_fluoro", "malik-2007-FP", "malik-2009-CVFA", "malik-thesis", "Manczarski-2016", "Marek06", "Maricic_2013_VFE", "martorell2022", "maruyama-2019-iv", "Masopust_2018", "Masterthesis-Viola", "Matkovic_Kresimir_2015_", "matt-2023-vae", "matt-2024-cvil", "matt-2025-scv", "matt-masterthesis", "Mattausch-2003-ISL", "Mattausch-2003-SIE", "Mattausch-2003-Str", "Matusich-2017-01", "Mautner 2020", "Mayr-2017-1", "mayr-2021-wec", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "Mazza_2020", "Mazza_2021_05", "meka-2024-lpi", "Melo_2018_11", "Meusburger_2020", "Miao_2015_VCBM", "Miao_2019", "Miao_Haichao_2015_VQC", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_plitvice_2018", "miao_thesis_2019", "miao_tvcg_2017", "miao_tvcg_2018", "miao_tvcg_2018", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "Michl_2017_CSV", "mindek_peter-2012-visgroupproj", "mindek_peter-2014-cs_kaust", "mindek-2013-cs_cvut", "mindek-2013-csl", "mindek-2013-pel", "mindek-2014-mcs", "mindek-2014-vivi_cvut", "mindek-2015-mc", "mindek-2015-mctalk", "mindek-2016-utah-talk", "mindek-2017-dsn", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-2019-mci", "mindek-thesis", "mistelbauer_2013_SIV", "Mistelbauer_2021", "Mistelbauer_Gabriel_2015_NHR", "Mistelbauer_Gabriel_2016", "mistelbauer-2010-pvv", "mistelbauer-2012-cr", "mistelbauer-2012-ssv", "mistelbauer-2013-cfa", "mistelbauer-2015-abvv", "Mitterhofer_2017", "mizuno-2019-eurovis", "Mlejnek_2004_PF", "Mlejnek_2005_AOEPF", "Mlejnek_2006_MVOA", "Mlejnek-2004-Int", "Mlejnek-2004-ITVAC", "Mlinaric-2015-MT", "Moellinger_Christian_IDE2", "moerth_eric-2016-3DF", "moerth-2018-tpose", "monitzer_2008_FluSi", "Morar_2012_ISB", "Muehlbacher_diss_2018", "mueller-2009-ivs", "Muigg_2011_ISI", "Muigg_2011_VC", "Muigg-2008-four", "muigg-2012-svr", "musleh-2024-conan", "muth-2026-clouds", "Neumann-2002-Fea", "nguyen_2020-covid", "Niedermayer_2018", "Novotny_2013_ASVD", "Nowak_2020", "Nowak_2021", "Oancea_2018_1", "Oancea_Stefan_2016_VOT", "Oancea2018OAK", "oeltze-2013-tut", "opitz-2009-cvv", "Ortner_PhD", "Ortner2020", "Pahr_PhD", "pahr-2021-vologram", "pahr-2024-ieo", "pahr-2024-squishicalization", "pahr-2025-holographs", "pahr-2025-nodkant", "Pahr2020", "Pajer_2012_VoM", "Panayotov", "papantonakis-2024-rmf", "Parzer_2013_IIG", "patel_2009_MC", "patel_daniel_2007_IRSD", "patel-2008-tsa", "patel-2009-evr", "patel-2011-PEA", "Pauschenwein_2022", "Peter_2012_AIV", "Pezenka-2016-MT", "Pfahler_David_2015_IPI", "Pfahler-2016-MT", "PH-2011-LDS", "phd-viola", "Philipp_Hochhauser_2023", "Pilizar_-2020-bachelor", "piringer-2009-hds", "Plank_Pascal_2015_HVP", "plank-2017-sldg", "PMI_AR_2012", "pointner_simon-2020", "polatsek-2018-stv", "polatsek-2018-stv", "Pramerdorfer-2011-PAV", "preim-2009-sve", "Presch_2020", "Priselac2021", "puehringer-2009-sbm", "puenguentzky-2014-ht", "Purchase-2020-gd", "raidou_2018_bladderrunner", "raidou_2019_pelvisrunner", "raidou_2019_preha", "raidou_2019_springer", "raidou_2020Onc", "raidou_EuroVis15", "raidou_eurovis16", "raidou_miccai16", "raidou_pingu2020", "raidou_previs2021", "raidou_RO2019", "raidou_shonan167", "raidou_slicedice", "raidou_star2019", "raidou_vcbm14", "raidou_vis14", "raidou_vis15", "raidou_visgap2020", "raidou2018_rv3", "raidou2018visualflatter", "raidou2019_prsps", "rasch-2016-imgses", "Rau08", "Rautek_Peter_2014_TUC", "Rautek_Peter_2014_VSA", "rautek-2005-dvr", "Rautek-2007-O3D", "Rautek-2007-SLI", "Rautek-2008-IDS", "Rautek-2008-kav", "Rautek-2008-VF", "rautek-2009-vmv", "RAUTEK06", "Rautek06Vis", "Rautek06VMLS", "rautek2010", "Red_Andreas_2015_FFT", "Reh_Andreas_VoP", "reh-2013", "reina-2020-mtv", "Reisacher_Matthias_CPW", "Reisacher2016", "Reiter_2009_IXIA", "Reiter2017CVAP", "Rezk06Vis", "Ribicic_2012_SUS", "Ribicic_2012_VAS", "Ribicic-2010-CRS", "Riegelnegg_2019", "rinortner_susanne-2019-vpicc", "rinortner_susanne-2019-vpicc", "Rippberger_2019", "rippl-2023-atg", "ritzberger-2010-nar", "Ropinski-2012-UBT", "rozana-2026-vcfd", "rraidou_clinical", "rraidou_EG17", "rraidou_phdbook", "rsabin-2013", "ruiz-2008-OVR", "ruiz-2008-SEV", "samoul-2019-cnp", "Sanjin_Rados_RV", "Sarkis_2021", "Sbardellati-2019-vcbm", "Sbardellati-2019-vcbm", "sbardellati-2021-eveos", "scharsach-2005-adv", "Schernthaner-2017-MCP", "schindler_2020vis", "Schindler-2022-eurovis", "schindler2020", "schleicher-2011-VLSC", "Schmidlehner_Sandra_SbC", "schmidlehner2021", "schmidt-2011-mt", "schmidt-phd", "schmidt-phd", "schoellhuber-2008-asc", "scholz_2021", "Schrempf_2018", "Schrempf_2020", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "schuh-2018-mesh-blending", "schultes_lampi", "Schulze_Florian_2013_CMI", "schwankl-2013-smis", "seyfert-2017", "shakhova-2023-atp", "sietzen-2019-wnn", "sietzen-2019-wnn", "sietzen-2021-perturber", "sietzen-2022-vacnnr", "sietzen-ifv-2019", "sifuentes-2018-crowd", "SifuentesGangl2017FIS", "sikachev_peter_2010_STLCI", "sikachev_peter-2011-dfc", "sikachev_peter-2011-incshad", "sikachev_peter-2011-metavis", "sikachev_peter-2011-protovis", "sikachev-2010-DFC", "sikachev-2010-ill_vis_vol_ren", "Sippl_Sebastian_EFG", "smiech-2018-tei", "Smisek_Michal_A3D", "Sollboeck_2011_FSS", "sollboeck-2011", "Solteszova-2009-VQN", "solteszova-2010-MOS", "Solteszova2016", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "sorger-2019-odn", "sorger-2021-egonet", "Soros_AVN_2011", "Soros-AV-2010", "Spechtenhauser_Florian_2016", "spegel-gruenberger-2020", "Spelitz2020", "spoerk-2010-hpgpu", "Stabel_2012_UDM", "stappen_2017_animatedcomic", "Staudacher_2022", "staudacher_florian-2016-topo3d", "stehno-2011-RVD", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "STEINLECHNER-2019-ICT", "StickmanMax-shoetta-kampfer", "stoff-2025-pvu", "stoff-concepMap-2021", "StrakaVis2004", "stritzel2022", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "suntinger-2008-etet", "suntinger-2008-tet", "Swoboda_Nicolas_VIT", "Swoboda2020", "szabo_patrik-2022-tour", "szabo-thesis", "takahashi-2019-acdt", "tekaya-2025-amo", "tekaya-2025-amo", "termeer-2006-000", "termeer-2007-covicad", "termeer-2008-scmr", "termeer-2008-vis", "termeer-2009-cvc", "termeer-2009-scmr", "textures-3d-printing", "thesis-kronsteiner", "thesis-tekaya", "Thomas-2018", "Thurner-2005-IVR", "toth-2007-ndd", "TR-186-2-05-01", "TR-186-2-05-02", "TR-186-2-05-03", "TR-186-2-05-04", "TR-186-2-05-06", "TR-186-2-05-07", "TR-186-2-05-08", "TR-186-2-06-01", "TR-186-2-06-02", "TR-186-2-06-03", "TR-186-2-06-04", "TR-186-2-07-02", "TR-186-2-07-03", "TR-186-2-07-04", "TR-186-2-07-05", "TR-186-2-07-06", "TR-186-2-07-07", "TR-186-2-07-08", "TR-186-2-07-10", "TR-186-2-07-11", "TR-186-2-07-12", "TR-186-2-08-01", "TR-186-2-08-02", "TR-186-2-08-03", "TR-186-2-08-04", "TR-186-2-08-05", "TR-186-2-08-06", "TR-186-2-08-07", "TR-186-2-08-08", "TR-186-2-08-10", "TR-186-2-08-11", "TR-186-2-08-12", "TR-186-2-08-14", "TR-186-2-09-01", "TR-186-2-15-03", "TR1862162", "Tramberger_2018", "Tramberger2017BCS", "Trautner_Thomas_2014_VAE", "trautner-2018-imd", "trautner-2018-imd", "travnicek-2017-thm", "Trenkwalder-2004-MAR", "tretyak-2025-tacmedvr", "Troidl_2019", "Troidl_2021", "Troidl_2022", "turner-aso", "tut-eg-2006", "tut-siggraph-2006", "tut-vis-2006", "tut-vis-2007", "tweebo-2014", "ulschmid-2024-reo", "ulschmid-2025-apc", "unger_2017", "unger-2019_vcp", "Unger2020", "unterguggenberger-2024-fropo", "usul-thesis", "vad_2015_phd", "Vad_Viktor_2015_RVV", "vad-2016-bre", "vaico", "varchola_andrej-2012-fetoscopic", "Vasileva_2022", "Vasileva-2018", "vessel2003", "Viola_2013_IDV", "Viola_Ivan_2013_CAI", "Viola_Ivan_2013_D3D", "Viola_Ivan_2013_DC", "Viola_Ivan_2013_GS", "Viola_Ivan_2013_HQ3", "Viola_Ivan_2013_RMA", "Viola_Ivan_2013_RSb", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_DAC", "Viola_Ivan_IIP", "Viola_Ivan_UVP", "Viola_Ivan_VDP", "Viola-05-Smart", "Viola-2003-GPU", "Viola-2003-Har", "viola-2003-hbn", "Viola-2003-NON", "viola-2004-gbf", "Viola-2004-GPU", "viola-2004-har", "viola-2004-har2", "viola-2004-idv", "viola-2004-imp", "Viola-2004-ImpX", "Viola-2004-ImpX2", "viola-2005-imp", "viola-2006-FoA", "viola-evr", "Viola-Pondering-2017", "viola-popular-article-2006", "Viola-vistutillustrativevis", "vis-foa", "VisWeek-Tutorial-2012-Uncertainty", "vitruvian_2019", "voglreiter-2023-tro", "Vucenovic_2022", "vucini_2006", "vucini_2008_rnp", "vucini_2009", "vucini_erald-2007-FRI", "vucini-2009-phd", "vucini-2011", "Wagner_032017", "walchhofer_ar_flowmaps", "walchhofer-tso", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "Waldin_Nicholas_2017_FlickerObserver", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2017-thesis", "waldin-2019-ccm", "waldin-2019-ccm", "Waldner_2017_11", "Waldner_2017_11", "waldner-2013-facetCloudsGI", "waldner-2013-ubiWM", "waldner-2014-af", "waldner-2014-ghi", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "waser_2011_VSD", "Waser-2010-WL", "webGPU_aggregateVis-2023", "weiner_2011", "Weissenboeck_2019", "Weissenboeck_2019_PhD", "weissenboeck-2014", "Wihann_2017", "wolf-2023-cc", "wolf-2024-jhd", "Woschizka_2021", "wu-2017-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-shonan", "wu-2018-story", "wu-2019-bmc", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-smwp", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg", "wu-2021", "wu-2021-vi", "xmastree2002", "xmastree2005", "ymca", "YOGHOURDJIAN2019", "Zambal-2003-SWA", "zambal-2005-3dact", "Zaufel_2021", "zauner-2013-svkinect", "zechmeister2020", "Zeng_2021", "Zhu-2014-flowvis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Workgroup&id=vis", "__class": "Workgroup" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2021/kouril-2021-molecumentary/", "__class": "Publication" }, { "id": "Zeng_2021", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": null, "title": "Data-Driven Colormap Adjustment for Exploring Spatial Variations in Scalar Fields", "date": "2021-09-01", "abstract": "Colormapping is an effective and popular visualization technique for analyzing patterns in scalar fields. Scientists usually adjust a default colormap to show hidden patterns by shifting the colors in a trial-and-error process. To improve efficiency, efforts have been made to automate the colormap adjustment process based on data properties (e.g., statistical data value or distribution). However, as the data properties have no direct correlation to the spatial variations, previous methods may be insufficient to reveal the dynamic range of spatial variations hidden in the data. To address the above issues, we conduct a pilot analysis with domain experts and summarize three requirements for the colormap adjustment process. Based on the requirements, we formulate colormap adjustment as an objective function, composed of a boundary term and a fidelity term, which is flexible enough to support interactive functionalities. We compare our approach with alternative methods under a quantitative measure and a qualitative user study (25 participants), based on a set of data with broad distribution diversity. We further evaluate our approach via three case studies with six domain experts. Our method is not necessarily more optimal than alternative methods of revealing patterns, but rather is an additional color adjustment option for exploring data with a dynamic range of spatial variations.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "Image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 576, "image_height": 323, "name": "Zeng_2021-Image.JPG", "type": "image/jpeg", "size": 41637, "path": "Publication:Zeng_2021", "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Zeng_2021/Zeng_2021-Image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2021/Zeng_2021/Zeng_2021-Image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1883, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Quiong", "lastname": "Zeng", "searchname": "Quiong 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Illustrators apply such techniques, for instance, to present non-important parts of an organ in a simplified way, while using detailed representations to put the focus of attention on a region where a tumor might be situated.\n\nTo identify such meaningful visual abstractions for visualization, their effectiveness for human perception and cognition has to be assessed, and they have to be formalized in order to make them applicable in rendering algorithms. 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"xmastree2002", "xmastree2005", "ymca", "YOGHOURDJIAN2019", "Zambal-2003-SWA", "zambal-2005-3dact", "Zaufel_2021", "zauner-2013-svkinect", "zechmeister2020", "Zeng_2021", "Zhu-2014-flowvis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Workgroup&id=vis", "__class": "Workgroup" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2021/Zeng_2021/", "__class": "Publication" }, { "id": "Sarkis_2021", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/138952", "title": "Multiscale Unfolding: Illustratively Visualizing the Whole Genome at a Glance", "date": "2021-03", "abstract": "We present Multiscale Unfolding, an interactive technique for illustratively visualizing multiple hierarchical scales of DNA in a single view, showing the genome at different scales and demonstrating how one scale spatially folds into the next. The DNA’s extremely long sequential structure—arranged differently on several distinct scale levels—is often lost in traditional 3D depictions, mainly due to its multiple levels of dense spatial packing and the resulting occlusion. Furthermore, interactive exploration of this complex structure is cumbersome, requiring visibility management like cut-aways. In contrast to existing temporally controlled multiscale data exploration, we allow viewers to always see and interact with any of the involved scales. For this purpose we separate the depiction into constant-scale and scale transition zones. Constant-scale zones maintain a single-scale representation, while still linearly unfolding the DNA. Inspired by illustration, scale transition zones connect adjacent constant-scale zones via level unfolding, scaling, and transparency. We thus represent the spatial structure of the whole DNA macro-molecule, maintain its local organizational characteristics, linearize its higher-level organization, and use spatially controlled, understandable interpolation between neighboring scales. We also contribute interaction\ntechniques that provide viewers with a coarse-to-fine control for navigating within our all-scales-in-one-view representations and visual \naids to illustrate the size differences. Overall, Multiscale Unfolding allows viewers to grasp the DNA’s structural composition from \nchromosomes to the atoms, with increasing levels of “unfoldedness,” and can be applied in data-driven illustration and communication. 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The visualization working group at TU Wien (vis-group) has been internationally active over more than 25 years. The group has been acting in a competitive scientific setting where sometimes contradicting multiple objectives require trade-offs and optimizations. Research-wise the group has been performing basic and applied research in visualization and visual computing. Teaching-wise the group has been involved in undergraduate and graduate lecturing in (medical) visualization and computer graphics. To be scientifically competitive requires to constantly expose the group and its members to a strong international competition at the highest level. This necessitates to shield the members against the ensuing pressures and demands and provide (emotional) support and encouragement. Internally, the vis-group has developed a unique professional and social interaction culture: work and celebrate, hard and together. This has crystallized into a nested, recursive, and triangular organization model, which concretizes what it takes to make a research group successful. 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"An-2018-CHI", "AndreUrsits_2013_APP", "antes-2023-vhv", "Antonini2020", "arbesser_ba_2023", "Artner-2004-Hig", "Artner-2005-Hig", "Artner-2005-Thesis", "audioflow", "Auzinger_Mistelbauer_2013_CSR", "balabanian-2007-ant", "balabanian-2008-hvv", "Balabanian-2010-IIV", "Balabanian-2010-PSDSV", "Balduz_01", "Basch_2011_ATA", "Bauer_David_2018", "Bauer_Johannes_2014_IWB", "bauer-2015-cbfd", "Bayat_2019", "bayer-2015-gapaot", "bbeer-2013", "Bechtold2020", "Beer_2011_DVE", "Beham_Michael_PSC", "beham-2014-cupid", "bernhard-2006-dvrcta", "bernhard-2014-GTOM", "bernhard-2016-gft", "Bernold_2019", "bernold-2019-epr", "bhore-2021-issac", "birkeland_aasmund_2014_pums", "Birkeland-2012-IMC", "BirsakHanzl-2009", "boeroendy-2022-uio", "boesch_2014_browserHistoryVis", "borgo-2013-gly", "borondy2022", "bouzari-thesis", "bramberger-3pv", "Brandorff-08-OV", "brandorff-2009-erv", "brandstaetter_01", "brandstaetter-2007-vosd", "Brandstaetter2020", "Braunsperger-2025_bsc", "breitenecker-2020-bct", "bront-2023-svo", "brucker-2010-RES", "Bruckner_Stefan_2015_VAS", "bruckner-2004-EVV", "bruckner-2005-AIV", "bruckner-2005-ATI", "bruckner-2005-ICV", "bruckner-2005-vid", "bruckner-2005-VIS", "bruckner-2006-EVV", "bruckner-2006-ICE", "bruckner-2007-EDF", "bruckner-2007-STF", "bruckner-2008-IIV", "bruckner-2008-IVV", "bruckner-2009-BVQ", "bruckner-2009-IVV", "bruckner-2010-HVC", "bruckner-2010-IFC", "bruckner-2010-ISM", "bruckner-2010-SES", "Bruckner-2012-VEA", "buerger_raphael_2006_3dpoly", "Buerger-2007-cmv", "Buerger-2007-eurovis", "buerger-2007-star", "bugnar-esk-2021", "burns-2007-fea", "bydlinski-2015-gapaot", "byska-2019-mdfc", "Cai_2018", "Caic2021", "Carata_2011_IVE", "carbesser-2013", "casellato-2016-pkg", "cellVIEW_2015", "cizmic-2018-evd", "cmolik-2020-tvcg", "Cornel_2020", "Cornel_Daniel_2015_VOC", "Cornel2016CFM", "coto-2005-MAC", "Cruz-thesis", "Csebfalvi-2002-FPVF", "Csebfalvi-2002-SBICG", "Csebfalvi-2002-Smo", "Csebfalvi-2012-IOM", "Csuk_2011", "daae-lampe-2010-dif", "dataset-christmastree", "dataset-present", "dataset-stagbeetle", "Deutsch-2018", "Dhanoa_2021", "dhanoa-2025-ave", "Dhanoa2024", "Diehl_2015", "Diehl_2021", "Diehl-2017-Albero", "Dietrich_1", "dietrich-2016-viseq2", "diss-thesis-bratislava", "diss-thesis-magdeburg", "diss-thesis-siegen", "djuric-2020-wvo", "donabauer_2019_1", "donabauer-2015-asc", "draeger-2005-chain", "dworschak-2016-szcm", "dworschak-2016-szcm", "dworschak-2024-aml", "Eckelt_2017", "Eckelt_2018_01", "Edi_2019_10_01", "edlinger-2018-vwr", "eg-tut2005-iv", "Ehlers_PhD", "ehlers-2023-iro", "ehlers-2024-mmm", "ehlers-2024-vgs", "ehlers-2025-ait", "Eichner2022", "eitler-2024-sos", "eiweck-hnv-2021", "ellhotka-2025-ipo", "emsenhuber-2008-vhd", "erler-2025-lidarscout", "eschner-2023-evl", "eschner-2023-ims", "eschner-2025-ide", "eschner-blur-2022", "Escribano_2017", "Essler2022", "EuroVis2018-ShortPapers-Karall", "EuroVis2018-ShortPapers-Reiter", "facial2004", "Fechter_2011_DBS", "filipovic-2014-dect", "FISCHL-2012-CTASEG", "fmistelbauer-2014-ad", "fmistelbauer-2014-adict", "Ford-2012-HRV", "fourousan2021", "freiler-2008-ste", "fritz-2009-ieq", "Froehler_Berhnard_2015_ESM", "froschauer-2009-iod", "Fruehstueck_Anna_2015_DOM", "fuchs_raphael_2007_par", "fuchs_vhml", "fuchs-2008-del", "fuchs-vortex", "furmanova_2020", "gadllah_2016", "Gadllah_Hani_2016", "gall_2016", "Gall_2017", "gall_alexander_2016BA", "gall-2025-marv", "Gall2020", "Gall2021", "gangl-2018-gpsart", "Ganglberger-2022-cg", "ganglberger2019", "Ganuza", "Ganuza_2015", "Ganuza_MJ_2015_AVe", "Ganuza_ML_2015_ISA", "Ganuza-2017-IVCSGM", "Gavrilescu_2011_VGP", "gavrilescu-2008-vsc", "gavrilescu-2009-postrend", "Gavrilescu-2010-CIE", "Gehrer_Daniel_CUI", "Gehrer-2017", "Gehrer-2017-molmach", "georgiev-2019-cbg", "gerl-2006-vhi", "geymayer-2017-std", "Gietl_2020", "Gillmann2021", "glanznig-2009-LAMC", "glinzner-2016-tex", "goel-2024-rdr", "Gogel2020", "gostler-2015-3dp", "grammatikaki-2025-htr", "grammatikaki-thesis", "grimm-2004-arefined", "GRIMM-2004-FDMX-P", "grimm-2004-memory", "GRIMM-2004-PPC", "grimm-2004-volume", "Groeller_2011_CVC", "Groeller_2011_CW", "Groeller_2011_GBC", "Groeller_2011_HP", "Groeller_2011_HSU", "Groeller_2011_IPV", "Groeller_2011_IVP", "Groeller_2011_NR", "Groeller_2011_NSM", "Groeller_2011_VCD", "Groeller_2011_VSD", "Groeller_2011_VSD", "Groeller_2011_VSD", "Groeller_2011_VSS", "Groeller_2012_KAV", "Groeller_2012_VBP", "Groeller_2012_ViV", "Groeller_2012_VV", "Groeller_2014_CaQ", "Groeller_2014_CQV", "Groeller_2014_CV", "Groeller_2014_RWA", "Groeller_2014_STC", "Groeller_2014_UPS", "Groeller_2014_VND", "Groeller_2016_I2", "Groeller_2016_I7", "Groeller_2016_I8", "Groeller_2016_P2", "Groeller_2016_P4", "Groeller_2016_P6", "Groeller_2016_P7", "Groeller_2021_11", "Groeller_2021_BVM", "Groeller_2021-10", "Groeller_Edi_2013_TVC", "Groeller_Edi_2013_VCQ", "Groeller_Edi_2013TVCK", "Groeller_Edi_VKA", "Groeller_Eduard_2014_THS", "Groeller_Eduard_2014_TSP", "Groeller_Eduard_2014_UCT", "Groeller_Eduard_2015_SMV", "Groeller_Eduard_2015_TCU", "Groeller_V1_2020", "Groeller_V2_2020", "Groeller_V3_2020", "Groeller_V42020", "Groeller_V5_2020", "groeller-2004-efficient", "groeller-2004-imp", "groeller-2004-sci", "groeller-2005-dia", "Groeller-2010-CVC", "Groeller-2010-IFI", "Groeller-2010-IVVI", "Groeller-2011-HSH", "Groeller-2017-ARTORW", "Groeller-2017-AVC", "Groeller-2017-IVAMCS", "Groeller-2017-PTPMD", "Groller_2021-12-03", "Gronde_2008", "Grorller-2010-IVV", "grossmann_2019_pelvisrunner_poster", "Grossmann_MA", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", "grossmann-thesis", "gruber-2025-vps", "Gruenauer-2011-CAT", "Gschwantner_2011_AMQ", "gundacker-2020-wlm", "Gurbat_2011_SBS", "gusenbauer-2018", "gusenbauer-2018", "gusenbauer-2018-P", "gutekunst_2019", "Hadwiger-2002-Fas", "haidacher_2010_statTF", "haidacher-2004-FVV", "haidacher-2005-MND", "haidacher-2007-idr", "haidacher-2008-vcbm", "haidacher-2011-MSM", "haidacher-2011-phd", "haidacher-2011-VAM", "Hainoun2019", "Halladjian_2020", "hanzl-2011", "hartl-2008-vcd", "hartmann-2005-adv", "haushofer-2018-skinning", "Heim_2020", "Heim_2021", "Heim-2017", "heim-2024-accustripes", "heim-gall-2020-dde", "heinzl_2006_RSDVCDM", "heinzl-2006-rep", "heinzl-2008-sam", "Heinzl2021", "Herghelegiu-2012-BPV", "herzberger-2023-swv", "herzberger-2024-roh", "Hirsch_Christian_2015_ABL", "Hladuvka-2002-Exp", "hladuvka-2002-exploiting", "Hochmayr_Manuel_2015_PSE", "hochmayr_manuel-2011-VoRMD", "Hochpoechler_2016_VR", "horvath-2018-ism", "hromniak-2019-vcn", "huber-2025-eed", "Iijima-2020-iV", "indirectBiasLanguageModels-2023", "irendorfer-2024-uat", "irger-2023-ves", "Ismail-2018", "jank-2022-cbf", "Kanitsar-2002-CPR", "Kanitsar-2003-Adva", "Kanitsar-2003-Dem", "Kanitsar-2004-Dia", "Kanitsar-thesis", "kapferer-2017-godot", "Karall2017CVAB", "Karall2018_2", "karimov-2013-vivisection", "karimov-2015-HD", "karimov-2016-GIVE", "karimov-2016-SD", "keglevic_schulz-2011-MB", "Kehrer-2008-hyp", "Kehrer-2010-mom", "kehrer-2011-vai", "kehrer-2012-mod", "kehrer-2013-IVA", "kehrer-2013-SBC", "Kehrer-2013-STAR", "Kehrer-2014-CSD", "kerbl-2024-ah3", "kimmersdorfer-fancyMaps-2023", "Kinkelin_2009", "Kinkelin-2011-VR", "Klaus2024", "Kleber-2004-TFE", "klein_2017_IM", "klein_2019_MSA_Poster", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "Klein_Tobias_2015TIV", "klein-thesis", "Knapp_2017_CVR", "knapp_michael_2004_MAS", "knapp-2004-semi", "koch_bernhard_2018-1", "koch-2018-sso", "koehle-2013-sgv", "koeppel-2021", "Koeppel2020", "Kohlmann-2007-EBV", "kohlmann-2007-livesync", "kohlmann-2008-lse", "kohlmann-2009-cp", "kohlmann-2009-lssl", "kolesar-ivan-2014-polymers", "Kolter_2021", "komon-2025-dco", "komon-2025-webigeo", "komon-2025-webigeo", "komon-kimmersdorfer-2025-weBIGeo", "Konyha_2013_IVA", "korpitsch_thorsten-2019", "korpitsch-2020-cescg", "Korpitsch-2020-wscg", "korpitsch-2021-lov", "Koszticsak-2017-ewt", "Kouril_2017_11", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2018-LoL", "kouril-2018-LoL", "kouril-2020-hyperlabels", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kovacs_PhD", "krakhofer-2015", "Krone2016VABC", "kuehschelm-2005-adv", "Kugler_2019", "Kuroko-2020-iV", "Labschuetz_Matthias_2015_JIT", "Labschuetz_Matthias_2016_AHD", "Labschuetz_Matthias_2016_JIT", "Labschuetz_Matthias_2016_JITT", "Lackner_2022", "LaCruz2004", "Ladstaedter-2009-sim", "Langer_Edith_IR1", "Langer_Maximillian_DMV", "Laschober-2018", "lawonn-2018-illvisstar", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "LeMuzic_2016_PhD", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lemuzic-mindek-sorger-cgfcc", "Leutschacher_2022", "li-2019-gdc", "lie-2009-cri", "lipp-2017-mgpu", "lipp-2017-vulkan", "lippeck-2022-mna", "liu-2014-ac", "lkoell-2014", "ludwig-2012-MT", "Machegger2018DTI", "magg-2021-dva", "magg2021", "mahler-2021-mdar", "major-2010-mrf", "malan_fluoro", "malik-2007-FP", "malik-2009-CVFA", "malik-thesis", "Manczarski-2016", "Marek06", "Maricic_2013_VFE", "martorell2022", "maruyama-2019-iv", "Masopust_2018", "Masterthesis-Viola", "Matkovic_Kresimir_2015_", "matt-2023-vae", "matt-2024-cvil", "matt-2025-scv", "matt-masterthesis", "Mattausch-2003-ISL", "Mattausch-2003-SIE", "Mattausch-2003-Str", "Matusich-2017-01", "Mautner 2020", "Mayr-2017-1", "mayr-2021-wec", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "Mazza_2020", "Mazza_2021_05", "meka-2024-lpi", "Melo_2018_11", "Meusburger_2020", "Miao_2015_VCBM", "Miao_2019", "Miao_Haichao_2015_VQC", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_plitvice_2018", "miao_thesis_2019", "miao_tvcg_2017", "miao_tvcg_2018", "miao_tvcg_2018", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "Michl_2017_CSV", "mindek_peter-2012-visgroupproj", "mindek_peter-2014-cs_kaust", "mindek-2013-cs_cvut", "mindek-2013-csl", "mindek-2013-pel", "mindek-2014-mcs", "mindek-2014-vivi_cvut", "mindek-2015-mc", "mindek-2015-mctalk", "mindek-2016-utah-talk", "mindek-2017-dsn", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-2019-mci", "mindek-thesis", "mistelbauer_2013_SIV", "Mistelbauer_2021", "Mistelbauer_Gabriel_2015_NHR", "Mistelbauer_Gabriel_2016", "mistelbauer-2010-pvv", "mistelbauer-2012-cr", "mistelbauer-2012-ssv", "mistelbauer-2013-cfa", "mistelbauer-2015-abvv", "Mitterhofer_2017", "mizuno-2019-eurovis", "Mlejnek_2004_PF", "Mlejnek_2005_AOEPF", "Mlejnek_2006_MVOA", "Mlejnek-2004-Int", "Mlejnek-2004-ITVAC", "Mlinaric-2015-MT", "Moellinger_Christian_IDE2", "moerth_eric-2016-3DF", "moerth-2018-tpose", "monitzer_2008_FluSi", "Morar_2012_ISB", "Muehlbacher_diss_2018", "mueller-2009-ivs", "Muigg_2011_ISI", "Muigg_2011_VC", "Muigg-2008-four", "muigg-2012-svr", "musleh-2024-conan", "muth-2026-clouds", "Neumann-2002-Fea", "nguyen_2020-covid", "Niedermayer_2018", "Novotny_2013_ASVD", "Nowak_2020", "Nowak_2021", "Oancea_2018_1", "Oancea_Stefan_2016_VOT", "Oancea2018OAK", "oeltze-2013-tut", "opitz-2009-cvv", "Ortner_PhD", "Ortner2020", "Pahr_PhD", "pahr-2021-vologram", "pahr-2024-ieo", "pahr-2024-squishicalization", "pahr-2025-holographs", "pahr-2025-nodkant", "Pahr2020", "Pajer_2012_VoM", "Panayotov", "papantonakis-2024-rmf", "Parzer_2013_IIG", "patel_2009_MC", "patel_daniel_2007_IRSD", "patel-2008-tsa", "patel-2009-evr", "patel-2011-PEA", "Pauschenwein_2022", "Peter_2012_AIV", "Pezenka-2016-MT", "Pfahler_David_2015_IPI", "Pfahler-2016-MT", "PH-2011-LDS", "phd-viola", "Philipp_Hochhauser_2023", "Pilizar_-2020-bachelor", "piringer-2009-hds", "Plank_Pascal_2015_HVP", "plank-2017-sldg", "PMI_AR_2012", "pointner_simon-2020", "polatsek-2018-stv", "polatsek-2018-stv", "Pramerdorfer-2011-PAV", "preim-2009-sve", "Presch_2020", "Priselac2021", "puehringer-2009-sbm", "puenguentzky-2014-ht", "Purchase-2020-gd", "raidou_2018_bladderrunner", "raidou_2019_pelvisrunner", "raidou_2019_preha", "raidou_2019_springer", "raidou_2020Onc", "raidou_EuroVis15", "raidou_eurovis16", "raidou_miccai16", "raidou_pingu2020", "raidou_previs2021", "raidou_RO2019", "raidou_shonan167", "raidou_slicedice", "raidou_star2019", "raidou_vcbm14", "raidou_vis14", "raidou_vis15", "raidou_visgap2020", "raidou2018_rv3", "raidou2018visualflatter", "raidou2019_prsps", "rasch-2016-imgses", "Rau08", "Rautek_Peter_2014_TUC", "Rautek_Peter_2014_VSA", "rautek-2005-dvr", "Rautek-2007-O3D", "Rautek-2007-SLI", "Rautek-2008-IDS", "Rautek-2008-kav", "Rautek-2008-VF", "rautek-2009-vmv", "RAUTEK06", "Rautek06Vis", "Rautek06VMLS", "rautek2010", "Red_Andreas_2015_FFT", "Reh_Andreas_VoP", "reh-2013", "reina-2020-mtv", "Reisacher_Matthias_CPW", "Reisacher2016", "Reiter_2009_IXIA", "Reiter2017CVAP", "Rezk06Vis", "Ribicic_2012_SUS", "Ribicic_2012_VAS", "Ribicic-2010-CRS", "Riegelnegg_2019", "rinortner_susanne-2019-vpicc", "rinortner_susanne-2019-vpicc", "Rippberger_2019", "rippl-2023-atg", "ritzberger-2010-nar", "Ropinski-2012-UBT", "rozana-2026-vcfd", "rraidou_clinical", "rraidou_EG17", "rraidou_phdbook", "rsabin-2013", "ruiz-2008-OVR", "ruiz-2008-SEV", "samoul-2019-cnp", "Sanjin_Rados_RV", "Sarkis_2021", "Sbardellati-2019-vcbm", "Sbardellati-2019-vcbm", "sbardellati-2021-eveos", "scharsach-2005-adv", "Schernthaner-2017-MCP", "schindler_2020vis", "Schindler-2022-eurovis", "schindler2020", "schleicher-2011-VLSC", "Schmidlehner_Sandra_SbC", "schmidlehner2021", "schmidt-2011-mt", "schmidt-phd", "schmidt-phd", "schoellhuber-2008-asc", "scholz_2021", "Schrempf_2018", "Schrempf_2020", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "schuh-2018-mesh-blending", "schultes_lampi", "Schulze_Florian_2013_CMI", "schwankl-2013-smis", "seyfert-2017", "shakhova-2023-atp", "sietzen-2019-wnn", "sietzen-2019-wnn", "sietzen-2021-perturber", "sietzen-2022-vacnnr", "sietzen-ifv-2019", "sifuentes-2018-crowd", "SifuentesGangl2017FIS", "sikachev_peter_2010_STLCI", "sikachev_peter-2011-dfc", "sikachev_peter-2011-incshad", "sikachev_peter-2011-metavis", "sikachev_peter-2011-protovis", "sikachev-2010-DFC", "sikachev-2010-ill_vis_vol_ren", "Sippl_Sebastian_EFG", "smiech-2018-tei", "Smisek_Michal_A3D", "Sollboeck_2011_FSS", "sollboeck-2011", "Solteszova-2009-VQN", "solteszova-2010-MOS", "Solteszova2016", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "sorger-2019-odn", "sorger-2021-egonet", "Soros_AVN_2011", "Soros-AV-2010", "Spechtenhauser_Florian_2016", "spegel-gruenberger-2020", "Spelitz2020", "spoerk-2010-hpgpu", "Stabel_2012_UDM", "stappen_2017_animatedcomic", "Staudacher_2022", "staudacher_florian-2016-topo3d", "stehno-2011-RVD", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "STEINLECHNER-2019-ICT", "StickmanMax-shoetta-kampfer", "stoff-2025-pvu", "stoff-concepMap-2021", "StrakaVis2004", "stritzel2022", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "suntinger-2008-etet", "suntinger-2008-tet", "Swoboda_Nicolas_VIT", "Swoboda2020", "szabo_patrik-2022-tour", "szabo-thesis", "takahashi-2019-acdt", "tekaya-2025-amo", "tekaya-2025-amo", "termeer-2006-000", "termeer-2007-covicad", "termeer-2008-scmr", "termeer-2008-vis", "termeer-2009-cvc", "termeer-2009-scmr", "textures-3d-printing", "thesis-kronsteiner", "thesis-tekaya", "Thomas-2018", "Thurner-2005-IVR", "toth-2007-ndd", "TR-186-2-05-01", "TR-186-2-05-02", "TR-186-2-05-03", "TR-186-2-05-04", "TR-186-2-05-06", "TR-186-2-05-07", "TR-186-2-05-08", "TR-186-2-06-01", "TR-186-2-06-02", "TR-186-2-06-03", "TR-186-2-06-04", "TR-186-2-07-02", "TR-186-2-07-03", "TR-186-2-07-04", "TR-186-2-07-05", "TR-186-2-07-06", "TR-186-2-07-07", "TR-186-2-07-08", "TR-186-2-07-10", "TR-186-2-07-11", "TR-186-2-07-12", "TR-186-2-08-01", "TR-186-2-08-02", "TR-186-2-08-03", "TR-186-2-08-04", "TR-186-2-08-05", "TR-186-2-08-06", "TR-186-2-08-07", "TR-186-2-08-08", "TR-186-2-08-10", "TR-186-2-08-11", "TR-186-2-08-12", "TR-186-2-08-14", "TR-186-2-09-01", "TR-186-2-15-03", "TR1862162", "Tramberger_2018", "Tramberger2017BCS", "Trautner_Thomas_2014_VAE", "trautner-2018-imd", "trautner-2018-imd", "travnicek-2017-thm", "Trenkwalder-2004-MAR", "tretyak-2025-tacmedvr", "Troidl_2019", "Troidl_2021", "Troidl_2022", "turner-aso", "tut-eg-2006", "tut-siggraph-2006", "tut-vis-2006", "tut-vis-2007", "tweebo-2014", "ulschmid-2024-reo", "ulschmid-2025-apc", "unger_2017", "unger-2019_vcp", "Unger2020", "unterguggenberger-2024-fropo", "usul-thesis", "vad_2015_phd", "Vad_Viktor_2015_RVV", "vad-2016-bre", "vaico", "varchola_andrej-2012-fetoscopic", "Vasileva_2022", "Vasileva-2018", "vessel2003", "Viola_2013_IDV", "Viola_Ivan_2013_CAI", "Viola_Ivan_2013_D3D", "Viola_Ivan_2013_DC", "Viola_Ivan_2013_GS", "Viola_Ivan_2013_HQ3", "Viola_Ivan_2013_RMA", "Viola_Ivan_2013_RSb", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", 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"https://www.cg.tuwien.ac.at/research/publications/2021/wu-2021-vi/", "__class": "Publication" }, { "id": "wu-2020-tvcg", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/140950", "title": "Multi-level Area Balancing of Clustered Graphs", "date": "2020-11-17", "abstract": "We present a multi-level area balancing technique for laying out clustered graphs to facilitate a comprehensive understanding of the complex relationships that exist in various fields, such as life sciences and sociology. Clustered graphs are often used to model relationships that are accompanied by attribute-based grouping information. Such information is essential for robust data analysis, such as for the study of biological taxonomies or educational backgrounds. Hence, the ability to smartly arrange textual labels and packing graphs within a certain screen space is therefore desired to successfully convey the attribute data . Here we propose to hierarchically partition the input screen space using Voronoi tessellations in multiple levels of detail. In our method, the position of textual labels is guided by the blending of constrained forces and the forces derived from centroidal Voronoi cells. The proposed algorithm considers three main factors: (1) area balancing, (2) schematized space partitioning, and (3) hairball management. We primarily focus on area balancing, which aims to allocate a uniform area for each textual label in the diagram. We achieve this by first untangling a general graph to a clustered graph through textual label duplication, and then coupling with spanning-tree-like visual integration. We illustrate the feasibility of our approach with examples and then evaluate our method by comparing it with well-known conventional approaches and collecting feedback from domain experts.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "wu-2020-tvcg-image.png", "type": "image/png", "size": 85239, "path": "Publication:wu-2020-tvcg", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-tvcg/wu-2020-tvcg-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-tvcg/wu-2020-tvcg-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1464, "drupal_id": 1266, "orcid_id": "0000-0003-1028-0010", "website": "https://www.cg.tuwien.ac.at/staff/Hsiang-YunWu", 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"ordernum": 0 }, { "publ_id": "vad_2015_phd", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Viola_Ivan_2013_HQ3", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Viola-05-Smart", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "viola-2007-ort", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Viola-Pondering-2017", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "vis-foa", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldin-2017-thesis", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Wihann_2017", "field_id": "supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=171", "__class": "Author" } ], "doi": "https://doi.org/10.1109/TVCG.2020.3038154", "journal": "IEEE Transactions on Visualization and Computer Graphics (TVCG)", "open_access": "yes", "pages_from": "1", "pages_to": "15", "volume": "x", "research_areas": [ { "id": "BioVis", "drupal_id": 4127, "name": "Biological Data Visualization", "short_abstract": "In this research area, we develop new visualization techniques to support biologists in data analysis and create visualizations to disseminate scientific discoveries in biology.", "abstract": "In modern biological research domain experts have to deal with complex and large data collections and simulations. Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n", "website": "https://www.cg.tuwien.ac.at/research/area/BioVis", "teaser": { "name": "teaser.png", "path": "research_area:BioVis", "type": "image/png", "size": 16330957, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/BioVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "amirkhanov-2019-manylands", "byska-2019-mdfc", "cellVIEW_2015", "cmolik-2020-tvcg", "Dietrich_1", "dietrich-2016-viseq2", "Ehlers_PhD", "ehlers-2025-ait", "eschner-2023-ims", "eschner-blur-2022", "Escribano_2017", "Furmanova_2018", "Gehrer-2017", "Gehrer-2017-molmach", "glinzner-2016-tex", "Halladjian_2020", "kapferer-2017-godot", "klein_2017_IM", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koch-2018-sso", "Kolesar-Fractional-2016", "kolesar-ivan-2014-polymers", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kozlikova-Visualization-2016b", "Krone2016VABC", "Kugler_2019", "lemuzic_2015_timelapse", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lipp-2017-mgpu", "lipp-2017-vulkan", "Manczarski-2016", "manylands_award", "Miao_2019", "miao_inria_2017", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-xmas-card-2016", "Mitterhofer_2017", "nguyen_2020-covid", "Nowak_2020", "raidou_2019_springer", "raidou_shonan167", "raidou2018visualflatter", "rasch-2016-imgses", "Reisacher2016", "rinortner_susanne-2019-vpicc", "Sarkis_2021", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2013-neuromap", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "stappen_2017_animatedcomic", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "trautner-2018-imd", "unger-2019_vcp", "vad_2015_phd", "vad_viktor-2017-WVE", "vad-2016-bre", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "waldin-2019-ccm", "waldner-2014-af", "Weissenboeck_2019", "wu-2017-dagstuhl", "wu-2018-metabo", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg" ], "projects": [ "BioNetIllustration", "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=BioVis", "__class": "ResearchArea" }, { "id": "InfoVis", "drupal_id": 4128, "name": "Information Visualization and Visual Analytics", "short_abstract": "In this research area, our focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning. ", "abstract": "

Data and information created by various processes (e.g., simulations) is getting larger, and more and more complex. We use interactive visualization and analysis techniques to facilitate exploration of complex parameter spaces (e.g., to analyze and compare parameters for automotive engineering, reconstruction algorithms, or geometry generators) or unstructured information collections (e.g., annotated digital documents or image collections). Our research focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning.

\r\n", "website": "https://www.cg.tuwien.ac.at/research/area/InfoVis", "teaser": { "name": "teaser.png", "path": "research_area:InfoVis", "type": "image/png", "size": 60875, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/InfoVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "8564188", "arbesser_ba_2023", "Arleo-2019-vis", "Batik-2021", "batik-2021-gd", "bayat-2022-mva", "beham-2014-cupid", "bhore-2021-issac", "birsak-2014-agtb", "birsak-2017-dpe", "borgo-2013-gly", "borondy2022", "Braunsperger-2025_bsc", "Bruckner_Stefan_2015_VAS", "bugnar-esk-2021", "byska-2019-mdfc", "Cai_2018", "casellato-2016-pkg", "Chen-Information-2016", "cizmic-2018-evd", "cmolik-2020-tvcg", "Cornel_2020", "daae-lampe-2010-dif", "Deutsch-2018", "Diehl_2015", "Diehl_2021", "dworschak-2016-szcm", "Eckelt_2018_01", "edlinger-2018-vwr", "ehlers-2024-vgs", "eichner-2024-erv", "eitler-2024-sos", "eiweck-hnv-2021", "ellhotka-2025-ipo", "eschner-2023-evl", "eschner-2025-ide", "Escribano_2017", "fourousan2021", "furmanova_2020", "Gadllah_Hani_2016", "Gall2020", "Ganuza_ML_2015_ISA", "georgiev-2019-cbg", "geyer_lukas_2015_prj", "geymayer-2017-std", "Groeller_2011_CW", "Groeller_2011_NR", "Groeller_2014_RWA", "Groeller_2016_P1", "Groeller_2016_P2", "Groeller_2016_P4", "Groeller_2016_P6", "Groeller_2021-10", "Groeller_V2_2020", "Groeller_V3_2020", "Groeller_V5_2020", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", "gundacker-2020-wlm", "gusenbauer-2018", "gusenbauer-2018-P", "Heim_2021", "heim-2024-accustripes", "heim-gall-2020-dde", "Heinzl2021", "holzer-edo", "hromniak-2019-vcn", "huber-2025-eed", "Iijima-2020-iV", "indirectBiasLanguageModels-2023", "irendorfer-2024-uat", "karnik-09-shapegrammar", "Kehrer-2010-mom", "kehrer-2012-mod", "kehrer-2013-SBC", "Kehrer-2013-STAR", "klaffenboeck-2024-rva", "klaffenboeck-thesis", "Klein_Tobias_2015TIV", "klein-2016-WCL", "knoetzl_alexander-2025-prj", "koeppel-2021", "Kolter_2021", "komon-2025-webigeo", "komon-kimmersdorfer-2025-weBIGeo", "Konyha_2013_IVA", "korpitsch-2021-lov", "Kuroko-2020-iV", "Laschober-2018", "li-2019-gdc", "lippeck-2022-mna", "louis-alexandre_dit_petit-frere-2022-veo", "magg2022", "mahler-2021-mdar", "martorell2022", "maruyama-2019-iv", "Matkovic_Kresimir_2015_", "Matkovic-2014-ieee", "matt-2024-cvil", "matt-2025-scv", "mayr-2021-wec", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "medeiros-2023-gwf", "meka-2024-lpi", "melcher-2024-asi", "Miao_2015_VCBM", "miao_2016_cgf", "Miao_Haichao_2015_VQC", "miao2018Dimsum", "mizuno-2019-eurovis", "Muehlbacher_diss_2018", "musleh_maath_2021_mam", "musleh_maath-2021-mam1", "musleh_maath-2021-mam2", "Musleh_PhD", "musleh-2022-mam5", "musleh-2025-trustme", "Neubauer2020", "Nowak_2021", "ortner-2016-tunnel", "ortner-2016-visaware", "pahr-2024-ieo", "PH-2011-LDS", "Pilizar_-2020-bachelor", "pirch_2021_VRN", "pointner_simon-2020", "polatsek-2018-stv", "Presch_2020", "Priselac2021", "Purchase-2020-gd", "Purgathofer-2017-China1", "Purgathofer-2017-China2", "Purgathofer-2017-VC-Interface", "raidou_2019_pelvisrunner", "raidou_2019_preha", "raidou_2019_springer", "raidou_bestphd", "raidou_EuroVis15", "raidou_eurovis16", "raidou_miccai16", "raidou_pingu2020", "raidou_previs2021", "raidou_vcbm14", "raidou_vis14", "raidou_vis15", "raidou_visgap2020", "raidou2019_prsps", "Ribicic_2012_VAS", "Rippberger_2019", "rozana-2026-vcfd", "sakr_sherif-2020-cacm", "samoul-2019-cnp", "sbardellati-2021-eveos", "schmidt-phd", "sietzen-2019-wnn", "sietzen-2021-perturber", "sietzen-2022-vacnnr", "sietzen-ifv-2019", "sikachev_peter-2011-protovis", "smiech-2018-tei", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger-2013-neuromap", "sorger-2015-litevis", "sorger-2015-taxintec", "sorger-2017-thesis", "sorger-2019-odn", "sorger-2021-egonet", "spegel-gruenberger-2020", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "STEINLECHNER-2019-ICT", "steinschorn-2025-parameter", "stoff-2025-pvu", "stoff-concepMap-2021", "stritzel2022", "Strohmayer-2018-BT", "takahashi-2019-acdt", "tekaya-2025-amo", "Thomas-2018", "TR1862162", "Troidl_2019", "turner-aso", "unger-2019_vcp", "vad_viktor-2017-WVE", "vaico", "Vasileva-2018", "vasileva-2019-smw", "Wagner_032017", "wagner-2024-par", "walchhofer_ar_flowmaps", "waldin-2019-ccm", "waldner-2013-facetCloudsGI", "waldner-2013-ubiWM", "waldner-2014-ghi", "waldner-2017-vph", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "waser_2011_VSD", "webGPU_aggregateVis-2023", "wolf-2023-cc", "wolf-2024-jhd", "wu-2017-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-shonan", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-smwp", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-eurovis-star", "wu-2020-tvcg", "ymca", "YOGHOURDJIAN2019" ], "projects": [ "BioNetIllustration", "d10206", "d10413", "d10450", "d9282", "d9522", "d9555", "deskollage", "Scenario Pool" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=InfoVis", "__class": "ResearchArea" } ], "keywords": [ "Graph drawing", "Voronoi tessellation", "multi-level", "spatially-efficient layout" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "wu-2020-tvcg-image.png", "type": "image/png", "size": 85239, "path": "Publication:wu-2020-tvcg", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-tvcg/wu-2020-tvcg-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-tvcg/wu-2020-tvcg-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "wu-2020-tvcg-paper.pdf", "type": "application/pdf", "size": 48103600, "path": "Publication:wu-2020-tvcg", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-tvcg/wu-2020-tvcg-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-tvcg/wu-2020-tvcg-paper:thumb{{size}}.png" }, { "description": null, "filetitle": "video", "main_file": true, "use_in_gallery": false, "access": "public", "name": "wu-2020-tvcg-video.mov", "type": "video/quicktime", "size": 12802528, "path": "Publication:wu-2020-tvcg", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-tvcg/wu-2020-tvcg-video.mov", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-tvcg/wu-2020-tvcg-video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-tvcg/wu-2020-tvcg-video:video.mp4" } ], "projects_workgroups": [ { "id": "BioNetIllustration", "workgroup_id": "vis", "drupal_id": 4196, "drupal_path": "/research/projects/BioNetIllustration", "name": "BioNetIllustration: User Centric Illustrations of Biological Networks", "name_de": null, "short_title": "BioNetIllustration", "website": null, "status": "active", "short_abstract": "

In living systems, one molecule is commonly involved in several distinct physiological functions. The roles of molecules are commonly summarized in pathway diagrams, which, however, are abstract, hierarchically nested and thus is difficult to comprehend especially by non-expert audience. The primary goal of this research in visualization is to intuitively support the comprehensive understanding of relationships among biological networks using interactively computed illustrations. Illustrations, especially in textbooks of biology are carefully designed to clearly present reactions between organs as well as interactions within cells. Automatic generation of illustrative visualizations of biological networks is thus the technical content of this proposal. Automatic generation of hand-drawn illustrations has been a challenging task due to the difficulty of algorithmically describing a human creative process such as evaluating and selecting significant information and composing meaningful explanations in a visually plausible manner. The project also involves experts from several disciplines including network and medical visualization, data mining, systems biology as well as perceptual psychology. The result will provide a new direction for physiological process analysis and accelerate the knowledge transfer not only within experts but also to the public. Acknowledgment: The project has received funding from the European Union Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 747985.

\r\n", "abstract": "

In living systems, one molecule is commonly involved in several distinct physiological functions. The roles of molecules are commonly summarized in pathway diagrams, which, however, are abstract, hierarchically nested and thus is difficult to comprehend especially by non-expert audience. The primary goal of this research in visualization is to intuitively support the comprehensive understanding of relationships among biological networks using interactively computed illustrations. Illustrations, especially in textbooks of biology are carefully designed to clearly present reactions between organs as well as interactions within cells. Automatic generation of illustrative visualizations of biological networks is thus the technical content of this proposal. Automatic generation of hand-drawn illustrations has been a challenging task due to the difficulty of algorithmically describing a human creative process such as evaluating and selecting significant information and composing meaningful explanations in a visually plausible manner. The project also involves experts from several disciplines including network and medical visualization, data mining, systems biology as well as perceptual psychology. The result will provide a new direction for physiological process analysis and accelerate the knowledge transfer not only within experts but also to the public. Acknowledgment: The project has received funding from the European Union Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 747985.

\r\n", "start_date": "2017-06-21", "end_date": "2019-06-20", "leader_id": 1464, "logo": { "name": "logo.png", "path": "project:BioNetIllustration", "type": "image/png", "size": 16337, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/BioNetIllustration/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "Horizon 2020", "contract_number": "747985", "comment": null } ], "research_areas": [ "BioVis", "InfoVis" ], "publications": [ "cmolik-2020-tvcg", "kouril-2018-LoL", "mizuno-2019-eurovis", "Purchase-2020-gd", "rinortner_susanne-2019-vpicc", "Sbardellati-2019-vcbm", "wu-2017-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-shonan", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg", "YOGHOURDJIAN2019" ], "url": "https://www.cg.tuwien.ac.at/research/projects/BioNetIllustration", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-tvcg/", "__class": "Publication" }, { "id": "Mazza_2020", "type_id": "journalpaper", "tu_id": null, "repositum_id": "20.500.12708/140975", "title": "Homomorphic-Encrypted Volume Rendering", "date": "2020-10-13", "abstract": "Computationally demanding tasks are typically calculated in dedicated data centers, and real-time visualizations also follow this trend. Some rendering tasks, however, require the highest level of confidentiality so that no other party, besides the owner, can read or see the sensitive data. Here we present a direct volume rendering approach that performs volume rendering directly on encrypted volume data by using the homomorphic Paillier encryption algorithm. This approach ensures that the volume data by using the homomorphic Paillier encryption algorithm. This approach ensures that the volume data and rendered image are uninterpretable to the rendering server. Our volume rendering pipeline introduces novel approaches for encrypted-data compositing, interpolation, and opacity modulation, as well as simple transfer function design, where each of these routines maintains the highest level of privacy. We present performance and memory overhead analysis that is associated with our privacy-preserving scheme. Our approach is open and secure by design, as opposed to secure through obscurity. Owners of the data only have to keep their secure key confidential to guarantee the privacy of their volume data and the rendered images. Our work is, to our knowledge, the first privacy-preserving remote volume-rendering approach that does not require that any server involved be trustworthy; even in cases when the server is compromised, no sensitive data will be leaked to a foreign party.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 1871, "image_height": 757, "name": "Mazza_2020-image.JPG", "type": "image/jpeg", "size": 151232, "path": "Publication:Mazza_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Mazza_2020/Mazza_2020-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Mazza_2020/Mazza_2020-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1035, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Sebastian", "lastname": "Mazza", "searchname": "Sebastian Mazza", "is_teacher": false, "name": "Sebastian Mazza", "publications": [ "Mazza_2020", "Mazza_2021_05", "mazza-2012-bakk" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "Mazza_2020", "field_id": "lecturer", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1035", "__class": "Author" }, { "id": 616, "drupal_id": null, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/DanielPatel.html", "firstname": "Daniel", "lastname": "Patel", "searchname": "Daniel Patel", "is_teacher": false, "name": "Daniel Patel", "publications": [ "2013_Viola_Ivan_2013_MTS", "haidacher_2010_statTF", "Mazza_2020", "patel_2009_MC", "patel_daniel_2007_IRSD", "patel-2008-tsa", "patel-2009-evr", "patel-2009-kav", "patel-2010-SVV", "patel-2011-PEA", "solteszova-2010-MOS", "TR-186-2-07-08", "TR-186-2-08-07", "Viola_Ivan_2013_GS", "Viola_Ivan_2013_RSb", "vucini-2011", "xmas-2006" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "patel_2009_MC", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "patel_daniel_2007_IRSD", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "patel-2008-tsa", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "patel-2010-SVV", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "patel-2011-PEA", "field_id": "lecturer", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=616", "__class": "Author" }, { "id": 171, "drupal_id": 168, "orcid_id": "0000-0003-4248-6574", "website": "https://www.cg.tuwien.ac.at/staff/IvanViola", "firstname": "Ivan", "lastname": "Viola", "searchname": "Ivan Viola", "is_teacher": true, "name": "Ivan Viola", "publications": [ "2013_Viola_Ivan_2013_MTS", "Alharbi_2021", "Artner-2004-Hig", "Artner-2005-Hig", "balabanian-2007-ant", "balabanian-2008-hvv", "balabanian-2008-tst", 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With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n", "website": "https://www.cg.tuwien.ac.at/research/area/BioVis", "teaser": { "name": "teaser.png", "path": "research_area:BioVis", "type": "image/png", "size": 16330957, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/BioVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "amirkhanov-2019-manylands", "byska-2019-mdfc", "cellVIEW_2015", "cmolik-2020-tvcg", "Dietrich_1", "dietrich-2016-viseq2", "Ehlers_PhD", "ehlers-2025-ait", "eschner-2023-ims", "eschner-blur-2022", "Escribano_2017", "Furmanova_2018", "Gehrer-2017", "Gehrer-2017-molmach", "glinzner-2016-tex", "Halladjian_2020", "kapferer-2017-godot", "klein_2017_IM", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koch-2018-sso", "Kolesar-Fractional-2016", "kolesar-ivan-2014-polymers", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kozlikova-Visualization-2016b", "Krone2016VABC", "Kugler_2019", "lemuzic_2015_timelapse", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lipp-2017-mgpu", "lipp-2017-vulkan", "Manczarski-2016", "manylands_award", "Miao_2019", "miao_inria_2017", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-xmas-card-2016", "Mitterhofer_2017", "nguyen_2020-covid", "Nowak_2020", "raidou_2019_springer", "raidou_shonan167", "raidou2018visualflatter", "rasch-2016-imgses", "Reisacher2016", "rinortner_susanne-2019-vpicc", "Sarkis_2021", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2013-neuromap", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "stappen_2017_animatedcomic", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "trautner-2018-imd", "unger-2019_vcp", "vad_2015_phd", "vad_viktor-2017-WVE", "vad-2016-bre", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "waldin-2019-ccm", "waldner-2014-af", "Weissenboeck_2019", "wu-2017-dagstuhl", "wu-2018-metabo", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg" ], "projects": [ "BioNetIllustration", "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=BioVis", "__class": "ResearchArea" }, { "id": "IllVis", "drupal_id": 4131, "name": "Illustrative Visualization", "short_abstract": "In this research area, we develop rendering methods that are inspired by scientific illustrations, in order to make complex biological information more intuitive to understand and more pleasant to read.", "abstract": "Scientific illustration is concerned with researching ways in which complex biological and medical data can be abstracted in order to convey a desired information that would otherwise be impossible or hard to retrieve from the original data. Illustrators apply such techniques, for instance, to present non-important parts of an organ in a simplified way, while using detailed representations to put the focus of attention on a region where a tumor might be situated.\n\nTo identify such meaningful visual abstractions for visualization, their effectiveness for human perception and cognition has to be assessed, and they have to be formalized in order to make them applicable in rendering algorithms. In this project, we try to advance the understanding of procedural visual abstraction of complex physiological processes that describe the complex machinery of biological life.", "website": "https://www.cg.tuwien.ac.at/research/area/IllVis", "teaser": { "name": "teaser.jpg", "path": "research_area:IllVis", "type": "image/jpeg", "size": 34861, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/IllVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "antes-2026-maa", "Antonini2020", "Balabanian-2010-IIV", "Balduz_01", "Bayat_2019", "Bechtold2020", "Birkeland-2012-IMC", "brandstaetter_01", "bruckner-2005-ICV", "bruckner-2006-ICE", "bruckner-2007-STF", "bruckner-2008-IIV", "bruckner-2010-HVC", "bruckner-2010-IFC", "cellVIEW_2015", "Chen-Information-2016", "Deutsch-2018", "Dhanoa_2021", "Dhanoa2024", "dietrich-2016-viseq2", "donabauer_2019_1", "eg-tut2005-iv", "eschner-2023-ims", "Essler2022", "gangl-2018-gpsart", "Gehrer_Daniel_CUI", "Gehrer-2017-molmach", "gerl-2006-vhi", "Gogel2020", "Groeller_2011_IPV", "Groeller_2016_I3", "Groeller_2016_I6", "Groeller_2016_I7", "Groeller_2016_I8", "Groeller_V1_2020", "groeller-2006-ivt", "groeller-2007-fci", "groeller-2008-irs", "Groeller-2010-IFI", "gruber-2025-vps", "Halladjian_2020", "haushofer-2018-skinning", "Heim_2020", "horvath-2018-ism", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "Knapp_2017_CVR", "Koeppel2020", "kolesar-ivan-2014-polymers", "Konev-FCV2018", "Koszticsak-2017-ewt", "Kouril_2017_11", "kouril-2020-hyperlabels", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "kroesl_x_card_2017", "Lackner_2022", "Langer_Edith_IR1", "lawonn-2018-illvisstar", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "LeMuzic_2016_PhD", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "Leutschacher_2022", "ludwig-2012-MT", "Manczarski-2016", "Matusich-2017-01", "Mautner 2020", "Mayr-2017-1", "Melo_2018_11", "Meusburger_2020", "Miao_2019", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao2018Dimsum", "Michl_2017_CSV", "mindek-2015-mc", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-2019-mci", "mindek-xmas-card-2016", "Moellinger_Christian_IDE2", "Niedermayer_2018", "Ortner_PhD", "Ortner2020", "pahr-2021-vologram", "Panayotov", "patel_daniel_2007_IRSD", "Pauschenwein_2022", "Peter_2012_AIV", "plank-2017-sldg", "prost-2016-molecule", "purgathofer-2008-cgi", "Radwan-2017-Occ", "Rautek-2007-SLI", "Rautek-2008-IDS", "Rautek-2008-VF", "Reichinger_2016", "Reichinger_Fuhrmann_2016", "Reisacher_Matthias_CPW", "Reisacher2016", "Riegelnegg_2019", "rippl-2023-atg", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "schindler_2020vis", "schmidlehner2021", "scholz_2021", "Schrempf_2020", "schultes_lampi", "seyfert-2017", "sikachev-2010-ill_vis_vol_ren", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "Spechtenhauser_Florian_2016", "stappen_2017_animatedcomic", "Stoll2020", "sturl_2016_dynlabels", "Swoboda2020", "szabo_patrik-2022-tour", "takahashi-2019-acdt", "Thomas-2018", "TR-186-2-07-08", "Troidl_2021", "Troidl_2022", "tut-eg-2006", "tut-siggraph-2006", "tut-vis-2006", "tut-vis-2007", "Unger2020", "Vasileva_2022", "Viola_Ivan_2013_SVA", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "viola-evr", "Viola-Pondering-2017", "Viola-vistutillustrativevis", "Waldin_Nicholas_2016_Colormaps", "waldin-2019-ccm", "Waldner_2017_11", "Wihann_2017", "Woschizka_2021", "wu-2019-bmc", "wu-2019-report", "Zaufel_2021", "zechmeister2020", "Zeng_2021", "Zusag-2017-Bach" ], "projects": [ "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=IllVis", "__class": "ResearchArea" }, { "id": "Modeling", "drupal_id": 4130, "name": "Modeling", "short_abstract": "In this area, we focus on researching methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.", "abstract": "One of the major bottlenecks in the field of computer graphics is the one of content creation, particularly the creation of high-quality 3D geometric models. These models are a demand in many industries, such as entertainment, computer-aided design, urban planning, the fabrication of physical objects, as well as research areas like medical or scientific visualizations and simulations.\n\nWhile rendering - the classical field of computer graphics - has reached very high standards in the recent two decades, the issue of the creation of appropriate digital models is a difficult problem that hardly keeps pace with current demands. Indeed, it is a complex creative process that involves both artistic and technical skills.\n\nTo make this process easier, our goal in this research area is to find new methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.", "website": "https://www.cg.tuwien.ac.at/research/area/Modeling", "teaser": { "name": "teaser.jpg", "path": "research_area:Modeling", "type": "image/jpeg", "size": 190581, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Modeling/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "AA2020", "Adorjan-2015", "aichner-2016-sadf", "arikan-2013-osn", "birsak-thesis", "Birsak2018-SA", "Brandstaetter2020", "brunner_lukas_2022_ssb", "Caic2021", "clemenz_2019_rosy_fields", "DOG10", "dusberger-2010-msm", "eibens-2021-tsgpmg", "eibensteiner-2021-pmcg", "eibner-2009-gpc", "Erhardt_2025_Scutes", "erler_2024_ppsurf", 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"scharl-master-thesis", "schneider-sturm-2026-mia", "scholz_2017_bac", "SCHWAERZLER-2017-SBGM", "SIETZEN-2017-BBO", "sifuentes-2018-crowd", "sippl-2014-fss", "sperl-2013-BA", "spitaler-2015-pbi", "steiner_2016_isad", "steiner-2014-da", "steinkellner-2022-dll", "steinschorn-2023-p2m", "steinschorn-2025-par", "steinschorn-2025-parameter", "tobler02_amrmg", "tobler02_mbpls", "Traxler-1996-GAI", "VASILJEVS-2018-PMPL", "Viola_Ivan_2013_RMA", "Viola_Ivan_2013_RSb", "weiner_2011", "WIMMER-2015-CGFC", "WIMMER-2016-FUTURIS", "WIMMER-2020-ASG", "wimmer-2023-acd", "Winkler-2017", "WINKLER-2019-PDG", "Wonka-2003-Ins", "xmas-2024", "zeiller-1993-coll", "Zotti-2003-AMP", "zotti-2003-ash", "zotti-2006-pla", "zotti-2007-eg" ], "projects": [ "3DSpatialization", "d4388", "EVOCATION", "GAMEWORLD", "Harvest4D", "PAMINA", "Photo-Guide", "REPLICATE", "SCI_BIM", "Wohnen 4.0" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Modeling", "__class": "ResearchArea" } ], 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This applies to scientists trying to make sense of their experiments and simulations, to bankers and traders trying to understand the dynamics of the financial markets, and to large enterprises which need to understand the principles behind demand and supply—to name just a few examples. The basic problem in all these cases is that people need to identify important and/or unexpected features in large simulated or captured datasets. Visualization is the domain that facilitates this process of sense-making by dramatically simplifying the process of obtaining an understanding of the data—by representing data visually and thus amplifying people’s cognition. This inherent capability of (good) visualization techniques to amplify human cognition, however, is no longer enough to be able to make sense of today’s huge datasets. To be able to see the essential aspects we need dedicated mechanisms that abstract away the (unnecessary) detail to, in turn, allow the user of the visualization to focus on the important elements. The crucial problem in this context is that it is impossible to know what is important and what is not in a general way—importance changes based on the research question, on the application domain, on the data size, on the user, on the specific situation, etc. Visualization technology therefore needs to support dynamic change of visual abstraction of the data to reflect these contextual changes. The fundamental research challenge in visualization for us is to get an understanding of what (visual) abstraction really is, what it means, how it can be controlled, and how it is, can be, and should be used in visualization.\n", "start_date": "2017-01-01", "end_date": "2019-12-31", "leader_id": 171, "logo": { "name": "logo.jpg", "path": "project:Illustrare", "type": "image/jpeg", "size": 95116, "orig_name": "logo.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/Illustrare/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "I 2953-N31", "comment": null } ], "research_areas": [ "BioVis", "IllVis" ], "publications": [ "Halladjian_2020", "kouril-2018-LoL", "lawonn-2018-illvisstar", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "Viola-Pondering-2017" ], "url": "https://www.cg.tuwien.ac.at/research/projects/Illustrare", 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"Kohlmann-2007-EBV", "kohlmann-2007-livesync", "kohlmann-2008-lse", "kohlmann-2009-cp", "kohlmann-2009-lssl", "kolesar-ivan-2014-polymers", "Kolter_2021", "komon-2025-dco", "komon-2025-webigeo", "komon-2025-webigeo", "komon-kimmersdorfer-2025-weBIGeo", "Konyha_2013_IVA", "korpitsch_thorsten-2019", "korpitsch-2020-cescg", "Korpitsch-2020-wscg", "korpitsch-2021-lov", "Koszticsak-2017-ewt", "Kouril_2017_11", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2018-LoL", "kouril-2018-LoL", "kouril-2020-hyperlabels", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kovacs_PhD", "krakhofer-2015", "Krone2016VABC", "kuehschelm-2005-adv", "Kugler_2019", "Kuroko-2020-iV", "Labschuetz_Matthias_2015_JIT", "Labschuetz_Matthias_2016_AHD", "Labschuetz_Matthias_2016_JIT", "Labschuetz_Matthias_2016_JITT", "Lackner_2022", "LaCruz2004", "Ladstaedter-2009-sim", "Langer_Edith_IR1", "Langer_Maximillian_DMV", "Laschober-2018", "lawonn-2018-illvisstar", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "LeMuzic_2016_PhD", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lemuzic-mindek-sorger-cgfcc", "Leutschacher_2022", "li-2019-gdc", "lie-2009-cri", "lipp-2017-mgpu", "lipp-2017-vulkan", "lippeck-2022-mna", "liu-2014-ac", "lkoell-2014", "ludwig-2012-MT", "Machegger2018DTI", "magg-2021-dva", "magg2021", "mahler-2021-mdar", "major-2010-mrf", "malan_fluoro", "malik-2007-FP", "malik-2009-CVFA", "malik-thesis", "Manczarski-2016", "Marek06", "Maricic_2013_VFE", "martorell2022", "maruyama-2019-iv", "Masopust_2018", "Masterthesis-Viola", "Matkovic_Kresimir_2015_", "matt-2023-vae", "matt-2024-cvil", "matt-2025-scv", "matt-masterthesis", "Mattausch-2003-ISL", "Mattausch-2003-SIE", "Mattausch-2003-Str", "Matusich-2017-01", "Mautner 2020", "Mayr-2017-1", "mayr-2021-wec", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "Mazza_2020", "Mazza_2021_05", "meka-2024-lpi", "Melo_2018_11", "Meusburger_2020", "Miao_2015_VCBM", "Miao_2019", "Miao_Haichao_2015_VQC", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_plitvice_2018", "miao_thesis_2019", "miao_tvcg_2017", "miao_tvcg_2018", "miao_tvcg_2018", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "Michl_2017_CSV", "mindek_peter-2012-visgroupproj", "mindek_peter-2014-cs_kaust", "mindek-2013-cs_cvut", "mindek-2013-csl", "mindek-2013-pel", "mindek-2014-mcs", "mindek-2014-vivi_cvut", "mindek-2015-mc", "mindek-2015-mctalk", "mindek-2016-utah-talk", "mindek-2017-dsn", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-2019-mci", "mindek-thesis", "mistelbauer_2013_SIV", "Mistelbauer_2021", "Mistelbauer_Gabriel_2015_NHR", "Mistelbauer_Gabriel_2016", "mistelbauer-2010-pvv", "mistelbauer-2012-cr", "mistelbauer-2012-ssv", "mistelbauer-2013-cfa", "mistelbauer-2015-abvv", "Mitterhofer_2017", "mizuno-2019-eurovis", "Mlejnek_2004_PF", "Mlejnek_2005_AOEPF", "Mlejnek_2006_MVOA", "Mlejnek-2004-Int", "Mlejnek-2004-ITVAC", "Mlinaric-2015-MT", "Moellinger_Christian_IDE2", "moerth_eric-2016-3DF", "moerth-2018-tpose", "monitzer_2008_FluSi", "Morar_2012_ISB", "Muehlbacher_diss_2018", "mueller-2009-ivs", "Muigg_2011_ISI", "Muigg_2011_VC", "Muigg-2008-four", "muigg-2012-svr", "musleh-2024-conan", "muth-2026-clouds", "Neumann-2002-Fea", "nguyen_2020-covid", "Niedermayer_2018", "Novotny_2013_ASVD", "Nowak_2020", "Nowak_2021", "Oancea_2018_1", "Oancea_Stefan_2016_VOT", "Oancea2018OAK", "oeltze-2013-tut", "opitz-2009-cvv", "Ortner_PhD", "Ortner2020", "Pahr_PhD", "pahr-2021-vologram", "pahr-2024-ieo", "pahr-2024-squishicalization", "pahr-2025-holographs", "pahr-2025-nodkant", "Pahr2020", "Pajer_2012_VoM", "Panayotov", "papantonakis-2024-rmf", "Parzer_2013_IIG", "patel_2009_MC", "patel_daniel_2007_IRSD", "patel-2008-tsa", "patel-2009-evr", "patel-2011-PEA", "Pauschenwein_2022", "Peter_2012_AIV", "Pezenka-2016-MT", "Pfahler_David_2015_IPI", "Pfahler-2016-MT", "PH-2011-LDS", "phd-viola", 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], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1665", "__class": "Author" } ], "number": "1", "volume": "26", "research_areas": [ { "id": "BioVis", "drupal_id": 4127, "name": "Biological Data Visualization", "short_abstract": "In this research area, we develop new visualization techniques to support biologists in data analysis and create visualizations to disseminate scientific discoveries in biology.", "abstract": "In modern biological research domain experts have to deal with complex and large data collections and simulations. Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n", "website": "https://www.cg.tuwien.ac.at/research/area/BioVis", "teaser": { "name": "teaser.png", "path": "research_area:BioVis", "type": "image/png", "size": 16330957, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/BioVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "amirkhanov-2019-manylands", "byska-2019-mdfc", "cellVIEW_2015", "cmolik-2020-tvcg", "Dietrich_1", "dietrich-2016-viseq2", "Ehlers_PhD", "ehlers-2025-ait", "eschner-2023-ims", "eschner-blur-2022", "Escribano_2017", "Furmanova_2018", "Gehrer-2017", "Gehrer-2017-molmach", "glinzner-2016-tex", "Halladjian_2020", "kapferer-2017-godot", "klein_2017_IM", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koch-2018-sso", "Kolesar-Fractional-2016", "kolesar-ivan-2014-polymers", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kozlikova-Visualization-2016b", "Krone2016VABC", "Kugler_2019", "lemuzic_2015_timelapse", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lipp-2017-mgpu", "lipp-2017-vulkan", "Manczarski-2016", "manylands_award", "Miao_2019", "miao_inria_2017", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-xmas-card-2016", "Mitterhofer_2017", "nguyen_2020-covid", "Nowak_2020", "raidou_2019_springer", "raidou_shonan167", "raidou2018visualflatter", "rasch-2016-imgses", "Reisacher2016", "rinortner_susanne-2019-vpicc", "Sarkis_2021", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2013-neuromap", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "stappen_2017_animatedcomic", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "trautner-2018-imd", "unger-2019_vcp", "vad_2015_phd", "vad_viktor-2017-WVE", "vad-2016-bre", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "waldin-2019-ccm", "waldner-2014-af", "Weissenboeck_2019", "wu-2017-dagstuhl", "wu-2018-metabo", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg" ], "projects": [ "BioNetIllustration", "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=BioVis", "__class": "ResearchArea" }, { "id": "IllVis", "drupal_id": 4131, "name": "Illustrative Visualization", "short_abstract": "In this research area, we develop rendering methods that are inspired by scientific illustrations, in order to make complex biological information more intuitive to understand and more pleasant to read.", "abstract": "Scientific illustration is concerned with researching ways in which complex biological and medical data can be abstracted in order to convey a desired information that would otherwise be impossible or hard to retrieve from the original data. Illustrators apply such techniques, for instance, to present non-important parts of an organ in a simplified way, while using detailed representations to put the focus of attention on a region where a tumor might be situated.\n\nTo identify such meaningful visual abstractions for visualization, their effectiveness for human perception and cognition has to be assessed, and they have to be formalized in order to make them applicable in rendering algorithms. In this project, we try to advance the understanding of procedural visual abstraction of complex physiological processes that describe the complex machinery of biological life.", "website": "https://www.cg.tuwien.ac.at/research/area/IllVis", "teaser": { "name": "teaser.jpg", "path": "research_area:IllVis", "type": "image/jpeg", "size": 34861, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/IllVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "antes-2026-maa", "Antonini2020", "Balabanian-2010-IIV", "Balduz_01", "Bayat_2019", "Bechtold2020", "Birkeland-2012-IMC", "brandstaetter_01", "bruckner-2005-ICV", "bruckner-2006-ICE", "bruckner-2007-STF", "bruckner-2008-IIV", "bruckner-2010-HVC", "bruckner-2010-IFC", "cellVIEW_2015", "Chen-Information-2016", "Deutsch-2018", "Dhanoa_2021", "Dhanoa2024", "dietrich-2016-viseq2", 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"files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Halladjian_2020-paper.pdf", "type": "application/pdf", "size": 14976666, "path": "Publication:Halladjian_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Halladjian_2020/Halladjian_2020-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Halladjian_2020/Halladjian_2020-paper:thumb{{size}}.png" }, { "description": null, "filetitle": "scale_trotter", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 770, "image_height": 838, "name": "Halladjian_2020-scale_trotter.png", "type": "image/png", "size": 746352, "path": "Publication:Halladjian_2020", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Halladjian_2020/Halladjian_2020-scale_trotter.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": 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This applies to scientists trying to make sense of their experiments and simulations, to bankers and traders trying to understand the dynamics of the financial markets, and to large enterprises which need to understand the principles behind demand and supply—to name just a few examples. The basic problem in all these cases is that people need to identify important and/or unexpected features in large simulated or captured datasets. Visualization is the domain that facilitates this process of sense-making by dramatically simplifying the process of obtaining an understanding of the data—by representing data visually and thus amplifying people’s cognition. This inherent capability of (good) visualization techniques to amplify human cognition, however, is no longer enough to be able to make sense of today’s huge datasets. To be able to see the essential aspects we need dedicated mechanisms that abstract away the (unnecessary) detail to, in turn, allow the user of the visualization to focus on the important elements. The crucial problem in this context is that it is impossible to know what is important and what is not in a general way—importance changes based on the research question, on the application domain, on the data size, on the user, on the specific situation, etc. Visualization technology therefore needs to support dynamic change of visual abstraction of the data to reflect these contextual changes. The fundamental research challenge in visualization for us is to get an understanding of what (visual) abstraction really is, what it means, how it can be controlled, and how it is, can be, and should be used in visualization.\n", "start_date": "2017-01-01", "end_date": "2019-12-31", "leader_id": 171, "logo": { "name": "logo.jpg", "path": "project:Illustrare", "type": "image/jpeg", "size": 95116, "orig_name": "logo.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/Illustrare/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "I 2953-N31", "comment": null } ], "research_areas": [ "BioVis", "IllVis" ], "publications": [ "Halladjian_2020", "kouril-2018-LoL", "lawonn-2018-illvisstar", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "Viola-Pondering-2017" ], "url": "https://www.cg.tuwien.ac.at/research/projects/Illustrare", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Halladjian_2020/", "__class": "Publication" }, { "id": "nguyen_2020-covid", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "Modeling in the Time of COVID-19: Statistical and Rule-based Mesoscale Models", "date": "2020", "abstract": "We present a new technique for rapid modeling and construction of scientifically accurate mesoscale biological models. Resulting 3D models are based on few 2D microscopy scans and the latest knowledge about the biological entity represented as a set of geometric relationships. Our new technique is based on statistical and rule-based modeling approaches that are rapid to author, fast to construct, and easy to revise. From a few 2D microscopy scans, we learn statistical properties of various structural aspects, such as the outer membrane shape, spatial properties and distribution characteristics of the macromolecular elements on the membrane. This information is utilized in 3D model construction. Once all imaging evidence is incorporated in the model, additional information can be incorporated by interactively defining rules that spatially characterize the rest of the biological entity, such as mutual interactions among macromolecules, their distances and orientations to other structures. These rules are defined through an intuitive 3D interactive visualization and modeling feedback loop. We demonstrate the utility of our approach on a use case of the modeling procedure of the SARS-CoV-2 virus particle ultrastructure. Its first complete atomistic model, which we present here, can steer biological research to new promising directions in fighting spread of the virus.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 2160, "image_height": 1824, "name": "nguyen_2020-covid-image.png", "type": "image/png", "size": 3574056, "path": "Publication:nguyen_2020-covid", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/nguyen_2020-covid/nguyen_2020-covid-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/nguyen_2020-covid/nguyen_2020-covid-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1788, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Ngan", "lastname": "Nguyen", "searchname": "Ngan Nguyen", 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mesoscale models provides a glimpse at the inner workings of living cells. One of the most complex components of these models is DNA, which is of fundamental importance for all forms of life. Modeling the 3D structure of genomes has previously only been attempted by sequential approaches. We present the first parallel approach for the instant construction of DNA structures. Traditionally, such structures are generated with algorithms like random walk, which have inherent sequential constraints. These algorithms result in the desired structure, are easy to control, and simple to formulate. Their execution, however, is very time-consuming, as they are not designed to exploit parallelism. We propose an approach to parallelize the process, facilitating an implementation on the GPU.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1534, "image_height": 782, "name": "klein_2019_PGG-teaser.png", "type": "image/png", "size": 2567699, "path": "Publication:klein_2019_PGG", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/klein_2019_PGG/klein_2019_PGG-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/klein_2019_PGG/klein_2019_PGG-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1285, "drupal_id": 1146, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/TobiasKlein", "firstname": "Tobias", "lastname": "Klein", "searchname": "Tobias Klein", "is_teacher": false, "name": 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"publ_id": "Viola_Ivan_2013_HQ3", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Viola-05-Smart", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "viola-2007-ort", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Viola-Pondering-2017", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "vis-foa", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldin-2017-thesis", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Wihann_2017", "field_id": "supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=171", "__class": "Author" } ], "cfp": { "name": "Capture.JPG", "type": "image/jpeg", "error": "0", "size": "167470", "orig_name": "Capture.JPG", "ext": "JPG" }, "date_from": "2019", "date_to": "2019", "doi": "10.1111/cgf.13816", "event": "Pacific Graphics 2109", "journal": "Computer Graphics Forum", "lecturer": [ { "id": 1285, "drupal_id": 1146, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/TobiasKlein", "firstname": "Tobias", "lastname": "Klein", "searchname": "Tobias Klein", "is_teacher": false, "name": "Tobias Klein", "publications": [ "Alharbi_2021", "klein_2017_IM", "klein_2019_MSA_Poster", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "Klein_Tobias_2015TIV", "klein-2016-WCL", "klein-thesis", "koch_bernhard_2018-1", "Miao_2019", "mindek-2017-virtualcell", "mindek-2019-mci", "nguyen_2020-covid", "sorger-2016-fowardabstraction", "wu-2021", "wu-2021-vi" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "Escribano_2017", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Hochpoechler_2016_VR", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "klein_2017_IM", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "klein_2019_PGG", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "klein_2019_PMP", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Knapp_2017_CVR", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Kugler_2019", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Michl_2017_CSV", "field_id": "supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1285", "__class": "Author" } ], "number": "7", "pages_from": "57", "pages_to": "68", "volume": "38", "research_areas": [ { "id": "BioVis", "drupal_id": 4127, "name": "Biological Data Visualization", "short_abstract": "In this research area, we develop new visualization techniques to support biologists in data analysis and create visualizations to disseminate scientific discoveries in biology.", "abstract": "In modern biological research domain experts have to deal with complex and large data collections and simulations. Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n", "website": "https://www.cg.tuwien.ac.at/research/area/BioVis", "teaser": { "name": "teaser.png", "path": "research_area:BioVis", "type": "image/png", "size": 16330957, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/BioVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "amirkhanov-2019-manylands", "byska-2019-mdfc", "cellVIEW_2015", "cmolik-2020-tvcg", "Dietrich_1", "dietrich-2016-viseq2", "Ehlers_PhD", "ehlers-2025-ait", "eschner-2023-ims", "eschner-blur-2022", "Escribano_2017", "Furmanova_2018", "Gehrer-2017", "Gehrer-2017-molmach", "glinzner-2016-tex", "Halladjian_2020", "kapferer-2017-godot", "klein_2017_IM", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koch-2018-sso", "Kolesar-Fractional-2016", "kolesar-ivan-2014-polymers", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kozlikova-Visualization-2016b", "Krone2016VABC", "Kugler_2019", "lemuzic_2015_timelapse", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lipp-2017-mgpu", "lipp-2017-vulkan", "Manczarski-2016", "manylands_award", "Miao_2019", "miao_inria_2017", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-xmas-card-2016", "Mitterhofer_2017", "nguyen_2020-covid", "Nowak_2020", "raidou_2019_springer", "raidou_shonan167", "raidou2018visualflatter", "rasch-2016-imgses", "Reisacher2016", "rinortner_susanne-2019-vpicc", "Sarkis_2021", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2013-neuromap", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "stappen_2017_animatedcomic", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "trautner-2018-imd", "unger-2019_vcp", "vad_2015_phd", "vad_viktor-2017-WVE", "vad-2016-bre", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "waldin-2019-ccm", "waldner-2014-af", "Weissenboeck_2019", "wu-2017-dagstuhl", "wu-2018-metabo", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg" ], "projects": [ "BioNetIllustration", "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=BioVis", "__class": "ResearchArea" }, { "id": "IllVis", "drupal_id": 4131, "name": "Illustrative Visualization", "short_abstract": "In this research area, we develop rendering methods that are inspired by scientific illustrations, in order to make complex biological information more intuitive to understand and more pleasant to read.", "abstract": "Scientific illustration is concerned with researching ways in which complex biological and medical data can be abstracted in order to convey a desired information that would otherwise be impossible or hard to retrieve from the original data. Illustrators apply such techniques, for instance, to present non-important parts of an organ in a simplified way, while using detailed representations to put the focus of attention on a region where a tumor might be situated.\n\nTo identify such meaningful visual abstractions for visualization, their effectiveness for human perception and cognition has to be assessed, and they have to be formalized in order to make them applicable in rendering algorithms. In this project, we try to advance the understanding of procedural visual abstraction of complex physiological processes that describe the complex machinery of biological life.", "website": "https://www.cg.tuwien.ac.at/research/area/IllVis", "teaser": { "name": "teaser.jpg", "path": "research_area:IllVis", "type": "image/jpeg", "size": 34861, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/IllVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "antes-2026-maa", "Antonini2020", "Balabanian-2010-IIV", "Balduz_01", "Bayat_2019", "Bechtold2020", "Birkeland-2012-IMC", "brandstaetter_01", "bruckner-2005-ICV", "bruckner-2006-ICE", "bruckner-2007-STF", "bruckner-2008-IIV", "bruckner-2010-HVC", "bruckner-2010-IFC", "cellVIEW_2015", "Chen-Information-2016", "Deutsch-2018", "Dhanoa_2021", "Dhanoa2024", "dietrich-2016-viseq2", "donabauer_2019_1", "eg-tut2005-iv", "eschner-2023-ims", "Essler2022", "gangl-2018-gpsart", "Gehrer_Daniel_CUI", "Gehrer-2017-molmach", "gerl-2006-vhi", "Gogel2020", "Groeller_2011_IPV", "Groeller_2016_I3", "Groeller_2016_I6", "Groeller_2016_I7", "Groeller_2016_I8", "Groeller_V1_2020", "groeller-2006-ivt", "groeller-2007-fci", "groeller-2008-irs", "Groeller-2010-IFI", "gruber-2025-vps", "Halladjian_2020", "haushofer-2018-skinning", "Heim_2020", "horvath-2018-ism", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "Knapp_2017_CVR", "Koeppel2020", "kolesar-ivan-2014-polymers", "Konev-FCV2018", "Koszticsak-2017-ewt", "Kouril_2017_11", "kouril-2020-hyperlabels", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "kroesl_x_card_2017", "Lackner_2022", "Langer_Edith_IR1", "lawonn-2018-illvisstar", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "LeMuzic_2016_PhD", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "Leutschacher_2022", "ludwig-2012-MT", "Manczarski-2016", "Matusich-2017-01", "Mautner 2020", "Mayr-2017-1", "Melo_2018_11", "Meusburger_2020", "Miao_2019", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao2018Dimsum", "Michl_2017_CSV", "mindek-2015-mc", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-2019-mci", "mindek-xmas-card-2016", "Moellinger_Christian_IDE2", "Niedermayer_2018", "Ortner_PhD", "Ortner2020", "pahr-2021-vologram", "Panayotov", "patel_daniel_2007_IRSD", "Pauschenwein_2022", "Peter_2012_AIV", "plank-2017-sldg", "prost-2016-molecule", "purgathofer-2008-cgi", "Radwan-2017-Occ", "Rautek-2007-SLI", "Rautek-2008-IDS", "Rautek-2008-VF", "Reichinger_2016", "Reichinger_Fuhrmann_2016", "Reisacher_Matthias_CPW", "Reisacher2016", "Riegelnegg_2019", "rippl-2023-atg", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "schindler_2020vis", "schmidlehner2021", "scholz_2021", "Schrempf_2020", "schultes_lampi", "seyfert-2017", "sikachev-2010-ill_vis_vol_ren", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "Spechtenhauser_Florian_2016", "stappen_2017_animatedcomic", "Stoll2020", "sturl_2016_dynlabels", "Swoboda2020", "szabo_patrik-2022-tour", "takahashi-2019-acdt", "Thomas-2018", "TR-186-2-07-08", "Troidl_2021", "Troidl_2022", "tut-eg-2006", "tut-siggraph-2006", "tut-vis-2006", "tut-vis-2007", "Unger2020", "Vasileva_2022", "Viola_Ivan_2013_SVA", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "viola-evr", "Viola-Pondering-2017", "Viola-vistutillustrativevis", "Waldin_Nicholas_2016_Colormaps", "waldin-2019-ccm", "Waldner_2017_11", "Wihann_2017", "Woschizka_2021", "wu-2019-bmc", "wu-2019-report", "Zaufel_2021", "zechmeister2020", "Zeng_2021", "Zusag-2017-Bach" ], "projects": [ "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=IllVis", "__class": "ResearchArea" }, { "id": "Modeling", "drupal_id": 4130, "name": "Modeling", "short_abstract": "In this area, we focus on researching methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.", "abstract": "One of the major bottlenecks in the field of computer graphics is the one of content creation, particularly the creation of high-quality 3D geometric models. These models are a demand in many industries, such as entertainment, computer-aided design, urban planning, the fabrication of physical objects, as well as research areas like medical or scientific visualizations and simulations.\n\nWhile rendering - the classical field of computer graphics - has reached very high standards in the recent two decades, the issue of the creation of appropriate digital models is a difficult problem that hardly keeps pace with current demands. Indeed, it is a complex creative process that involves both artistic and technical skills.\n\nTo make this process easier, our goal in this research area is to find new methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.", "website": "https://www.cg.tuwien.ac.at/research/area/Modeling", "teaser": { "name": "teaser.jpg", "path": "research_area:Modeling", "type": "image/jpeg", "size": 190581, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Modeling/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "AA2020", "Adorjan-2015", "aichner-2016-sadf", "arikan-2013-osn", "birsak-thesis", "Birsak2018-SA", "Brandstaetter2020", "brunner_lukas_2022_ssb", "Caic2021", "clemenz_2019_rosy_fields", "DOG10", "dusberger-2010-msm", "eibens-2021-tsgpmg", "eibensteiner-2021-pmcg", "eibner-2009-gpc", "Erhardt_2025_Scutes", "erler_2024_ppsurf", "erler_philipp-2016-femfluid-prakt", "erler_philipp-2017-phd", "erler-2020-p2s", "erler-2025-lidarscout", "fan-2014-scfl", "ferschin-1992-kons", "fiedler-2009-php", "fleiss-2015-da", "GAHR-2013-AGM", "gamsjaeger-2022-proc", "gersthofer-2016-sosob", "gervautz-1989-sol1", "gervautz-1993-use", "griessmair-1989-def1", "groeller-1992-frac", "groeller-1995-mod", "Groeller-1995-SDC", "Grossfurtner-2023-paego", "Guerrero-2014-GRF", "Guerrero-2014-TPS", "guerrero-2015-lsp", "HECHER-2017-HDY", "hiess-1992-comb", "hofer_kerstin-2023-sketch2model", "honic-2020-w78", "HU-2017-ETM", "HUMMEL-2001-MSE", "Ilcik_2015_LAY", "ilcik-2010-ps", "ilcik-2013-cipmi", "ilcik-2014-cgbpmi", "ilcik-2016-cmssg", "ilcik-2021-xmas", "kapferer_2021_advancing", "karnik-09-shapegrammar", "Kellner-2021-DA", "kendlbacher-2016", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koenigsberger-2024-msu", "komon-2025-webigeo", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kraehsmaier-dsc", "kreuzer-2016-isf", 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"xmastree2002", "xmastree2005", "ymca", "YOGHOURDJIAN2019", "Zambal-2003-SWA", "zambal-2005-3dact", "Zaufel_2021", "zauner-2013-svkinect", "zechmeister2020", "Zeng_2021", "Zhu-2014-flowvis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Workgroup&id=vis", "__class": "Workgroup" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/klein_2019_PGG/", "__class": "Publication" }, { "id": "wu-2019-visworkshop", "type_id": "WorkshopTalk", "tu_id": null, "repositum_id": null, "title": "Graph Models for Biological Pathway Visualization: State of the Art and Future Challenges", "date": "2019-10-20", "abstract": "The concept of multilayer networks has become recently integrated into complex systems modeling since it encapsulates a very general concept of complex relationships. Biological pathways are an exam- ple of complex real-world networks, where vertices represent biolog- ical entities, and edges indicate the underlying connectivity. For this reason, using multilayer networks to model biological knowledge allows us to formally cover essential properties and theories in the field, which also raises challenges in visualization. This is because, in the early days of pathway visualization research, only restricted types of graphs, such as simple graphs, clustered graphs, and others were adopted. In this paper, we revisit a heterogeneous definition of biological networks and aim to provide an overview to see the gaps between data modeling and visual representation. The contribution will, therefore, lie in providing guidelines and challenges of using multilayer networks as a unified data structure for the biological pathway visualization.\n", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 256, "image_height": 192, "name": "wu-2019-visworkshop-image.png", "type": "image/png", "size": 22606, "path": "Publication:wu-2019-visworkshop", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-visworkshop/wu-2019-visworkshop-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-visworkshop/wu-2019-visworkshop-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1464, "drupal_id": 1266, "orcid_id": "0000-0003-1028-0010", "website": 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Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n", "website": "https://www.cg.tuwien.ac.at/research/area/BioVis", "teaser": { "name": "teaser.png", "path": "research_area:BioVis", "type": "image/png", "size": 16330957, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/BioVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "amirkhanov-2019-manylands", "byska-2019-mdfc", "cellVIEW_2015", "cmolik-2020-tvcg", "Dietrich_1", "dietrich-2016-viseq2", "Ehlers_PhD", "ehlers-2025-ait", "eschner-2023-ims", "eschner-blur-2022", "Escribano_2017", "Furmanova_2018", "Gehrer-2017", "Gehrer-2017-molmach", "glinzner-2016-tex", "Halladjian_2020", "kapferer-2017-godot", "klein_2017_IM", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koch-2018-sso", "Kolesar-Fractional-2016", "kolesar-ivan-2014-polymers", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kozlikova-Visualization-2016b", "Krone2016VABC", "Kugler_2019", "lemuzic_2015_timelapse", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lipp-2017-mgpu", "lipp-2017-vulkan", "Manczarski-2016", "manylands_award", "Miao_2019", "miao_inria_2017", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-xmas-card-2016", "Mitterhofer_2017", "nguyen_2020-covid", "Nowak_2020", "raidou_2019_springer", "raidou_shonan167", "raidou2018visualflatter", "rasch-2016-imgses", "Reisacher2016", "rinortner_susanne-2019-vpicc", "Sarkis_2021", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2013-neuromap", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "stappen_2017_animatedcomic", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "trautner-2018-imd", "unger-2019_vcp", "vad_2015_phd", "vad_viktor-2017-WVE", "vad-2016-bre", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "waldin-2019-ccm", "waldner-2014-af", "Weissenboeck_2019", "wu-2017-dagstuhl", "wu-2018-metabo", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg" ], "projects": [ "BioNetIllustration", "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=BioVis", "__class": "ResearchArea" }, { "id": "InfoVis", "drupal_id": 4128, "name": "Information Visualization and Visual Analytics", "short_abstract": "In this research area, our focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning. ", "abstract": "

Data and information created by various processes (e.g., simulations) is getting larger, and more and more complex. We use interactive visualization and analysis techniques to facilitate exploration of complex parameter spaces (e.g., to analyze and compare parameters for automotive engineering, reconstruction algorithms, or geometry generators) or unstructured information collections (e.g., annotated digital documents or image collections). Our research focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning.

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"d9522", "d9555", "deskollage", "Scenario Pool" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=InfoVis", "__class": "ResearchArea" } ], "keywords": [ "Graph drawing", "multilayer network", "biological pathway" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 256, "image_height": 192, "name": "wu-2019-visworkshop-image.png", "type": "image/png", "size": 22606, "path": "Publication:wu-2019-visworkshop", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-visworkshop/wu-2019-visworkshop-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-visworkshop/wu-2019-visworkshop-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": 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In living systems, one molecule is commonly involved in several distinct physiological functions. The roles of molecules are commonly summarized in pathway diagrams, which, however, are abstract, hierarchically nested and thus is difficult to comprehend especially by non-expert audience. The primary goal of this research in visualization is to intuitively support the comprehensive understanding of relationships among biological networks using interactively computed illustrations. Illustrations, especially in textbooks of biology are carefully designed to clearly present reactions between organs as well as interactions within cells. Automatic generation of illustrative visualizations of biological networks is thus the technical content of this proposal. Automatic generation of hand-drawn illustrations has been a challenging task due to the difficulty of algorithmically describing a human creative process such as evaluating and selecting significant information and composing meaningful explanations in a visually plausible manner. The project also involves experts from several disciplines including network and medical visualization, data mining, systems biology as well as perceptual psychology. The result will provide a new direction for physiological process analysis and accelerate the knowledge transfer not only within experts but also to the public. Acknowledgment: The project has received funding from the European Union Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 747985.

\r\n", "abstract": "

In living systems, one molecule is commonly involved in several distinct physiological functions. The roles of molecules are commonly summarized in pathway diagrams, which, however, are abstract, hierarchically nested and thus is difficult to comprehend especially by non-expert audience. The primary goal of this research in visualization is to intuitively support the comprehensive understanding of relationships among biological networks using interactively computed illustrations. Illustrations, especially in textbooks of biology are carefully designed to clearly present reactions between organs as well as interactions within cells. Automatic generation of illustrative visualizations of biological networks is thus the technical content of this proposal. Automatic generation of hand-drawn illustrations has been a challenging task due to the difficulty of algorithmically describing a human creative process such as evaluating and selecting significant information and composing meaningful explanations in a visually plausible manner. The project also involves experts from several disciplines including network and medical visualization, data mining, systems biology as well as perceptual psychology. The result will provide a new direction for physiological process analysis and accelerate the knowledge transfer not only within experts but also to the public. Acknowledgment: The project has received funding from the European Union Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 747985.

\r\n", "start_date": "2017-06-21", "end_date": "2019-06-20", "leader_id": 1464, "logo": { "name": "logo.png", "path": "project:BioNetIllustration", "type": "image/png", "size": 16337, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/BioNetIllustration/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "Horizon 2020", "contract_number": "747985", "comment": null } ], "research_areas": [ "BioVis", "InfoVis" ], "publications": [ "cmolik-2020-tvcg", "kouril-2018-LoL", "mizuno-2019-eurovis", "Purchase-2020-gd", "rinortner_susanne-2019-vpicc", "Sbardellati-2019-vcbm", "wu-2017-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-shonan", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg", "YOGHOURDJIAN2019" ], "url": "https://www.cg.tuwien.ac.at/research/projects/BioNetIllustration", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-visworkshop/", "__class": "Publication" }, { "id": "li-2019-gdc", "type_id": "unknown", "tu_id": 282819, "repositum_id": null, "title": "World map of recipes", "date": "2019-09-19", "abstract": "This poster visualises the Meal Ingredients dataset with 151 international food recipes and their corresponding ingredients. The underlying graph layout in the image is automatically generated using a new multi-level force-based algorithm developed by the authors, but not yet published. The background flags were added manually to identify the countries from the data set. The algorithm aims to untangle mutually nested subgraphs by harmonizing the available space for the labels and improving edge visibility by duplicating high-frequency ingredient nodes. Ingredients occurring in multiple countries also receive at least one node per country. The idea is inspired by map diagrams, which often show the semantics enclosed by country boundaries. In our diagram, countries are represented by octolinear polygons, and are placed next to each other if they share many ingredients in their recipes. The actual placement of the countries by the algorithm is entirely data driven. As we can see, this design naturally gathers countries that are located on the same continent, due to the accessibility of the ingredients. The names of recipes are visualized using textual labels with sharp corners, and they are enclosed by the country polygon they belong to. Contrarily, ingredients are represented by textual labels with rounded corners. Moreover, ingredients are visually classified into common (pink) and special (blue) ingredients based on their frequency in the dataset. \nFor visually analyzing the data set, we can generate smoothed spanning trees along the boundaries of an (invisible) Voronoi diagram of all textual labels to connect identical nodes to visually integrate all copies of one ingredient. For example, we highlighted the ingredient \"soy sauce\", one of the most commonly used ingredients in Asia, to discover that it has spread to the UK as well. We can also perform visual queries for related recipes based on sharing rare ingredients. For example, the British dish \"steak and kidney pie\" is highlighted in green together with three blue spanning trees connecting all recipes related to that dish via at least one of its special (blue) ingredients.", "authors_et_al": false, "substitute": null, "main_image": { "description": "1st Place Award, Creative Topic-\"Meal Ingredients\", of the 28th Annual Graph Drawing Contest", "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "li-2019-gdc-image.png", "type": "image/png", "size": 109353, "path": "Publication:li-2019-gdc", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/li-2019-gdc/li-2019-gdc-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/li-2019-gdc/li-2019-gdc-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1698, "drupal_id": null, "orcid_id": null, "website": "https://www.ac.tuwien.ac.at/people/guangping/", "firstname": "Guangping", "lastname": "Li", "searchname": "Guangping Li", "is_teacher": false, "name": "Guangping Li", "publications": [ "bhore-2021-issac", "bhore-2023-ucd", "li-2019-gdc" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "bhore-2021-issac", "field_id": "lecturer", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1698", "__class": "Author" }, { "id": 1699, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Soeren", "lastname": "Nickel", "searchname": "Soeren Nickel", "is_teacher": false, "name": "Soeren Nickel", "publications": [ "batik-2021-gd", "li-2019-gdc" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1699", "__class": "Author" }, { "id": 1579, "drupal_id": null, "orcid_id": null, "website": "https://www.ac.tuwien.ac.at/people/noellenburg/", "firstname": "Martin", "lastname": "Nöllenburg", "searchname": "Martin Nöllenburg", "is_teacher": false, "name": "Martin Nöllenburg", "publications": [ "batik-2021-gd", "batik-2022-smm", "bhore-2021-issac", "bhore-2023-ucd", "cmolik-2020-tvcg", "ehlers-2025-ait", "li-2019-gdc", "noellenburg-2023-pga", "Purchase-2020-gd", "wu-2018-metabo", "wu-2018-story", "wu-2019-bmc", "wu-2019-smw", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-eurovis-star", "wu-2020-tvcg" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1579", "__class": "Author" }, { "id": 171, "drupal_id": 168, "orcid_id": "0000-0003-4248-6574", "website": "https://www.cg.tuwien.ac.at/staff/IvanViola", "firstname": "Ivan", "lastname": "Viola", "searchname": "Ivan Viola", "is_teacher": true, "name": "Ivan Viola", 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"ordernum": 0 }, { "publ_id": "Batik-2021", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Deutsch-2018", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Ehlers_PhD", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Ismail-2018", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "koeppel-2021", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Koeppel2020", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Kompatscher-2021", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "korpitsch_thorsten-2019", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Korpitsch-2020-wscg", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "korpitsch-2023-sao", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Laschober-2018", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "mistelbauer-2023-aha", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Pahr_PhD", "field_id": "co_supervisor", "ordernum": 0 }, { 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"short_abstract": "In this research area, our focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning. ", "abstract": "

Data and information created by various processes (e.g., simulations) is getting larger, and more and more complex. We use interactive visualization and analysis techniques to facilitate exploration of complex parameter spaces (e.g., to analyze and compare parameters for automotive engineering, reconstruction algorithms, or geometry generators) or unstructured information collections (e.g., annotated digital documents or image collections). Our research focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning.

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"unterguggenberger-2024-fropo", "usul-thesis", "vad_2015_phd", "Vad_Viktor_2015_RVV", "vad-2016-bre", "vaico", "varchola_andrej-2012-fetoscopic", "Vasileva_2022", "Vasileva-2018", "vessel2003", "Viola_2013_IDV", "Viola_Ivan_2013_CAI", "Viola_Ivan_2013_D3D", "Viola_Ivan_2013_DC", "Viola_Ivan_2013_GS", "Viola_Ivan_2013_HQ3", "Viola_Ivan_2013_RMA", "Viola_Ivan_2013_RSb", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_DAC", "Viola_Ivan_IIP", "Viola_Ivan_UVP", "Viola_Ivan_VDP", "Viola-05-Smart", "Viola-2003-GPU", "Viola-2003-Har", "viola-2003-hbn", "Viola-2003-NON", "viola-2004-gbf", "Viola-2004-GPU", "viola-2004-har", "viola-2004-har2", "viola-2004-idv", "viola-2004-imp", "Viola-2004-ImpX", "Viola-2004-ImpX2", "viola-2005-imp", "viola-2006-FoA", "viola-evr", "Viola-Pondering-2017", "viola-popular-article-2006", "Viola-vistutillustrativevis", "vis-foa", "VisWeek-Tutorial-2012-Uncertainty", 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"wu-2018-story", "wu-2019-bmc", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-smwp", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg", "wu-2021", "wu-2021-vi", "xmastree2002", "xmastree2005", "ymca", "YOGHOURDJIAN2019", "Zambal-2003-SWA", "zambal-2005-3dact", "Zaufel_2021", "zauner-2013-svkinect", "zechmeister2020", "Zeng_2021", "Zhu-2014-flowvis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Workgroup&id=vis", "__class": "Workgroup" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/li-2019-gdc/", "__class": "Publication" }, { "id": "Sbardellati-2019-vcbm", "type_id": "inproceedings", "tu_id": 282838, "repositum_id": null, "title": "Interactive Exploded Views for Molecular Structures", "date": "2019-09-03", "abstract": "We propose an approach to interactively create exploded views of molecular structures with the goal to help domain experts in their design process and provide them with a meaningful visual representation of component relationships. Exploded views are excellently suited to manage visual occlusion of structure components, which is one of the main challenges when visualizing complex 3D data. In this paper, we discuss four key parameters of an exploded view: explosion distance, direction, order, and the selection of explosion components. We propose two strategies, namely the structure-derived exploded view and the interactive free-form exploded view, for computing these four parameters systematically. The first strategy allows scientists to automatically create exploded views by computing the parameters from the given object structures. The second strategy further supports them to design and customize detailed explosion paths through user interaction. Our approach features the possibility to animate exploded views, to incorporate ease functions into these animations and to display the explosion path of components via arrows. Finally, we demonstrate three use cases with various challenges that we investigated in collaboration with a domain scientist. Our approach, therefore, provides interesting new ways of investigating and presenting the design layout and composition of complex molecular structures.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "Sbardellati-2019-vcbm-image.png", "type": "image/png", "size": 46683, "path": "Publication:Sbardellati-2019-vcbm", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/Sbardellati-2019-vcbm/Sbardellati-2019-vcbm-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/Sbardellati-2019-vcbm/Sbardellati-2019-vcbm-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1555, "drupal_id": 1363, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/MaximilianSbardellati", "firstname": "Maximilian", "lastname": "Sbardellati", "searchname": "Maximilian Sbardellati", "is_teacher": false, "name": "Maximilian Sbardellati", "publications": [ "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "sbardellati-2021-eveos" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "Sbardellati-2019-vcbm", "field_id": "lecturer", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1555", "__class": "Author" }, { "id": 1263, "drupal_id": 863, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/HaichaoMiao", "firstname": "Haichao", "lastname": "Miao", "searchname": "Haichao Miao", "is_teacher": false, "name": "Haichao Miao", "publications": [ "gadllah_2016", "gall_2016", "Halladjian_2020", "Miao_2015_VCBM", "miao_2016_cgf", "Miao_2019", "Miao_Haichao_2015_VQC", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_plitvice_2018", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2017", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "Sarkis_2021", "Sbardellati-2019-vcbm", "wu-2019-report", "wu-2021", "wu-2021-vi" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "gall_alexander_2016BA", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Miao_2015_VCBM", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "miao_tvcg_2017", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "miao_tvcg_2018", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "miao2018Dimsum", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "sbardellati_ba_2018", "field_id": "supervisor", "ordernum": 1 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1263", "__class": "Author" }, { "id": 1464, "drupal_id": 1266, "orcid_id": "0000-0003-1028-0010", "website": 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Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n", "website": "https://www.cg.tuwien.ac.at/research/area/BioVis", "teaser": { "name": "teaser.png", "path": "research_area:BioVis", "type": "image/png", "size": 16330957, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/BioVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "amirkhanov-2019-manylands", "byska-2019-mdfc", "cellVIEW_2015", "cmolik-2020-tvcg", "Dietrich_1", "dietrich-2016-viseq2", "Ehlers_PhD", "ehlers-2025-ait", "eschner-2023-ims", "eschner-blur-2022", "Escribano_2017", "Furmanova_2018", "Gehrer-2017", "Gehrer-2017-molmach", "glinzner-2016-tex", "Halladjian_2020", "kapferer-2017-godot", "klein_2017_IM", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koch-2018-sso", "Kolesar-Fractional-2016", "kolesar-ivan-2014-polymers", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kozlikova-Visualization-2016b", "Krone2016VABC", "Kugler_2019", "lemuzic_2015_timelapse", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lipp-2017-mgpu", "lipp-2017-vulkan", "Manczarski-2016", "manylands_award", "Miao_2019", "miao_inria_2017", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-xmas-card-2016", "Mitterhofer_2017", "nguyen_2020-covid", "Nowak_2020", "raidou_2019_springer", "raidou_shonan167", "raidou2018visualflatter", "rasch-2016-imgses", "Reisacher2016", "rinortner_susanne-2019-vpicc", "Sarkis_2021", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2013-neuromap", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "stappen_2017_animatedcomic", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "trautner-2018-imd", "unger-2019_vcp", "vad_2015_phd", "vad_viktor-2017-WVE", "vad-2016-bre", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "waldin-2019-ccm", "waldner-2014-af", "Weissenboeck_2019", "wu-2017-dagstuhl", "wu-2018-metabo", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg" ], "projects": [ "BioNetIllustration", "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=BioVis", "__class": "ResearchArea" }, { "id": "IllVis", "drupal_id": 4131, "name": "Illustrative Visualization", "short_abstract": "In this research area, we develop rendering methods that are inspired by scientific illustrations, in order to make complex biological information more intuitive to understand and more pleasant to read.", "abstract": "Scientific illustration is concerned with researching ways in which complex biological and medical data can be abstracted in order to convey a desired information that would otherwise be impossible or hard to retrieve from the original data. Illustrators apply such techniques, for instance, to present non-important parts of an organ in a simplified way, while using detailed representations to put the focus of attention on a region where a tumor might be situated.\n\nTo identify such meaningful visual abstractions for visualization, their effectiveness for human perception and cognition has to be assessed, and they have to be formalized in order to make them applicable in rendering algorithms. In this project, we try to advance the understanding of procedural visual abstraction of complex physiological processes that describe the complex machinery of biological life.", "website": "https://www.cg.tuwien.ac.at/research/area/IllVis", "teaser": { "name": "teaser.jpg", "path": "research_area:IllVis", "type": "image/jpeg", "size": 34861, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/IllVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "antes-2026-maa", "Antonini2020", "Balabanian-2010-IIV", "Balduz_01", "Bayat_2019", "Bechtold2020", "Birkeland-2012-IMC", "brandstaetter_01", "bruckner-2005-ICV", "bruckner-2006-ICE", "bruckner-2007-STF", "bruckner-2008-IIV", "bruckner-2010-HVC", "bruckner-2010-IFC", "cellVIEW_2015", "Chen-Information-2016", "Deutsch-2018", "Dhanoa_2021", "Dhanoa2024", "dietrich-2016-viseq2", 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"BioNetIllustration: User Centric Illustrations of Biological Networks", "name_de": null, "short_title": "BioNetIllustration", "website": null, "status": "active", "short_abstract": "

In living systems, one molecule is commonly involved in several distinct physiological functions. The roles of molecules are commonly summarized in pathway diagrams, which, however, are abstract, hierarchically nested and thus is difficult to comprehend especially by non-expert audience. The primary goal of this research in visualization is to intuitively support the comprehensive understanding of relationships among biological networks using interactively computed illustrations. Illustrations, especially in textbooks of biology are carefully designed to clearly present reactions between organs as well as interactions within cells. Automatic generation of illustrative visualizations of biological networks is thus the technical content of this proposal. Automatic generation of hand-drawn illustrations has been a challenging task due to the difficulty of algorithmically describing a human creative process such as evaluating and selecting significant information and composing meaningful explanations in a visually plausible manner. The project also involves experts from several disciplines including network and medical visualization, data mining, systems biology as well as perceptual psychology. The result will provide a new direction for physiological process analysis and accelerate the knowledge transfer not only within experts but also to the public. Acknowledgment: The project has received funding from the European Union Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 747985.

\r\n", "abstract": "

In living systems, one molecule is commonly involved in several distinct physiological functions. The roles of molecules are commonly summarized in pathway diagrams, which, however, are abstract, hierarchically nested and thus is difficult to comprehend especially by non-expert audience. The primary goal of this research in visualization is to intuitively support the comprehensive understanding of relationships among biological networks using interactively computed illustrations. Illustrations, especially in textbooks of biology are carefully designed to clearly present reactions between organs as well as interactions within cells. Automatic generation of illustrative visualizations of biological networks is thus the technical content of this proposal. Automatic generation of hand-drawn illustrations has been a challenging task due to the difficulty of algorithmically describing a human creative process such as evaluating and selecting significant information and composing meaningful explanations in a visually plausible manner. The project also involves experts from several disciplines including network and medical visualization, data mining, systems biology as well as perceptual psychology. The result will provide a new direction for physiological process analysis and accelerate the knowledge transfer not only within experts but also to the public. Acknowledgment: The project has received funding from the European Union Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 747985.

\r\n", "start_date": "2017-06-21", "end_date": "2019-06-20", "leader_id": 1464, "logo": { "name": "logo.png", "path": "project:BioNetIllustration", "type": "image/png", "size": 16337, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/BioNetIllustration/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "Horizon 2020", "contract_number": "747985", "comment": null } ], "research_areas": [ "BioVis", "InfoVis" ], "publications": [ "cmolik-2020-tvcg", "kouril-2018-LoL", "mizuno-2019-eurovis", "Purchase-2020-gd", "rinortner_susanne-2019-vpicc", "Sbardellati-2019-vcbm", "wu-2017-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-shonan", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg", "YOGHOURDJIAN2019" ], "url": "https://www.cg.tuwien.ac.at/research/projects/BioNetIllustration", "__class": "Project" }, { "id": "illvisation", "workgroup_id": "vis", "drupal_id": 4171, "drupal_path": "/research/projects/illvisation", "name": "Visual Computing: Illustrative Visualization", "name_de": null, "short_title": "illvisation", "website": null, "status": "active", "short_abstract": "

The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/

\r\n\r\n

Prototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/

\r\n\r\n

cellVIEW

\r\n\r\n

cellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.

\r\n\r\n

Invited Talks

\r\n\r\n

18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness

\r\n", "abstract": "

The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/

\r\n\r\n

Prototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/

\r\n\r\n

cellVIEW

\r\n\r\n

cellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.

\r\n\r\n

Invited Talks

\r\n\r\n

18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness

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We\ndeveloped an automatic approach to hierarchically decompose the screen\nspace to multiple functional regions and embed sub-pathways into their\ncorresponding regions to unveil complex metabolite relationships.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "wu-2019-vcbm-image.png", "type": "image/png", "size": 109418, "path": "Publication:wu-2019-vcbm", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-vcbm/wu-2019-vcbm-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-vcbm/wu-2019-vcbm-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1464, "drupal_id": 1266, "orcid_id": "0000-0003-1028-0010", "website": 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"wu-2018-shonan", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-smwp", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-eurovis-star", "wu-2020-tvcg", "wu-2021", "wu-2021-vi", "YOGHOURDJIAN2019" ], "publications_first": [], "project_leader": [ "BioNetIllustration" ], "publication_field": [ { "publ_id": "8564188", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Batik-2021", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Deutsch-2018", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Ehlers_PhD", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Ismail-2018", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "koeppel-2021", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Koeppel2020", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Kompatscher-2021", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "korpitsch_thorsten-2019", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": 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research area, we develop new visualization techniques to support biologists in data analysis and create visualizations to disseminate scientific discoveries in biology.", "abstract": "In modern biological research domain experts have to deal with complex and large data collections and simulations. Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n", "website": "https://www.cg.tuwien.ac.at/research/area/BioVis", "teaser": { "name": "teaser.png", "path": "research_area:BioVis", "type": "image/png", "size": 16330957, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/BioVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "amirkhanov-2019-manylands", "byska-2019-mdfc", "cellVIEW_2015", "cmolik-2020-tvcg", "Dietrich_1", "dietrich-2016-viseq2", "Ehlers_PhD", "ehlers-2025-ait", "eschner-2023-ims", "eschner-blur-2022", "Escribano_2017", "Furmanova_2018", "Gehrer-2017", "Gehrer-2017-molmach", "glinzner-2016-tex", "Halladjian_2020", "kapferer-2017-godot", "klein_2017_IM", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koch-2018-sso", "Kolesar-Fractional-2016", "kolesar-ivan-2014-polymers", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kozlikova-Visualization-2016b", "Krone2016VABC", "Kugler_2019", "lemuzic_2015_timelapse", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lipp-2017-mgpu", "lipp-2017-vulkan", "Manczarski-2016", "manylands_award", "Miao_2019", "miao_inria_2017", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-xmas-card-2016", "Mitterhofer_2017", "nguyen_2020-covid", "Nowak_2020", "raidou_2019_springer", "raidou_shonan167", "raidou2018visualflatter", "rasch-2016-imgses", "Reisacher2016", "rinortner_susanne-2019-vpicc", "Sarkis_2021", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2013-neuromap", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "stappen_2017_animatedcomic", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "trautner-2018-imd", "unger-2019_vcp", "vad_2015_phd", "vad_viktor-2017-WVE", "vad-2016-bre", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "waldin-2019-ccm", "waldner-2014-af", "Weissenboeck_2019", "wu-2017-dagstuhl", "wu-2018-metabo", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg" ], "projects": [ "BioNetIllustration", "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=BioVis", "__class": "ResearchArea" }, { "id": "InfoVis", "drupal_id": 4128, "name": "Information Visualization and Visual Analytics", "short_abstract": "In this research area, our focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning. ", "abstract": "

Data and information created by various processes (e.g., simulations) is getting larger, and more and more complex. We use interactive visualization and analysis techniques to facilitate exploration of complex parameter spaces (e.g., to analyze and compare parameters for automotive engineering, reconstruction algorithms, or geometry generators) or unstructured information collections (e.g., annotated digital documents or image collections). Our research focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning.

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"eiweck-hnv-2021", "ellhotka-2025-ipo", "eschner-2023-evl", "eschner-2025-ide", "Escribano_2017", "fourousan2021", "furmanova_2020", "Gadllah_Hani_2016", "Gall2020", "Ganuza_ML_2015_ISA", "georgiev-2019-cbg", "geyer_lukas_2015_prj", "geymayer-2017-std", "Groeller_2011_CW", "Groeller_2011_NR", "Groeller_2014_RWA", "Groeller_2016_P1", "Groeller_2016_P2", "Groeller_2016_P4", "Groeller_2016_P6", "Groeller_2021-10", "Groeller_V2_2020", "Groeller_V3_2020", "Groeller_V5_2020", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", "gundacker-2020-wlm", "gusenbauer-2018", "gusenbauer-2018-P", "Heim_2021", "heim-2024-accustripes", "heim-gall-2020-dde", "Heinzl2021", "holzer-edo", "hromniak-2019-vcn", "huber-2025-eed", "Iijima-2020-iV", "indirectBiasLanguageModels-2023", "irendorfer-2024-uat", "karnik-09-shapegrammar", "Kehrer-2010-mom", "kehrer-2012-mod", "kehrer-2013-SBC", "Kehrer-2013-STAR", "klaffenboeck-2024-rva", "klaffenboeck-thesis", "Klein_Tobias_2015TIV", "klein-2016-WCL", 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"d9522", "d9555", "deskollage", "Scenario Pool" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=InfoVis", "__class": "ResearchArea" } ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image-full", "main_file": true, "use_in_gallery": false, "access": "public", "image_width": 8878, "image_height": 6919, "name": "wu-2019-vcbm-image-full.png", "type": "image/png", "size": 15607607, "path": "Publication:wu-2019-vcbm", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-vcbm/wu-2019-vcbm-image-full.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-vcbm/wu-2019-vcbm-image-full:thumb{{size}}.png" }, { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "wu-2019-vcbm-image.png", "type": "image/png", "size": 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In living systems, one molecule is commonly involved in several distinct physiological functions. The roles of molecules are commonly summarized in pathway diagrams, which, however, are abstract, hierarchically nested and thus is difficult to comprehend especially by non-expert audience. The primary goal of this research in visualization is to intuitively support the comprehensive understanding of relationships among biological networks using interactively computed illustrations. Illustrations, especially in textbooks of biology are carefully designed to clearly present reactions between organs as well as interactions within cells. Automatic generation of illustrative visualizations of biological networks is thus the technical content of this proposal. Automatic generation of hand-drawn illustrations has been a challenging task due to the difficulty of algorithmically describing a human creative process such as evaluating and selecting significant information and composing meaningful explanations in a visually plausible manner. The project also involves experts from several disciplines including network and medical visualization, data mining, systems biology as well as perceptual psychology. The result will provide a new direction for physiological process analysis and accelerate the knowledge transfer not only within experts but also to the public. Acknowledgment: The project has received funding from the European Union Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 747985.

\r\n", "abstract": "

In living systems, one molecule is commonly involved in several distinct physiological functions. The roles of molecules are commonly summarized in pathway diagrams, which, however, are abstract, hierarchically nested and thus is difficult to comprehend especially by non-expert audience. The primary goal of this research in visualization is to intuitively support the comprehensive understanding of relationships among biological networks using interactively computed illustrations. Illustrations, especially in textbooks of biology are carefully designed to clearly present reactions between organs as well as interactions within cells. Automatic generation of illustrative visualizations of biological networks is thus the technical content of this proposal. Automatic generation of hand-drawn illustrations has been a challenging task due to the difficulty of algorithmically describing a human creative process such as evaluating and selecting significant information and composing meaningful explanations in a visually plausible manner. The project also involves experts from several disciplines including network and medical visualization, data mining, systems biology as well as perceptual psychology. The result will provide a new direction for physiological process analysis and accelerate the knowledge transfer not only within experts but also to the public. Acknowledgment: The project has received funding from the European Union Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 747985.

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Screening the development of the fetus is important to assess possible complications early on. State of the art approaches involve taking standardized measurements to compare them with standardized tables. The measurements are taken\nin a 2D slice view, where precise measurements can be difficult to acquire due to the fetal pose. Performing the analysis in a\n3D view would enable the viewer to better discriminate between artefacts and representative information. Additionally making\ndata comparable between different investigations and patients is a goal in medical imaging techniques and is often achieved by\nstandardization. With this paper, we introduce a novel approach to provide a standardization method for 3D ultrasound fetus\nscreenings. Our approach is called “The Vitruvian Baby” and incorporates a complete pipeline for standardized measuring\nin fetal 3D ultrasound. The input of the method is a 3D ultrasound screening of a fetus and the output is the fetus in a standardized T-pose. In this pose, taking measurements is easier and comparison of different fetuses is possible. In addition to the\ntransformation of the 3D ultrasound data, we create an abstract representation of the fetus based on accurate measurements.\nWe demonstrate the accuracy of our approach on simulated data where the ground truth is known.\n", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "name": "vitruvian_2019-.pdf", "type": "application/pdf", "size": 1371768, "path": "Publication:vitruvian_2019", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/vitruvian_2019/vitruvian_2019-.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/vitruvian_2019/vitruvian_2019-:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1345, "drupal_id": null, "orcid_id": "0000-0003-1625-0146", "website": null, "firstname": "Eric", "lastname": 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Due to the increasing amount of data generated by hospital information systems, visualization becomes successively more important. Extracting certain trends from such highly diverse data by suitable visual mappings is one of the primary goals of medical visualization. The data is usually acquired by computed tomography, magnetic resonance imaging or ultrasound.\n\nCurrently, our research addresses the analysis of blood vessels such as the inspection of possible stenotic regions or their spatial arrangement as in the Circle of Willis. Furthermore, we investigate aneurysm classification and lesion detection as well as visualization. Another research area deals with realistic prenatal visualization of the fetus in-vivo and in real-time. 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"https://www.cg.tuwien.ac.at/research/publications/2019/vitruvian_2019/", "__class": "Publication" }, { "id": "klein_2019_PMP", "type_id": "journalpaper", "tu_id": null, "repositum_id": "20.500.12708/57947", "title": "Multi-Scale Procedural Animations of Microtubule Dynamics Based on Measured Data", "date": "2019-08", "abstract": "Biologists often use computer graphics to visualize structures, which due to physical limitations are not possible to imagewith a microscope. One example for such structures are microtubules, which are present in every eukaryotic cell. They are part ofthe cytoskeleton maintaining the shape of the cell and playing a key role in the cell division. In this paper, we propose a scientifically-accurate multi-scale procedural model of microtubule dynamics as a novel application scenario for procedural animation, which cangenerate visualizations of their overall shape, molecular structure, as well as animations of the dynamic behaviour of their growth anddisassembly. The model is spanning from tens of micrometers down to atomic resolution. All the aspects of the model are driven byscientific data. The advantage over a traditional, manual animation approach is that when the underlying data change, for instance dueto new evidence, the model can be recreated immediately. The procedural animation concept is presented in its generic form, withseveral novel extensions, facilitating an easy translation to other domains with emergent multi-scale behavior.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1706, "image_height": 770, "name": "klein_2019_PMP-image.jpg", "type": "image/jpeg", "size": 953504, "path": "Publication:klein_2019_PMP", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/klein_2019_PMP/klein_2019_PMP-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/klein_2019_PMP/klein_2019_PMP-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1285, "drupal_id": 1146, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/TobiasKlein", "firstname": 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create visualizations to disseminate scientific discoveries in biology.", "abstract": "In modern biological research domain experts have to deal with complex and large data collections and simulations. Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n", "website": "https://www.cg.tuwien.ac.at/research/area/BioVis", "teaser": { "name": "teaser.png", "path": "research_area:BioVis", "type": "image/png", "size": 16330957, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/BioVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "amirkhanov-2019-manylands", "byska-2019-mdfc", "cellVIEW_2015", "cmolik-2020-tvcg", "Dietrich_1", "dietrich-2016-viseq2", "Ehlers_PhD", "ehlers-2025-ait", "eschner-2023-ims", "eschner-blur-2022", "Escribano_2017", "Furmanova_2018", "Gehrer-2017", "Gehrer-2017-molmach", "glinzner-2016-tex", "Halladjian_2020", "kapferer-2017-godot", "klein_2017_IM", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koch-2018-sso", "Kolesar-Fractional-2016", "kolesar-ivan-2014-polymers", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kozlikova-Visualization-2016b", "Krone2016VABC", "Kugler_2019", "lemuzic_2015_timelapse", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lipp-2017-mgpu", "lipp-2017-vulkan", "Manczarski-2016", "manylands_award", "Miao_2019", "miao_inria_2017", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-xmas-card-2016", "Mitterhofer_2017", "nguyen_2020-covid", "Nowak_2020", "raidou_2019_springer", "raidou_shonan167", "raidou2018visualflatter", "rasch-2016-imgses", "Reisacher2016", "rinortner_susanne-2019-vpicc", "Sarkis_2021", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2013-neuromap", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "stappen_2017_animatedcomic", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "trautner-2018-imd", "unger-2019_vcp", "vad_2015_phd", "vad_viktor-2017-WVE", "vad-2016-bre", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "waldin-2019-ccm", "waldner-2014-af", "Weissenboeck_2019", "wu-2017-dagstuhl", "wu-2018-metabo", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg" ], "projects": [ "BioNetIllustration", "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=BioVis", "__class": "ResearchArea" }, { "id": "IllVis", "drupal_id": 4131, "name": "Illustrative Visualization", "short_abstract": "In this research area, we develop rendering methods that are inspired by scientific illustrations, in order to make complex biological information more intuitive to understand and more pleasant to read.", "abstract": "Scientific illustration is concerned with researching ways in which complex biological and medical data can be abstracted in order to convey a desired information that would otherwise be impossible or hard to retrieve from the original data. Illustrators apply such techniques, for instance, to present non-important parts of an organ in a simplified way, while using detailed representations to put the focus of attention on a region where a tumor might be situated.\n\nTo identify such meaningful visual abstractions for visualization, their effectiveness for human perception and cognition has to be assessed, and they have to be formalized in order to make them applicable in rendering algorithms. In this project, we try to advance the understanding of procedural visual abstraction of complex physiological processes that describe the complex machinery of biological life.", "website": "https://www.cg.tuwien.ac.at/research/area/IllVis", "teaser": { "name": "teaser.jpg", "path": "research_area:IllVis", "type": "image/jpeg", "size": 34861, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/IllVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "antes-2026-maa", "Antonini2020", "Balabanian-2010-IIV", "Balduz_01", "Bayat_2019", "Bechtold2020", "Birkeland-2012-IMC", "brandstaetter_01", "bruckner-2005-ICV", "bruckner-2006-ICE", "bruckner-2007-STF", "bruckner-2008-IIV", "bruckner-2010-HVC", "bruckner-2010-IFC", "cellVIEW_2015", "Chen-Information-2016", "Deutsch-2018", "Dhanoa_2021", "Dhanoa2024", "dietrich-2016-viseq2", "donabauer_2019_1", "eg-tut2005-iv", "eschner-2023-ims", "Essler2022", "gangl-2018-gpsart", "Gehrer_Daniel_CUI", "Gehrer-2017-molmach", "gerl-2006-vhi", "Gogel2020", "Groeller_2011_IPV", "Groeller_2016_I3", "Groeller_2016_I6", "Groeller_2016_I7", "Groeller_2016_I8", "Groeller_V1_2020", "groeller-2006-ivt", "groeller-2007-fci", "groeller-2008-irs", "Groeller-2010-IFI", "gruber-2025-vps", "Halladjian_2020", "haushofer-2018-skinning", "Heim_2020", "horvath-2018-ism", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "Knapp_2017_CVR", "Koeppel2020", "kolesar-ivan-2014-polymers", "Konev-FCV2018", "Koszticsak-2017-ewt", "Kouril_2017_11", "kouril-2020-hyperlabels", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "kroesl_x_card_2017", "Lackner_2022", "Langer_Edith_IR1", "lawonn-2018-illvisstar", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "LeMuzic_2016_PhD", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "Leutschacher_2022", "ludwig-2012-MT", "Manczarski-2016", "Matusich-2017-01", "Mautner 2020", "Mayr-2017-1", "Melo_2018_11", "Meusburger_2020", "Miao_2019", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao2018Dimsum", "Michl_2017_CSV", "mindek-2015-mc", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-2019-mci", "mindek-xmas-card-2016", "Moellinger_Christian_IDE2", "Niedermayer_2018", "Ortner_PhD", "Ortner2020", "pahr-2021-vologram", "Panayotov", "patel_daniel_2007_IRSD", "Pauschenwein_2022", "Peter_2012_AIV", "plank-2017-sldg", "prost-2016-molecule", "purgathofer-2008-cgi", "Radwan-2017-Occ", "Rautek-2007-SLI", "Rautek-2008-IDS", "Rautek-2008-VF", "Reichinger_2016", "Reichinger_Fuhrmann_2016", "Reisacher_Matthias_CPW", "Reisacher2016", "Riegelnegg_2019", "rippl-2023-atg", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "schindler_2020vis", "schmidlehner2021", "scholz_2021", "Schrempf_2020", "schultes_lampi", "seyfert-2017", "sikachev-2010-ill_vis_vol_ren", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "Spechtenhauser_Florian_2016", "stappen_2017_animatedcomic", "Stoll2020", "sturl_2016_dynlabels", "Swoboda2020", "szabo_patrik-2022-tour", "takahashi-2019-acdt", "Thomas-2018", "TR-186-2-07-08", "Troidl_2021", "Troidl_2022", "tut-eg-2006", "tut-siggraph-2006", "tut-vis-2006", "tut-vis-2007", "Unger2020", "Vasileva_2022", "Viola_Ivan_2013_SVA", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "viola-evr", "Viola-Pondering-2017", "Viola-vistutillustrativevis", "Waldin_Nicholas_2016_Colormaps", "waldin-2019-ccm", "Waldner_2017_11", "Wihann_2017", "Woschizka_2021", "wu-2019-bmc", "wu-2019-report", "Zaufel_2021", "zechmeister2020", "Zeng_2021", "Zusag-2017-Bach" ], "projects": [ "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=IllVis", "__class": "ResearchArea" }, { "id": "Modeling", "drupal_id": 4130, "name": "Modeling", "short_abstract": "In this area, we focus on researching methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.", "abstract": "One of the major bottlenecks in the field of computer graphics is the one of content creation, particularly the creation of high-quality 3D geometric models. These models are a demand in many industries, such as entertainment, computer-aided design, urban planning, the fabrication of physical objects, as well as research areas like medical or scientific visualizations and simulations.\n\nWhile rendering - the classical field of computer graphics - has reached very high standards in the recent two decades, the issue of the creation of appropriate digital models is a difficult problem that hardly keeps pace with current demands. Indeed, it is a complex creative process that involves both artistic and technical skills.\n\nTo make this process easier, our goal in this research area is to find new methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.", "website": "https://www.cg.tuwien.ac.at/research/area/Modeling", "teaser": { "name": "teaser.jpg", "path": "research_area:Modeling", "type": "image/jpeg", "size": 190581, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Modeling/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "AA2020", "Adorjan-2015", "aichner-2016-sadf", "arikan-2013-osn", "birsak-thesis", "Birsak2018-SA", "Brandstaetter2020", "brunner_lukas_2022_ssb", "Caic2021", "clemenz_2019_rosy_fields", "DOG10", "dusberger-2010-msm", "eibens-2021-tsgpmg", "eibensteiner-2021-pmcg", "eibner-2009-gpc", "Erhardt_2025_Scutes", "erler_2024_ppsurf", "erler_philipp-2016-femfluid-prakt", "erler_philipp-2017-phd", "erler-2020-p2s", "erler-2025-lidarscout", "fan-2014-scfl", "ferschin-1992-kons", "fiedler-2009-php", "fleiss-2015-da", "GAHR-2013-AGM", "gamsjaeger-2022-proc", "gersthofer-2016-sosob", "gervautz-1989-sol1", "gervautz-1993-use", "griessmair-1989-def1", "groeller-1992-frac", "groeller-1995-mod", "Groeller-1995-SDC", "Grossfurtner-2023-paego", "Guerrero-2014-GRF", "Guerrero-2014-TPS", "guerrero-2015-lsp", "HECHER-2017-HDY", "hiess-1992-comb", "hofer_kerstin-2023-sketch2model", "honic-2020-w78", "HU-2017-ETM", "HUMMEL-2001-MSE", "Ilcik_2015_LAY", "ilcik-2010-ps", "ilcik-2013-cipmi", "ilcik-2014-cgbpmi", "ilcik-2016-cmssg", "ilcik-2021-xmas", "kapferer_2021_advancing", "karnik-09-shapegrammar", "Kellner-2021-DA", "kendlbacher-2016", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koenigsberger-2024-msu", "komon-2025-webigeo", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kraehsmaier-dsc", "kreuzer-2016-isf", "kuehtreiber-2010-ikph", "leimer_2017_rbpesc", "leimer_2020-cag", "leimer-2016-coan", "leimer-2016-rpe", "leimer-2018-sar", "leimer-2023-ecd", "LEOPOLD-2017-ALG", "LIPP-2007-CGA", "LIPP-2008-IEV", "LIPP-2009-PGL", "LIPP-2009-PGL2", "lipp2011a", "Lupu-2026-Cloth", "macho_jonas-2024-baa", "Maierhofer-thesis", "manpreet_kainth-2012-rus", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_thesis_2019", "mindek-xmas-card-2016", "mujadzic-2023-hfp", "musialski-2009-sbfr", "musialski-2010-pfi", "musialski-2010-tof", "musialski-2012-icb", "musialski-2012-sur", "Musialski-2013-ipmum", "musialski-2013-surcgf", "NIEDERREITER-2010-SIM", "Pahr2020", "Parzer_2013_IIG", "pegrisch_2018_uvs", "Pel-2026", "pogrzebacz-2014-gggm", "polzer-sog", "preiner_2017_phd", "PUEYO-2019-SCL", "RADAX-2010-LOD", "Radwan_2021_Occ", "rasch-2016-imgses", "recheis-2009-arr", "Reichinger-12", "reisinger-2023-iad", "reisner-2010-ind", "reisner-2011-akgeo", "reitsamer-2008-tsud", "Rumpelnik_Martin-2020-NPR", "scharl-master-thesis", "schneider-sturm-2026-mia", "scholz_2017_bac", "SCHWAERZLER-2017-SBGM", "SIETZEN-2017-BBO", "sifuentes-2018-crowd", "sippl-2014-fss", "sperl-2013-BA", "spitaler-2015-pbi", "steiner_2016_isad", "steiner-2014-da", "steinkellner-2022-dll", "steinschorn-2023-p2m", "steinschorn-2025-par", "steinschorn-2025-parameter", "tobler02_amrmg", "tobler02_mbpls", "Traxler-1996-GAI", "VASILJEVS-2018-PMPL", "Viola_Ivan_2013_RMA", "Viola_Ivan_2013_RSb", "weiner_2011", "WIMMER-2015-CGFC", "WIMMER-2016-FUTURIS", "WIMMER-2020-ASG", "wimmer-2023-acd", "Winkler-2017", "WINKLER-2019-PDG", "Wonka-2003-Ins", "xmas-2024", "zeiller-1993-coll", "Zotti-2003-AMP", "zotti-2003-ash", "zotti-2006-pla", "zotti-2007-eg" ], "projects": [ "3DSpatialization", "d4388", "EVOCATION", "GAMEWORLD", "Harvest4D", "PAMINA", "Photo-Guide", "REPLICATE", "SCI_BIM", "Wohnen 4.0" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Modeling", "__class": "ResearchArea" }, { "id": "Rendering", "drupal_id": 4134, "name": "Rendering", "short_abstract": "In this area, we concentrate on algorithms that synthesize images to depict 3D models or scenes, often by simulating or approximating the physics of light.", "abstract": "The rendering of 3D models and scenes has been a major, long-standing challenge in computer graphics that can be divided into two major subfields. Real-time rendering refers to the real-time synthesis of images on commodity graphics hardware to facilitate interaction for visualizations or computer games. The field of physically based rendering focuses on algorithms that accurately simulate the physics of light for use in the movie industry, architectural visualizations, etc. Compared to real-time rendering methods, these algorithms generally require a considerable amount of time (i.e., hours up to days) to generate acceptable results.\n\nIn the context of real-time rendering, our work revolves around the development of algorithms to achieve higher visual quality. Furthermore, we work on techniques to accelerate physically based rendering algorithms to make them viable for interactive rendering. Another aspect of our research work revolves around tools that facilitate the work of content creators.", "website": "https://www.cg.tuwien.ac.at/research/area/Rendering", "teaser": { "name": "teaser.png", "path": "research_area:Rendering", "type": "image/png", "size": 5244928, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Rendering/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "2011scherzerE", "2018_Mautner_Praktikum", "ABG25", "Adorjan-2015", "agyemang-2021-bsdfproxyppg", "Ams25", "antes-g", "arikan-2014-pcvis", "arikan-2015-dmrt", "Artusi-2003-Del", "ASCHL-2022-OTV", "Auzinger_2012_AAA", "Auzinger_2012_GeigerCam", "Auzinger_2013_AnaVis", "Auzinger_2013_NSAA", "Auzinger_2013_SAR", "Auzinger_2014_DCGI", "Auzinger_2014_UJA", "Auzinger-2015-IST", "bagar2010", "balvan-g", "Bauer_Dominik_2018_VR", "BAUER-2024-PWG", "BAUER-2025-PCW", "bernhard-2011-bmtf", "bernhard-2014-GTOM", "bhagvat-09-frusta", "birsak-2013-sta", "Bittner-2001-Vis", "Bittner-2003-Vis", "Bittner-2004-CHC", "bittner-2005-egsr", "BITTNER-2009-AGVS", "BITTNER-2009-GEFOC", "bittner-2011-scc", "BOKSANSKY-2019-RTS", "brandmair-2025-rub", "brugger-2020-tdp", "brugger-2020-tsdpbr", "Brusi-2001-Opt", "CADIK-2006-IAQ", "CADIK-2008-EHD", "cardoso-2021-cost", "cardoso-2022-rtpercept", "cardoso-2024-r-c", "cardoso-thesis", "cech-2023-taa", "celarek_adam-2019-qelta", "CELAREK-2017-QCL", "CHARALAMBOS-2007-HLOD", "charpenay-2014-sgn", "Che-2025", "cline-09-poisson", "CORNEL-2017-FRS", "CORNEL-2019-IVF", "Derflinger-2026-RTTW2", "Devlin-2002-STA", "dodik-2017-pcbpt", "dworschak-2024-aml", "ecormier-nocca-2025-sls", "eichner-2024-erv", "eickmeyer-2027-tcd", "EISEMANN-2011-RTS", "EISEMANN-2012-ERT", "EISEMANN-2013-ERT", "elagabani-2025-ieh", "Erhardt_Seirlehner-2024-TamashiiIntegration", "ERLER-2017-HVR", "ESBERGER-2016-AHO", "ESCHNER-2019-GDT", "fink-2012-cg1", "Fischer-2018-sssvr", "FRAISS-2017-PCU", "FRAISS-2022-CGMM", "freude_2020_rs", "FREUDE-2015-phd", "freude-2023-prh", "freude-2023-sem", "freude-2025-iso", "freude-2025-ras", "GAMPER-2018-OSG", "GANTNER-2018-ARO", "GANTNER-2019-CRS", "gersthofer_2017_COP", "geyer-2018-apbf", "GIEGL-2006-QVS", "GIEGL-2007-FVS", "GIEGL-2007-QV1", "GIEGL-2007-UNP", "gilmutdinov-2022-aomlbwug", "glanz-2017-pbrcomparison", "goel-2024-rdr", "gramegna-rfr", "GRELAUD-2009-EPA", "GRIESHOFER-2018-GOS", "Grisenti-2026-HSHPG", "Groeller_2016_P3", "Grossfurtner-2023-paego", "Gruber2019", "guerrero-2008-sli", "Habel_07_xms", "Habel_08_SSH", "Habel_09_PGT", "Habel_2007_IAG", "Habel_2007_RTT", "Habel_2009_PhD", "Habel_2012_PSP", "Habel_LSN_2011", "Habel_RAV_2010", "Habel-09-RAT", "Habel-09-THB", "Habel-2010-EIN", "HAFNER-2015-FEM", "HANN_2022_IPT", "hasbay-2026-tfo", "havran-2005-egsr", "havran-2005-sccg", "havran-2006-tut", "hecher-2012-MH", "hecher-2014-MH", "heinz-2019-psi", "hladky-2022-QS", "hofer_kerstin-2023-sketch2model", "horvath_imp", "houska-2020-IPGM", "huber-2025-esl", "huerbe-2019-BA", "intel2016", "ioannis-2026-sro", "JAHRMANN-2013-IGR", "JAHRMANN-2015-GRASS", "JAHRMANN-2016-IGR", "JAHRMANN-2017-RRTG", "jeschke-05-AIP", "jeschke-05-ARI", "jeschke-05-ISTAR", "jeschke-09-praguetalk", "jeschke-09-rendering", "Jeschke-2002-LEMA", "Jeschke-2002-TDMR", "JESCHKE-2007-ISC", "jeschke-2010-diff", "jeschke-2011-est", "Jimenez_SSS_2015", "KAFKA-2014-19MRD", "Kathi-2018-VRB", "Keilman2022", "Kellner-2021-DA", "kendlbacher-2016", "kerbl_2019_planet_poster", "kerbl_2021_hdg", "kerbl-2020-improvencoding", "kerbl-2022-trienc", "kerbl-2024-ah3", "kimmersdorfer-2024-vcpr", "kimmersdorfer-fancyMaps-2023", "KLAUS-2020-PCC", "klein_2019_PHD", "klein_2019_PMP", "klein-2020-rtgi", "knecht_2013_RSM", "knecht_martin_2010_DIR", "knecht_martin_2012_BRDFEstimation", "knecht_martin_2012_RSMR", "knecht_martin_2013_ReflRefrObjsMR", "knecht_martin-2011-FPSPAR", "knecht-2007-ao", "knecht-2011-CBCM", "koch-2019-PR", 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"publ_id": "Matusich-2017-01", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Mazza_2021_05", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "miao_thesis_2019", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Mitterhofer_2017", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "moerth-2018-tpose", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Plank_Pascal_2015_HVP", "field_id": "supervisor", "ordernum": 2 }, { "publ_id": "plank-2017-sldg", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "puenguentzky-2014-ht", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "raidou_vcbm14", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "rasch-2016-imgses", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "rautek-2009-vmv", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Reisacher_Matthias_CPW", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "sbardellati_ba_2018", "field_id": "supervisor", "ordernum": 0 }, { 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"Author" }, { "id": 1473, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Ivan", "lastname": "Barisic", "searchname": "Ivan Barisic", "is_teacher": false, "name": "Ivan Barisic", "publications": [ "miao_nantech_2019", "miao_nar_2020", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "Sbardellati-2019-vcbm" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1473", "__class": "Author" } ], "date_from": "2019-05-27", "date_to": "2019-05-29", "event": "NANTECH 2019 – Nucleic Acid Nanotechnology: From Algorithmic Design to Biochemical Applications – Espoo, Finland", "research_areas": [ { "id": "BioVis", "drupal_id": 4127, "name": "Biological Data Visualization", "short_abstract": "In this research area, we develop new visualization techniques to support biologists in data analysis and create visualizations to disseminate scientific discoveries in biology.", "abstract": "In modern biological research domain experts have to deal with complex and large data collections and simulations. Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n", "website": "https://www.cg.tuwien.ac.at/research/area/BioVis", "teaser": { "name": "teaser.png", "path": "research_area:BioVis", "type": "image/png", "size": 16330957, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/BioVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "amirkhanov-2019-manylands", "byska-2019-mdfc", "cellVIEW_2015", "cmolik-2020-tvcg", "Dietrich_1", "dietrich-2016-viseq2", "Ehlers_PhD", "ehlers-2025-ait", "eschner-2023-ims", "eschner-blur-2022", "Escribano_2017", "Furmanova_2018", "Gehrer-2017", "Gehrer-2017-molmach", "glinzner-2016-tex", "Halladjian_2020", "kapferer-2017-godot", "klein_2017_IM", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koch-2018-sso", "Kolesar-Fractional-2016", "kolesar-ivan-2014-polymers", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kozlikova-Visualization-2016b", "Krone2016VABC", "Kugler_2019", "lemuzic_2015_timelapse", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lipp-2017-mgpu", "lipp-2017-vulkan", "Manczarski-2016", "manylands_award", "Miao_2019", "miao_inria_2017", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-xmas-card-2016", "Mitterhofer_2017", "nguyen_2020-covid", "Nowak_2020", "raidou_2019_springer", "raidou_shonan167", "raidou2018visualflatter", "rasch-2016-imgses", "Reisacher2016", "rinortner_susanne-2019-vpicc", "Sarkis_2021", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2013-neuromap", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "stappen_2017_animatedcomic", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "trautner-2018-imd", "unger-2019_vcp", "vad_2015_phd", "vad_viktor-2017-WVE", "vad-2016-bre", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "waldin-2019-ccm", "waldner-2014-af", "Weissenboeck_2019", "wu-2017-dagstuhl", "wu-2018-metabo", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg" ], "projects": [ "BioNetIllustration", "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=BioVis", "__class": "ResearchArea" }, { "id": "IllVis", "drupal_id": 4131, "name": "Illustrative Visualization", "short_abstract": "In this research area, we develop rendering methods that are inspired by scientific illustrations, in order to make complex biological information more intuitive to understand and more pleasant to read.", "abstract": "Scientific illustration is concerned with researching ways in which complex biological and medical data can be abstracted in order to convey a desired information that would otherwise be impossible or hard to retrieve from the original data. Illustrators apply such techniques, for instance, to present non-important parts of an organ in a simplified way, while using detailed representations to put the focus of attention on a region where a tumor might be situated.\n\nTo identify such meaningful visual abstractions for visualization, their effectiveness for human perception and cognition has to be assessed, and they have to be formalized in order to make them applicable in rendering algorithms. In this project, we try to advance the understanding of procedural visual abstraction of complex physiological processes that describe the complex machinery of biological life.", "website": "https://www.cg.tuwien.ac.at/research/area/IllVis", "teaser": { "name": "teaser.jpg", "path": "research_area:IllVis", "type": "image/jpeg", "size": 34861, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/IllVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "antes-2026-maa", "Antonini2020", "Balabanian-2010-IIV", "Balduz_01", "Bayat_2019", "Bechtold2020", "Birkeland-2012-IMC", "brandstaetter_01", "bruckner-2005-ICV", "bruckner-2006-ICE", "bruckner-2007-STF", "bruckner-2008-IIV", "bruckner-2010-HVC", "bruckner-2010-IFC", "cellVIEW_2015", "Chen-Information-2016", "Deutsch-2018", "Dhanoa_2021", "Dhanoa2024", "dietrich-2016-viseq2", "donabauer_2019_1", "eg-tut2005-iv", "eschner-2023-ims", "Essler2022", "gangl-2018-gpsart", "Gehrer_Daniel_CUI", "Gehrer-2017-molmach", "gerl-2006-vhi", "Gogel2020", "Groeller_2011_IPV", "Groeller_2016_I3", "Groeller_2016_I6", "Groeller_2016_I7", "Groeller_2016_I8", "Groeller_V1_2020", "groeller-2006-ivt", "groeller-2007-fci", "groeller-2008-irs", "Groeller-2010-IFI", "gruber-2025-vps", "Halladjian_2020", "haushofer-2018-skinning", "Heim_2020", "horvath-2018-ism", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "Knapp_2017_CVR", "Koeppel2020", "kolesar-ivan-2014-polymers", "Konev-FCV2018", "Koszticsak-2017-ewt", "Kouril_2017_11", "kouril-2020-hyperlabels", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "kroesl_x_card_2017", "Lackner_2022", "Langer_Edith_IR1", "lawonn-2018-illvisstar", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "LeMuzic_2016_PhD", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "Leutschacher_2022", "ludwig-2012-MT", "Manczarski-2016", "Matusich-2017-01", "Mautner 2020", "Mayr-2017-1", "Melo_2018_11", "Meusburger_2020", "Miao_2019", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao2018Dimsum", "Michl_2017_CSV", "mindek-2015-mc", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-2019-mci", "mindek-xmas-card-2016", "Moellinger_Christian_IDE2", "Niedermayer_2018", "Ortner_PhD", "Ortner2020", "pahr-2021-vologram", "Panayotov", "patel_daniel_2007_IRSD", "Pauschenwein_2022", "Peter_2012_AIV", "plank-2017-sldg", "prost-2016-molecule", "purgathofer-2008-cgi", "Radwan-2017-Occ", "Rautek-2007-SLI", "Rautek-2008-IDS", "Rautek-2008-VF", "Reichinger_2016", "Reichinger_Fuhrmann_2016", "Reisacher_Matthias_CPW", "Reisacher2016", "Riegelnegg_2019", "rippl-2023-atg", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "schindler_2020vis", "schmidlehner2021", "scholz_2021", "Schrempf_2020", "schultes_lampi", "seyfert-2017", "sikachev-2010-ill_vis_vol_ren", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "Spechtenhauser_Florian_2016", "stappen_2017_animatedcomic", "Stoll2020", "sturl_2016_dynlabels", "Swoboda2020", "szabo_patrik-2022-tour", "takahashi-2019-acdt", "Thomas-2018", "TR-186-2-07-08", "Troidl_2021", "Troidl_2022", "tut-eg-2006", "tut-siggraph-2006", "tut-vis-2006", "tut-vis-2007", "Unger2020", "Vasileva_2022", "Viola_Ivan_2013_SVA", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "viola-evr", "Viola-Pondering-2017", "Viola-vistutillustrativevis", "Waldin_Nicholas_2016_Colormaps", "waldin-2019-ccm", "Waldner_2017_11", "Wihann_2017", "Woschizka_2021", "wu-2019-bmc", "wu-2019-report", "Zaufel_2021", "zechmeister2020", "Zeng_2021", "Zusag-2017-Bach" ], "projects": [ "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=IllVis", "__class": "ResearchArea" }, { "id": "Modeling", "drupal_id": 4130, "name": "Modeling", "short_abstract": "In this area, we focus on researching methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.", "abstract": "One of the major bottlenecks in the field of computer graphics is the one of content creation, particularly the creation of high-quality 3D geometric models. These models are a demand in many industries, such as entertainment, computer-aided design, urban planning, the fabrication of physical objects, as well as research areas like medical or scientific visualizations and simulations.\n\nWhile rendering - the classical field of computer graphics - has reached very high standards in the recent two decades, the issue of the creation of appropriate digital models is a difficult problem that hardly keeps pace with current demands. Indeed, it is a complex creative process that involves both artistic and technical skills.\n\nTo make this process easier, our goal in this research area is to find new methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.", "website": "https://www.cg.tuwien.ac.at/research/area/Modeling", "teaser": { "name": "teaser.jpg", "path": "research_area:Modeling", "type": "image/jpeg", "size": 190581, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Modeling/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "AA2020", "Adorjan-2015", "aichner-2016-sadf", "arikan-2013-osn", "birsak-thesis", "Birsak2018-SA", "Brandstaetter2020", "brunner_lukas_2022_ssb", "Caic2021", "clemenz_2019_rosy_fields", "DOG10", "dusberger-2010-msm", "eibens-2021-tsgpmg", "eibensteiner-2021-pmcg", "eibner-2009-gpc", "Erhardt_2025_Scutes", "erler_2024_ppsurf", 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"keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 647, "preview_image_height": 918, "name": "miao_nantech_2019-.pdf", "type": "application/pdf", "size": 2548866, "path": "Publication:miao_nantech_2019", "preview_name": "miao_nantech_2019-:preview.png", "preview_type": "image/png", "preview_size": 470720, "url": "https://www.cg.tuwien.ac.at/research/publications/2019/miao_nantech_2019/miao_nantech_2019-.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/miao_nantech_2019/miao_nantech_2019-:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "Illustrare", "workgroup_id": "vis", "drupal_id": 4189, "drupal_path": "/research/projects/Illustrare", "name": "ILLUSTRARE: Integrative Visual Abstraction of Molecular Data", "name_de": null, "short_title": "Illustrare", "website": null, "status": "active", "short_abstract": "FWF - I 2953-N31\nIntegrative Visual Abstraction of Molecular Data", "abstract": "In many aspects of our modern lives we face the problem of having to make sense of large amounts of data. This applies to scientists trying to make sense of their experiments and simulations, to bankers and traders trying to understand the dynamics of the financial markets, and to large enterprises which need to understand the principles behind demand and supply—to name just a few examples. The basic problem in all these cases is that people need to identify important and/or unexpected features in large simulated or captured datasets. Visualization is the domain that facilitates this process of sense-making by dramatically simplifying the process of obtaining an understanding of the data—by representing data visually and thus amplifying people’s cognition. This inherent capability of (good) visualization techniques to amplify human cognition, however, is no longer enough to be able to make sense of today’s huge datasets. To be able to see the essential aspects we need dedicated mechanisms that abstract away the (unnecessary) detail to, in turn, allow the user of the visualization to focus on the important elements. The crucial problem in this context is that it is impossible to know what is important and what is not in a general way—importance changes based on the research question, on the application domain, on the data size, on the user, on the specific situation, etc. Visualization technology therefore needs to support dynamic change of visual abstraction of the data to reflect these contextual changes. The fundamental research challenge in visualization for us is to get an understanding of what (visual) abstraction really is, what it means, how it can be controlled, and how it is, can be, and should be used in visualization.\n", "start_date": "2017-01-01", "end_date": "2019-12-31", "leader_id": 171, "logo": { "name": "logo.jpg", "path": "project:Illustrare", "type": "image/jpeg", "size": 95116, "orig_name": "logo.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/Illustrare/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "I 2953-N31", "comment": null } ], "research_areas": [ "BioVis", "IllVis" ], "publications": [ "Halladjian_2020", "kouril-2018-LoL", "lawonn-2018-illvisstar", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "Viola-Pondering-2017" ], "url": "https://www.cg.tuwien.ac.at/research/projects/Illustrare", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/miao_nantech_2019/", "__class": "Publication" }, { "id": "wu-2019-bmc", "type_id": "journalpaper_notalk", "tu_id": 280645, "repositum_id": null, "title": "Metabopolis: Scalable Network Layout for Biological Pathway Diagrams in Urban Map Style", "date": "2019-05-15", "abstract": "Background\nBiological pathways represent chains of molecular interactions in biological systems that jointly form complex dynamic networks. The network structure changes from the significance of biological experiments and layout algorithms often sacrifice low-level details to maintain high-level information, which complicates the entire image to large biochemical systems such as human metabolic pathways.\n\nResults\nOur work is inspired by concepts from urban planning since we create a visual hierarchy of biological pathways, which is analogous to city blocks and grid-like road networks in an urban area. We automatize the manual drawing process of biologists by first partitioning the map domain into multiple sub-blocks, and then building the corresponding pathways by routing edges schematically, to maintain the global and local context simultaneously. Our system incorporates constrained floor-planning and network-flow algorithms to optimize the layout of sub-blocks and to distribute the edge density along the map domain. We have developed the approach in close collaboration with domain experts and present their feedback on the pathway diagrams based on selected use cases.\n\nConclusions\nWe present a new approach for computing biological pathway maps that untangles visual clutter by decomposing large networks into semantic sub-networks and bundling long edges to create space for presenting relationships systematically.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "wu-2019-bmc-image.png", "type": "image/png", "size": 107492, "path": "Publication:wu-2019-bmc", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-bmc/wu-2019-bmc-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-bmc/wu-2019-bmc-image:thumb{{size}}.png" }, 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"Author" } ], "doi": "http://doi.org/10.1186/s12859-019-2779-4", "journal": "BMC Bioinformatics", "number": "187", "pages_from": "1", "pages_to": "20", "volume": "20", "research_areas": [ { "id": "BioVis", "drupal_id": 4127, "name": "Biological Data Visualization", "short_abstract": "In this research area, we develop new visualization techniques to support biologists in data analysis and create visualizations to disseminate scientific discoveries in biology.", "abstract": "In modern biological research domain experts have to deal with complex and large data collections and simulations. Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n", "website": "https://www.cg.tuwien.ac.at/research/area/BioVis", "teaser": { "name": "teaser.png", "path": "research_area:BioVis", "type": "image/png", "size": 16330957, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/BioVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "amirkhanov-2019-manylands", "byska-2019-mdfc", "cellVIEW_2015", "cmolik-2020-tvcg", "Dietrich_1", "dietrich-2016-viseq2", "Ehlers_PhD", "ehlers-2025-ait", "eschner-2023-ims", "eschner-blur-2022", "Escribano_2017", "Furmanova_2018", "Gehrer-2017", "Gehrer-2017-molmach", "glinzner-2016-tex", "Halladjian_2020", "kapferer-2017-godot", "klein_2017_IM", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koch-2018-sso", "Kolesar-Fractional-2016", "kolesar-ivan-2014-polymers", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kozlikova-Visualization-2016b", "Krone2016VABC", "Kugler_2019", "lemuzic_2015_timelapse", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lipp-2017-mgpu", "lipp-2017-vulkan", "Manczarski-2016", "manylands_award", "Miao_2019", "miao_inria_2017", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-xmas-card-2016", "Mitterhofer_2017", "nguyen_2020-covid", "Nowak_2020", "raidou_2019_springer", "raidou_shonan167", "raidou2018visualflatter", "rasch-2016-imgses", "Reisacher2016", "rinortner_susanne-2019-vpicc", "Sarkis_2021", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2013-neuromap", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "stappen_2017_animatedcomic", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "trautner-2018-imd", "unger-2019_vcp", "vad_2015_phd", "vad_viktor-2017-WVE", "vad-2016-bre", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "waldin-2019-ccm", "waldner-2014-af", "Weissenboeck_2019", "wu-2017-dagstuhl", "wu-2018-metabo", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg" ], "projects": [ "BioNetIllustration", "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=BioVis", "__class": "ResearchArea" }, { "id": "IllVis", "drupal_id": 4131, "name": "Illustrative Visualization", "short_abstract": "In this research area, we develop rendering methods that are inspired by scientific illustrations, in order to make complex biological information more intuitive to understand and more pleasant to read.", "abstract": "Scientific illustration is concerned with researching ways in which complex biological and medical data can be abstracted in order to convey a desired information that would otherwise be impossible or hard to retrieve from the original data. Illustrators apply such techniques, for instance, to present non-important parts of an organ in a simplified way, while using detailed representations to put the focus of attention on a region where a tumor might be situated.\n\nTo identify such meaningful visual abstractions for visualization, their effectiveness for human perception and cognition has to be assessed, and they have to be formalized in order to make them applicable in rendering algorithms. In this project, we try to advance the understanding of procedural visual abstraction of complex physiological processes that describe the complex machinery of biological life.", "website": "https://www.cg.tuwien.ac.at/research/area/IllVis", "teaser": { "name": "teaser.jpg", "path": "research_area:IllVis", "type": "image/jpeg", "size": 34861, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/IllVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "antes-2026-maa", "Antonini2020", "Balabanian-2010-IIV", "Balduz_01", "Bayat_2019", "Bechtold2020", "Birkeland-2012-IMC", "brandstaetter_01", "bruckner-2005-ICV", "bruckner-2006-ICE", "bruckner-2007-STF", "bruckner-2008-IIV", "bruckner-2010-HVC", "bruckner-2010-IFC", "cellVIEW_2015", "Chen-Information-2016", "Deutsch-2018", "Dhanoa_2021", "Dhanoa2024", "dietrich-2016-viseq2", "donabauer_2019_1", "eg-tut2005-iv", "eschner-2023-ims", "Essler2022", "gangl-2018-gpsart", "Gehrer_Daniel_CUI", "Gehrer-2017-molmach", "gerl-2006-vhi", "Gogel2020", "Groeller_2011_IPV", "Groeller_2016_I3", "Groeller_2016_I6", "Groeller_2016_I7", "Groeller_2016_I8", "Groeller_V1_2020", "groeller-2006-ivt", "groeller-2007-fci", "groeller-2008-irs", "Groeller-2010-IFI", "gruber-2025-vps", "Halladjian_2020", "haushofer-2018-skinning", "Heim_2020", "horvath-2018-ism", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "Knapp_2017_CVR", "Koeppel2020", "kolesar-ivan-2014-polymers", "Konev-FCV2018", "Koszticsak-2017-ewt", "Kouril_2017_11", "kouril-2020-hyperlabels", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "kroesl_x_card_2017", "Lackner_2022", "Langer_Edith_IR1", "lawonn-2018-illvisstar", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "LeMuzic_2016_PhD", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "Leutschacher_2022", "ludwig-2012-MT", "Manczarski-2016", "Matusich-2017-01", "Mautner 2020", "Mayr-2017-1", "Melo_2018_11", "Meusburger_2020", "Miao_2019", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao2018Dimsum", "Michl_2017_CSV", "mindek-2015-mc", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-2019-mci", "mindek-xmas-card-2016", "Moellinger_Christian_IDE2", "Niedermayer_2018", "Ortner_PhD", "Ortner2020", "pahr-2021-vologram", "Panayotov", "patel_daniel_2007_IRSD", "Pauschenwein_2022", "Peter_2012_AIV", "plank-2017-sldg", "prost-2016-molecule", "purgathofer-2008-cgi", "Radwan-2017-Occ", "Rautek-2007-SLI", "Rautek-2008-IDS", "Rautek-2008-VF", "Reichinger_2016", "Reichinger_Fuhrmann_2016", "Reisacher_Matthias_CPW", "Reisacher2016", "Riegelnegg_2019", "rippl-2023-atg", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "schindler_2020vis", "schmidlehner2021", "scholz_2021", "Schrempf_2020", "schultes_lampi", "seyfert-2017", "sikachev-2010-ill_vis_vol_ren", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "Spechtenhauser_Florian_2016", "stappen_2017_animatedcomic", "Stoll2020", "sturl_2016_dynlabels", "Swoboda2020", "szabo_patrik-2022-tour", "takahashi-2019-acdt", "Thomas-2018", "TR-186-2-07-08", "Troidl_2021", "Troidl_2022", "tut-eg-2006", "tut-siggraph-2006", "tut-vis-2006", "tut-vis-2007", "Unger2020", "Vasileva_2022", "Viola_Ivan_2013_SVA", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "viola-evr", "Viola-Pondering-2017", "Viola-vistutillustrativevis", "Waldin_Nicholas_2016_Colormaps", "waldin-2019-ccm", "Waldner_2017_11", "Wihann_2017", "Woschizka_2021", "wu-2019-bmc", "wu-2019-report", "Zaufel_2021", "zechmeister2020", "Zeng_2021", "Zusag-2017-Bach" ], "projects": [ "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=IllVis", "__class": "ResearchArea" }, { "id": "InfoVis", "drupal_id": 4128, "name": "Information Visualization and Visual Analytics", "short_abstract": "In this research area, our focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning. ", "abstract": "

Data and information created by various processes (e.g., simulations) is getting larger, and more and more complex. We use interactive visualization and analysis techniques to facilitate exploration of complex parameter spaces (e.g., to analyze and compare parameters for automotive engineering, reconstruction algorithms, or geometry generators) or unstructured information collections (e.g., annotated digital documents or image collections). Our research focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning.

\r\n", "website": "https://www.cg.tuwien.ac.at/research/area/InfoVis", "teaser": { "name": "teaser.png", "path": "research_area:InfoVis", "type": "image/png", "size": 60875, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/InfoVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "8564188", "arbesser_ba_2023", "Arleo-2019-vis", "Batik-2021", "batik-2021-gd", "bayat-2022-mva", "beham-2014-cupid", "bhore-2021-issac", "birsak-2014-agtb", "birsak-2017-dpe", "borgo-2013-gly", "borondy2022", "Braunsperger-2025_bsc", "Bruckner_Stefan_2015_VAS", "bugnar-esk-2021", "byska-2019-mdfc", "Cai_2018", "casellato-2016-pkg", "Chen-Information-2016", "cizmic-2018-evd", "cmolik-2020-tvcg", "Cornel_2020", "daae-lampe-2010-dif", "Deutsch-2018", "Diehl_2015", "Diehl_2021", "dworschak-2016-szcm", "Eckelt_2018_01", "edlinger-2018-vwr", "ehlers-2024-vgs", "eichner-2024-erv", "eitler-2024-sos", "eiweck-hnv-2021", "ellhotka-2025-ipo", "eschner-2023-evl", "eschner-2025-ide", "Escribano_2017", "fourousan2021", "furmanova_2020", "Gadllah_Hani_2016", "Gall2020", "Ganuza_ML_2015_ISA", "georgiev-2019-cbg", "geyer_lukas_2015_prj", "geymayer-2017-std", "Groeller_2011_CW", "Groeller_2011_NR", "Groeller_2014_RWA", "Groeller_2016_P1", "Groeller_2016_P2", "Groeller_2016_P4", "Groeller_2016_P6", "Groeller_2021-10", "Groeller_V2_2020", "Groeller_V3_2020", "Groeller_V5_2020", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", "gundacker-2020-wlm", "gusenbauer-2018", "gusenbauer-2018-P", "Heim_2021", "heim-2024-accustripes", "heim-gall-2020-dde", "Heinzl2021", "holzer-edo", "hromniak-2019-vcn", "huber-2025-eed", "Iijima-2020-iV", "indirectBiasLanguageModels-2023", "irendorfer-2024-uat", "karnik-09-shapegrammar", "Kehrer-2010-mom", "kehrer-2012-mod", "kehrer-2013-SBC", "Kehrer-2013-STAR", "klaffenboeck-2024-rva", "klaffenboeck-thesis", "Klein_Tobias_2015TIV", "klein-2016-WCL", "knoetzl_alexander-2025-prj", "koeppel-2021", "Kolter_2021", "komon-2025-webigeo", "komon-kimmersdorfer-2025-weBIGeo", "Konyha_2013_IVA", "korpitsch-2021-lov", "Kuroko-2020-iV", "Laschober-2018", "li-2019-gdc", "lippeck-2022-mna", "louis-alexandre_dit_petit-frere-2022-veo", "magg2022", "mahler-2021-mdar", "martorell2022", "maruyama-2019-iv", "Matkovic_Kresimir_2015_", "Matkovic-2014-ieee", "matt-2024-cvil", "matt-2025-scv", "mayr-2021-wec", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "medeiros-2023-gwf", "meka-2024-lpi", "melcher-2024-asi", "Miao_2015_VCBM", "miao_2016_cgf", "Miao_Haichao_2015_VQC", "miao2018Dimsum", "mizuno-2019-eurovis", "Muehlbacher_diss_2018", "musleh_maath_2021_mam", "musleh_maath-2021-mam1", "musleh_maath-2021-mam2", "Musleh_PhD", "musleh-2022-mam5", "musleh-2025-trustme", "Neubauer2020", "Nowak_2021", "ortner-2016-tunnel", "ortner-2016-visaware", "pahr-2024-ieo", "PH-2011-LDS", "Pilizar_-2020-bachelor", "pirch_2021_VRN", "pointner_simon-2020", "polatsek-2018-stv", "Presch_2020", "Priselac2021", "Purchase-2020-gd", "Purgathofer-2017-China1", "Purgathofer-2017-China2", "Purgathofer-2017-VC-Interface", "raidou_2019_pelvisrunner", "raidou_2019_preha", "raidou_2019_springer", "raidou_bestphd", "raidou_EuroVis15", "raidou_eurovis16", "raidou_miccai16", "raidou_pingu2020", "raidou_previs2021", "raidou_vcbm14", "raidou_vis14", "raidou_vis15", "raidou_visgap2020", "raidou2019_prsps", "Ribicic_2012_VAS", "Rippberger_2019", "rozana-2026-vcfd", "sakr_sherif-2020-cacm", "samoul-2019-cnp", "sbardellati-2021-eveos", "schmidt-phd", "sietzen-2019-wnn", "sietzen-2021-perturber", "sietzen-2022-vacnnr", "sietzen-ifv-2019", "sikachev_peter-2011-protovis", "smiech-2018-tei", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger-2013-neuromap", "sorger-2015-litevis", "sorger-2015-taxintec", "sorger-2017-thesis", "sorger-2019-odn", "sorger-2021-egonet", "spegel-gruenberger-2020", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "STEINLECHNER-2019-ICT", "steinschorn-2025-parameter", "stoff-2025-pvu", "stoff-concepMap-2021", "stritzel2022", "Strohmayer-2018-BT", "takahashi-2019-acdt", "tekaya-2025-amo", "Thomas-2018", "TR1862162", "Troidl_2019", "turner-aso", "unger-2019_vcp", "vad_viktor-2017-WVE", "vaico", "Vasileva-2018", "vasileva-2019-smw", "Wagner_032017", "wagner-2024-par", "walchhofer_ar_flowmaps", "waldin-2019-ccm", "waldner-2013-facetCloudsGI", "waldner-2013-ubiWM", "waldner-2014-ghi", "waldner-2017-vph", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "waser_2011_VSD", "webGPU_aggregateVis-2023", "wolf-2023-cc", "wolf-2024-jhd", "wu-2017-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-shonan", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-smwp", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-eurovis-star", "wu-2020-tvcg", "ymca", "YOGHOURDJIAN2019" ], "projects": [ "BioNetIllustration", "d10206", "d10413", "d10450", "d9282", "d9522", "d9555", "deskollage", "Scenario Pool" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=InfoVis", "__class": "ResearchArea" } ], "keywords": [ "Biological pathways", "Graph drawing", "Mapmetaphor", "Orthogonallayout", "Floorplanning", "Edgerouting" ], "weblinks": [ { "href": "https://www.youtube.com/watch?v=AhWCIGTxqAg", "caption": "video", "description": null, "main_file": 1 } ], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "wu-2019-bmc-image.png", "type": "image/png", "size": 107492, "path": "Publication:wu-2019-bmc", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-bmc/wu-2019-bmc-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-bmc/wu-2019-bmc-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "wu-2019-bmc-paper.pdf", "type": "application/pdf", "size": 8528804, "path": "Publication:wu-2019-bmc", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-bmc/wu-2019-bmc-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-bmc/wu-2019-bmc-paper:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "BioNetIllustration", "workgroup_id": "vis", "drupal_id": 4196, "drupal_path": "/research/projects/BioNetIllustration", "name": "BioNetIllustration: User Centric Illustrations of Biological Networks", "name_de": null, "short_title": "BioNetIllustration", "website": null, "status": "active", "short_abstract": "

In living systems, one molecule is commonly involved in several distinct physiological functions. The roles of molecules are commonly summarized in pathway diagrams, which, however, are abstract, hierarchically nested and thus is difficult to comprehend especially by non-expert audience. The primary goal of this research in visualization is to intuitively support the comprehensive understanding of relationships among biological networks using interactively computed illustrations. Illustrations, especially in textbooks of biology are carefully designed to clearly present reactions between organs as well as interactions within cells. Automatic generation of illustrative visualizations of biological networks is thus the technical content of this proposal. Automatic generation of hand-drawn illustrations has been a challenging task due to the difficulty of algorithmically describing a human creative process such as evaluating and selecting significant information and composing meaningful explanations in a visually plausible manner. The project also involves experts from several disciplines including network and medical visualization, data mining, systems biology as well as perceptual psychology. The result will provide a new direction for physiological process analysis and accelerate the knowledge transfer not only within experts but also to the public. Acknowledgment: The project has received funding from the European Union Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 747985.

\r\n", "abstract": "

In living systems, one molecule is commonly involved in several distinct physiological functions. The roles of molecules are commonly summarized in pathway diagrams, which, however, are abstract, hierarchically nested and thus is difficult to comprehend especially by non-expert audience. The primary goal of this research in visualization is to intuitively support the comprehensive understanding of relationships among biological networks using interactively computed illustrations. Illustrations, especially in textbooks of biology are carefully designed to clearly present reactions between organs as well as interactions within cells. Automatic generation of illustrative visualizations of biological networks is thus the technical content of this proposal. Automatic generation of hand-drawn illustrations has been a challenging task due to the difficulty of algorithmically describing a human creative process such as evaluating and selecting significant information and composing meaningful explanations in a visually plausible manner. The project also involves experts from several disciplines including network and medical visualization, data mining, systems biology as well as perceptual psychology. The result will provide a new direction for physiological process analysis and accelerate the knowledge transfer not only within experts but also to the public. Acknowledgment: The project has received funding from the European Union Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 747985.

\r\n", "start_date": "2017-06-21", "end_date": "2019-06-20", "leader_id": 1464, "logo": { "name": "logo.png", "path": "project:BioNetIllustration", "type": "image/png", "size": 16337, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/BioNetIllustration/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "Horizon 2020", "contract_number": "747985", "comment": null } ], "research_areas": [ "BioVis", "InfoVis" ], "publications": [ "cmolik-2020-tvcg", "kouril-2018-LoL", "mizuno-2019-eurovis", "Purchase-2020-gd", "rinortner_susanne-2019-vpicc", "Sbardellati-2019-vcbm", "wu-2017-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-shonan", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg", "YOGHOURDJIAN2019" ], "url": "https://www.cg.tuwien.ac.at/research/projects/BioNetIllustration", "__class": "Project" }, { "id": "illvisation", "workgroup_id": "vis", "drupal_id": 4171, "drupal_path": "/research/projects/illvisation", "name": "Visual Computing: Illustrative Visualization", "name_de": null, "short_title": "illvisation", "website": null, "status": "active", "short_abstract": "

The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/

\r\n\r\n

Prototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/

\r\n\r\n

cellVIEW

\r\n\r\n

cellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.

\r\n\r\n

Invited Talks

\r\n\r\n

18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness

\r\n", "abstract": "

The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/

\r\n\r\n

Prototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/

\r\n\r\n

cellVIEW

\r\n\r\n

cellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.

\r\n\r\n

Invited Talks

\r\n\r\n

18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness

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}, { "publ_id": "vis-foa", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldin-2017-thesis", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Wihann_2017", "field_id": "supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=171", "__class": "Author" } ], "number": "TR-193-02-2019-1", "open_access": "no", "research_areas": [ { "id": "BioVis", "drupal_id": 4127, "name": "Biological Data Visualization", "short_abstract": "In this research area, we develop new visualization techniques to support biologists in data analysis and create visualizations to disseminate scientific discoveries in biology.", "abstract": "In modern biological research domain experts have to deal with complex and large data collections and simulations. Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n", "website": "https://www.cg.tuwien.ac.at/research/area/BioVis", "teaser": { "name": "teaser.png", "path": "research_area:BioVis", "type": "image/png", "size": 16330957, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/BioVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "amirkhanov-2019-manylands", "byska-2019-mdfc", "cellVIEW_2015", "cmolik-2020-tvcg", "Dietrich_1", "dietrich-2016-viseq2", "Ehlers_PhD", "ehlers-2025-ait", "eschner-2023-ims", "eschner-blur-2022", "Escribano_2017", "Furmanova_2018", "Gehrer-2017", "Gehrer-2017-molmach", "glinzner-2016-tex", "Halladjian_2020", "kapferer-2017-godot", "klein_2017_IM", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koch-2018-sso", "Kolesar-Fractional-2016", "kolesar-ivan-2014-polymers", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kozlikova-Visualization-2016b", "Krone2016VABC", "Kugler_2019", "lemuzic_2015_timelapse", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lipp-2017-mgpu", "lipp-2017-vulkan", "Manczarski-2016", "manylands_award", "Miao_2019", "miao_inria_2017", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-xmas-card-2016", "Mitterhofer_2017", "nguyen_2020-covid", "Nowak_2020", "raidou_2019_springer", "raidou_shonan167", "raidou2018visualflatter", "rasch-2016-imgses", "Reisacher2016", "rinortner_susanne-2019-vpicc", "Sarkis_2021", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2013-neuromap", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "stappen_2017_animatedcomic", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "trautner-2018-imd", "unger-2019_vcp", "vad_2015_phd", "vad_viktor-2017-WVE", "vad-2016-bre", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "waldin-2019-ccm", "waldner-2014-af", "Weissenboeck_2019", "wu-2017-dagstuhl", "wu-2018-metabo", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg" ], "projects": [ "BioNetIllustration", "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=BioVis", "__class": "ResearchArea" }, { "id": "IllVis", "drupal_id": 4131, "name": "Illustrative Visualization", "short_abstract": "In this research area, we develop rendering methods that are inspired by scientific illustrations, in order to make complex biological information more intuitive to understand and more pleasant to read.", "abstract": "Scientific illustration is concerned with researching ways in which complex biological and medical data can be abstracted in order to convey a desired information that would otherwise be impossible or hard to retrieve from the original data. Illustrators apply such techniques, for instance, to present non-important parts of an organ in a simplified way, while using detailed representations to put the focus of attention on a region where a tumor might be situated.\n\nTo identify such meaningful visual abstractions for visualization, their effectiveness for human perception and cognition has to be assessed, and they have to be formalized in order to make them applicable in rendering algorithms. In this project, we try to advance the understanding of procedural visual abstraction of complex physiological processes that describe the complex machinery of biological life.", "website": "https://www.cg.tuwien.ac.at/research/area/IllVis", "teaser": { "name": "teaser.jpg", "path": "research_area:IllVis", "type": "image/jpeg", "size": 34861, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/IllVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "antes-2026-maa", "Antonini2020", "Balabanian-2010-IIV", "Balduz_01", "Bayat_2019", "Bechtold2020", "Birkeland-2012-IMC", "brandstaetter_01", "bruckner-2005-ICV", "bruckner-2006-ICE", "bruckner-2007-STF", "bruckner-2008-IIV", "bruckner-2010-HVC", "bruckner-2010-IFC", "cellVIEW_2015", "Chen-Information-2016", "Deutsch-2018", "Dhanoa_2021", "Dhanoa2024", "dietrich-2016-viseq2", "donabauer_2019_1", "eg-tut2005-iv", "eschner-2023-ims", "Essler2022", "gangl-2018-gpsart", "Gehrer_Daniel_CUI", "Gehrer-2017-molmach", "gerl-2006-vhi", "Gogel2020", "Groeller_2011_IPV", "Groeller_2016_I3", "Groeller_2016_I6", "Groeller_2016_I7", "Groeller_2016_I8", "Groeller_V1_2020", "groeller-2006-ivt", "groeller-2007-fci", "groeller-2008-irs", "Groeller-2010-IFI", "gruber-2025-vps", "Halladjian_2020", "haushofer-2018-skinning", "Heim_2020", "horvath-2018-ism", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "Knapp_2017_CVR", "Koeppel2020", "kolesar-ivan-2014-polymers", "Konev-FCV2018", "Koszticsak-2017-ewt", "Kouril_2017_11", "kouril-2020-hyperlabels", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "kroesl_x_card_2017", "Lackner_2022", "Langer_Edith_IR1", "lawonn-2018-illvisstar", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "LeMuzic_2016_PhD", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "Leutschacher_2022", "ludwig-2012-MT", "Manczarski-2016", "Matusich-2017-01", "Mautner 2020", "Mayr-2017-1", "Melo_2018_11", "Meusburger_2020", "Miao_2019", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao2018Dimsum", "Michl_2017_CSV", "mindek-2015-mc", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-2019-mci", "mindek-xmas-card-2016", "Moellinger_Christian_IDE2", "Niedermayer_2018", "Ortner_PhD", "Ortner2020", "pahr-2021-vologram", "Panayotov", "patel_daniel_2007_IRSD", "Pauschenwein_2022", "Peter_2012_AIV", "plank-2017-sldg", "prost-2016-molecule", "purgathofer-2008-cgi", "Radwan-2017-Occ", "Rautek-2007-SLI", "Rautek-2008-IDS", "Rautek-2008-VF", "Reichinger_2016", "Reichinger_Fuhrmann_2016", "Reisacher_Matthias_CPW", "Reisacher2016", "Riegelnegg_2019", "rippl-2023-atg", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "schindler_2020vis", "schmidlehner2021", "scholz_2021", "Schrempf_2020", "schultes_lampi", "seyfert-2017", "sikachev-2010-ill_vis_vol_ren", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "Spechtenhauser_Florian_2016", "stappen_2017_animatedcomic", "Stoll2020", "sturl_2016_dynlabels", "Swoboda2020", "szabo_patrik-2022-tour", "takahashi-2019-acdt", "Thomas-2018", "TR-186-2-07-08", "Troidl_2021", "Troidl_2022", "tut-eg-2006", "tut-siggraph-2006", "tut-vis-2006", "tut-vis-2007", "Unger2020", "Vasileva_2022", "Viola_Ivan_2013_SVA", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "viola-evr", "Viola-Pondering-2017", "Viola-vistutillustrativevis", "Waldin_Nicholas_2016_Colormaps", "waldin-2019-ccm", "Waldner_2017_11", "Wihann_2017", "Woschizka_2021", "wu-2019-bmc", "wu-2019-report", "Zaufel_2021", "zechmeister2020", "Zeng_2021", "Zusag-2017-Bach" ], "projects": [ "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=IllVis", "__class": "ResearchArea" }, { "id": "InfoVis", "drupal_id": 4128, "name": "Information Visualization and Visual Analytics", "short_abstract": "In this research area, our focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning. ", "abstract": "

Data and information created by various processes (e.g., simulations) is getting larger, and more and more complex. We use interactive visualization and analysis techniques to facilitate exploration of complex parameter spaces (e.g., to analyze and compare parameters for automotive engineering, reconstruction algorithms, or geometry generators) or unstructured information collections (e.g., annotated digital documents or image collections). Our research focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning.

\r\n", "website": "https://www.cg.tuwien.ac.at/research/area/InfoVis", "teaser": { "name": "teaser.png", "path": "research_area:InfoVis", "type": "image/png", "size": 60875, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/InfoVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "8564188", "arbesser_ba_2023", "Arleo-2019-vis", "Batik-2021", "batik-2021-gd", "bayat-2022-mva", "beham-2014-cupid", "bhore-2021-issac", "birsak-2014-agtb", "birsak-2017-dpe", "borgo-2013-gly", "borondy2022", "Braunsperger-2025_bsc", "Bruckner_Stefan_2015_VAS", "bugnar-esk-2021", "byska-2019-mdfc", "Cai_2018", "casellato-2016-pkg", "Chen-Information-2016", "cizmic-2018-evd", "cmolik-2020-tvcg", "Cornel_2020", "daae-lampe-2010-dif", "Deutsch-2018", "Diehl_2015", "Diehl_2021", "dworschak-2016-szcm", "Eckelt_2018_01", "edlinger-2018-vwr", "ehlers-2024-vgs", "eichner-2024-erv", "eitler-2024-sos", "eiweck-hnv-2021", "ellhotka-2025-ipo", "eschner-2023-evl", "eschner-2025-ide", "Escribano_2017", "fourousan2021", "furmanova_2020", "Gadllah_Hani_2016", "Gall2020", "Ganuza_ML_2015_ISA", "georgiev-2019-cbg", "geyer_lukas_2015_prj", "geymayer-2017-std", "Groeller_2011_CW", "Groeller_2011_NR", "Groeller_2014_RWA", "Groeller_2016_P1", "Groeller_2016_P2", "Groeller_2016_P4", "Groeller_2016_P6", "Groeller_2021-10", "Groeller_V2_2020", "Groeller_V3_2020", "Groeller_V5_2020", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", "gundacker-2020-wlm", "gusenbauer-2018", "gusenbauer-2018-P", "Heim_2021", "heim-2024-accustripes", "heim-gall-2020-dde", "Heinzl2021", "holzer-edo", "hromniak-2019-vcn", "huber-2025-eed", "Iijima-2020-iV", "indirectBiasLanguageModels-2023", "irendorfer-2024-uat", "karnik-09-shapegrammar", "Kehrer-2010-mom", "kehrer-2012-mod", "kehrer-2013-SBC", "Kehrer-2013-STAR", "klaffenboeck-2024-rva", "klaffenboeck-thesis", "Klein_Tobias_2015TIV", "klein-2016-WCL", "knoetzl_alexander-2025-prj", "koeppel-2021", "Kolter_2021", "komon-2025-webigeo", "komon-kimmersdorfer-2025-weBIGeo", "Konyha_2013_IVA", "korpitsch-2021-lov", "Kuroko-2020-iV", "Laschober-2018", "li-2019-gdc", "lippeck-2022-mna", "louis-alexandre_dit_petit-frere-2022-veo", "magg2022", "mahler-2021-mdar", "martorell2022", "maruyama-2019-iv", "Matkovic_Kresimir_2015_", "Matkovic-2014-ieee", "matt-2024-cvil", "matt-2025-scv", "mayr-2021-wec", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "medeiros-2023-gwf", "meka-2024-lpi", "melcher-2024-asi", "Miao_2015_VCBM", "miao_2016_cgf", "Miao_Haichao_2015_VQC", "miao2018Dimsum", "mizuno-2019-eurovis", "Muehlbacher_diss_2018", "musleh_maath_2021_mam", "musleh_maath-2021-mam1", "musleh_maath-2021-mam2", "Musleh_PhD", "musleh-2022-mam5", "musleh-2025-trustme", "Neubauer2020", "Nowak_2021", "ortner-2016-tunnel", "ortner-2016-visaware", "pahr-2024-ieo", "PH-2011-LDS", "Pilizar_-2020-bachelor", "pirch_2021_VRN", 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"steinboeck-2018-lbg", "STEINLECHNER-2019-ICT", "steinschorn-2025-parameter", "stoff-2025-pvu", "stoff-concepMap-2021", "stritzel2022", "Strohmayer-2018-BT", "takahashi-2019-acdt", "tekaya-2025-amo", "Thomas-2018", "TR1862162", "Troidl_2019", "turner-aso", "unger-2019_vcp", "vad_viktor-2017-WVE", "vaico", "Vasileva-2018", "vasileva-2019-smw", "Wagner_032017", "wagner-2024-par", "walchhofer_ar_flowmaps", "waldin-2019-ccm", "waldner-2013-facetCloudsGI", "waldner-2013-ubiWM", "waldner-2014-ghi", "waldner-2017-vph", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "waser_2011_VSD", "webGPU_aggregateVis-2023", "wolf-2023-cc", "wolf-2024-jhd", "wu-2017-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-shonan", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-smwp", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-eurovis-star", "wu-2020-tvcg", "ymca", "YOGHOURDJIAN2019" ], "projects": [ "BioNetIllustration", "d10206", "d10413", "d10450", "d9282", "d9522", "d9555", "deskollage", "Scenario Pool" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=InfoVis", "__class": "ResearchArea" } ], "keywords": [], "weblinks": [ { "href": "https://dl.ccf.org.cn/institude/institudeDetail?id=4320599515842560&_ack=1", "caption": null, "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "wu-2019-report-paper.pdf", "type": "application/pdf", "size": 8399742, "path": "Publication:wu-2019-report", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-report/wu-2019-report-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-report/wu-2019-report-paper:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "BioNetIllustration", "workgroup_id": "vis", "drupal_id": 4196, "drupal_path": "/research/projects/BioNetIllustration", "name": "BioNetIllustration: User Centric Illustrations of Biological Networks", "name_de": null, "short_title": "BioNetIllustration", "website": null, "status": "active", "short_abstract": "

In living systems, one molecule is commonly involved in several distinct physiological functions. The roles of molecules are commonly summarized in pathway diagrams, which, however, are abstract, hierarchically nested and thus is difficult to comprehend especially by non-expert audience. The primary goal of this research in visualization is to intuitively support the comprehensive understanding of relationships among biological networks using interactively computed illustrations. Illustrations, especially in textbooks of biology are carefully designed to clearly present reactions between organs as well as interactions within cells. Automatic generation of illustrative visualizations of biological networks is thus the technical content of this proposal. Automatic generation of hand-drawn illustrations has been a challenging task due to the difficulty of algorithmically describing a human creative process such as evaluating and selecting significant information and composing meaningful explanations in a visually plausible manner. The project also involves experts from several disciplines including network and medical visualization, data mining, systems biology as well as perceptual psychology. The result will provide a new direction for physiological process analysis and accelerate the knowledge transfer not only within experts but also to the public. Acknowledgment: The project has received funding from the European Union Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 747985.

\r\n", "abstract": "

In living systems, one molecule is commonly involved in several distinct physiological functions. The roles of molecules are commonly summarized in pathway diagrams, which, however, are abstract, hierarchically nested and thus is difficult to comprehend especially by non-expert audience. The primary goal of this research in visualization is to intuitively support the comprehensive understanding of relationships among biological networks using interactively computed illustrations. Illustrations, especially in textbooks of biology are carefully designed to clearly present reactions between organs as well as interactions within cells. Automatic generation of illustrative visualizations of biological networks is thus the technical content of this proposal. Automatic generation of hand-drawn illustrations has been a challenging task due to the difficulty of algorithmically describing a human creative process such as evaluating and selecting significant information and composing meaningful explanations in a visually plausible manner. The project also involves experts from several disciplines including network and medical visualization, data mining, systems biology as well as perceptual psychology. The result will provide a new direction for physiological process analysis and accelerate the knowledge transfer not only within experts but also to the public. Acknowledgment: The project has received funding from the European Union Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 747985.

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For example, in geographic visualization, there are continents, which can be subdivided into countries, states, counties and cities. Similarly, in models of viruses or bacteria at the highest level are the compartments, and below that are macromolecules, secondary structures (such as α‐helices), amino‐acids, and on the finest level atoms. Distinguishing between items can be assisted through the use of color at all levels. However, currently, there are no hierarchical and adaptive color mapping techniques for very large multi‐scale visualizations that can be explored interactively. We present a novel, multi‐scale, color‐mapping technique for adaptively adjusting the color scheme to the current view and scale. Color is treated as a resource and is smoothly redistributed. The distribution adjusts to the scale of the currently observed detail and maximizes the color range utilization given current viewing requirements. Thus, we ensure that the user is able to distinguish items on any level, even if the color is not constant for a particular feature. The coloring technique is demonstrated for a political map and a mesoscale structural model of HIV. The technique has been tested by users with expertise in structural biology and was overall well received.", "authors_et_al": false, "substitute": null, "main_image": { "description": "Multiple color zoom levels. 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"publ_id": "Viola-05-Smart", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "viola-2007-ort", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Viola-Pondering-2017", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "vis-foa", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldin-2017-thesis", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Wihann_2017", "field_id": "supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=171", "__class": "Author" } ], "doi": "10.1111/cgf.13611", "journal": "Computer Graphics Forum", "number": "6", "pages_from": "150", "pages_to": "164", "volume": "38", "research_areas": [ { "id": "BioVis", "drupal_id": 4127, "name": "Biological Data Visualization", "short_abstract": "In this research area, we develop new visualization techniques to support biologists in data analysis and create visualizations to disseminate scientific discoveries in biology.", "abstract": "In modern biological research domain experts have to deal with complex and large data collections and simulations. Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n", "website": "https://www.cg.tuwien.ac.at/research/area/BioVis", "teaser": { "name": "teaser.png", "path": "research_area:BioVis", "type": "image/png", "size": 16330957, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/BioVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "amirkhanov-2019-manylands", "byska-2019-mdfc", "cellVIEW_2015", "cmolik-2020-tvcg", "Dietrich_1", "dietrich-2016-viseq2", "Ehlers_PhD", "ehlers-2025-ait", "eschner-2023-ims", "eschner-blur-2022", "Escribano_2017", "Furmanova_2018", "Gehrer-2017", "Gehrer-2017-molmach", "glinzner-2016-tex", "Halladjian_2020", "kapferer-2017-godot", "klein_2017_IM", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koch-2018-sso", "Kolesar-Fractional-2016", "kolesar-ivan-2014-polymers", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kozlikova-Visualization-2016b", "Krone2016VABC", "Kugler_2019", "lemuzic_2015_timelapse", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lipp-2017-mgpu", "lipp-2017-vulkan", "Manczarski-2016", "manylands_award", "Miao_2019", "miao_inria_2017", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-xmas-card-2016", "Mitterhofer_2017", "nguyen_2020-covid", "Nowak_2020", "raidou_2019_springer", "raidou_shonan167", "raidou2018visualflatter", "rasch-2016-imgses", "Reisacher2016", "rinortner_susanne-2019-vpicc", "Sarkis_2021", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2013-neuromap", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "stappen_2017_animatedcomic", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "trautner-2018-imd", "unger-2019_vcp", "vad_2015_phd", "vad_viktor-2017-WVE", "vad-2016-bre", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "waldin-2019-ccm", "waldner-2014-af", "Weissenboeck_2019", "wu-2017-dagstuhl", "wu-2018-metabo", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg" ], "projects": [ "BioNetIllustration", "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=BioVis", "__class": "ResearchArea" }, { "id": "IllVis", "drupal_id": 4131, "name": "Illustrative Visualization", "short_abstract": "In this research area, we develop rendering methods that are inspired by scientific illustrations, in order to make complex biological information more intuitive to understand and more pleasant to read.", "abstract": "Scientific illustration is concerned with researching ways in which complex biological and medical data can be abstracted in order to convey a desired information that would otherwise be impossible or hard to retrieve from the original data. Illustrators apply such techniques, for instance, to present non-important parts of an organ in a simplified way, while using detailed representations to put the focus of attention on a region where a tumor might be situated.\n\nTo identify such meaningful visual abstractions for visualization, their effectiveness for human perception and cognition has to be assessed, and they have to be formalized in order to make them applicable in rendering algorithms. In this project, we try to advance the understanding of procedural visual abstraction of complex physiological processes that describe the complex machinery of biological life.", "website": "https://www.cg.tuwien.ac.at/research/area/IllVis", "teaser": { "name": "teaser.jpg", "path": "research_area:IllVis", "type": "image/jpeg", "size": 34861, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/IllVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "antes-2026-maa", "Antonini2020", "Balabanian-2010-IIV", "Balduz_01", "Bayat_2019", "Bechtold2020", "Birkeland-2012-IMC", "brandstaetter_01", "bruckner-2005-ICV", "bruckner-2006-ICE", "bruckner-2007-STF", "bruckner-2008-IIV", "bruckner-2010-HVC", "bruckner-2010-IFC", "cellVIEW_2015", "Chen-Information-2016", "Deutsch-2018", "Dhanoa_2021", "Dhanoa2024", "dietrich-2016-viseq2", "donabauer_2019_1", "eg-tut2005-iv", "eschner-2023-ims", "Essler2022", "gangl-2018-gpsart", "Gehrer_Daniel_CUI", "Gehrer-2017-molmach", "gerl-2006-vhi", "Gogel2020", "Groeller_2011_IPV", "Groeller_2016_I3", "Groeller_2016_I6", "Groeller_2016_I7", "Groeller_2016_I8", "Groeller_V1_2020", "groeller-2006-ivt", "groeller-2007-fci", "groeller-2008-irs", "Groeller-2010-IFI", "gruber-2025-vps", "Halladjian_2020", "haushofer-2018-skinning", "Heim_2020", "horvath-2018-ism", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "Knapp_2017_CVR", "Koeppel2020", "kolesar-ivan-2014-polymers", "Konev-FCV2018", "Koszticsak-2017-ewt", "Kouril_2017_11", "kouril-2020-hyperlabels", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "kroesl_x_card_2017", "Lackner_2022", "Langer_Edith_IR1", "lawonn-2018-illvisstar", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "LeMuzic_2016_PhD", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "Leutschacher_2022", "ludwig-2012-MT", "Manczarski-2016", "Matusich-2017-01", "Mautner 2020", "Mayr-2017-1", "Melo_2018_11", "Meusburger_2020", "Miao_2019", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao2018Dimsum", "Michl_2017_CSV", "mindek-2015-mc", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-2019-mci", "mindek-xmas-card-2016", "Moellinger_Christian_IDE2", "Niedermayer_2018", "Ortner_PhD", "Ortner2020", "pahr-2021-vologram", "Panayotov", "patel_daniel_2007_IRSD", "Pauschenwein_2022", "Peter_2012_AIV", "plank-2017-sldg", "prost-2016-molecule", "purgathofer-2008-cgi", "Radwan-2017-Occ", "Rautek-2007-SLI", "Rautek-2008-IDS", "Rautek-2008-VF", "Reichinger_2016", "Reichinger_Fuhrmann_2016", "Reisacher_Matthias_CPW", "Reisacher2016", "Riegelnegg_2019", "rippl-2023-atg", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "schindler_2020vis", "schmidlehner2021", "scholz_2021", "Schrempf_2020", "schultes_lampi", "seyfert-2017", "sikachev-2010-ill_vis_vol_ren", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "Spechtenhauser_Florian_2016", "stappen_2017_animatedcomic", "Stoll2020", "sturl_2016_dynlabels", "Swoboda2020", "szabo_patrik-2022-tour", "takahashi-2019-acdt", "Thomas-2018", "TR-186-2-07-08", "Troidl_2021", "Troidl_2022", "tut-eg-2006", "tut-siggraph-2006", "tut-vis-2006", "tut-vis-2007", "Unger2020", "Vasileva_2022", "Viola_Ivan_2013_SVA", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "viola-evr", "Viola-Pondering-2017", "Viola-vistutillustrativevis", "Waldin_Nicholas_2016_Colormaps", "waldin-2019-ccm", "Waldner_2017_11", "Wihann_2017", "Woschizka_2021", "wu-2019-bmc", "wu-2019-report", "Zaufel_2021", "zechmeister2020", "Zeng_2021", "Zusag-2017-Bach" ], "projects": [ "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=IllVis", "__class": "ResearchArea" }, { "id": "InfoVis", "drupal_id": 4128, "name": "Information Visualization and Visual Analytics", "short_abstract": "In this research area, our focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning. ", "abstract": "

Data and information created by various processes (e.g., simulations) is getting larger, and more and more complex. We use interactive visualization and analysis techniques to facilitate exploration of complex parameter spaces (e.g., to analyze and compare parameters for automotive engineering, reconstruction algorithms, or geometry generators) or unstructured information collections (e.g., annotated digital documents or image collections). Our research focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning.

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"pahr-2025-nodkant", "Pahr2020", "Pajer_2012_VoM", "Panayotov", "papantonakis-2024-rmf", "Parzer_2013_IIG", "patel_2009_MC", "patel_daniel_2007_IRSD", "patel-2008-tsa", "patel-2009-evr", "patel-2011-PEA", "Pauschenwein_2022", "Peter_2012_AIV", "Pezenka-2016-MT", "Pfahler_David_2015_IPI", "Pfahler-2016-MT", "PH-2011-LDS", "phd-viola", "Philipp_Hochhauser_2023", "Pilizar_-2020-bachelor", "piringer-2009-hds", "Plank_Pascal_2015_HVP", "plank-2017-sldg", "PMI_AR_2012", "pointner_simon-2020", "polatsek-2018-stv", "polatsek-2018-stv", "Pramerdorfer-2011-PAV", "preim-2009-sve", "Presch_2020", "Priselac2021", "puehringer-2009-sbm", "puenguentzky-2014-ht", "Purchase-2020-gd", "raidou_2018_bladderrunner", "raidou_2019_pelvisrunner", "raidou_2019_preha", "raidou_2019_springer", "raidou_2020Onc", "raidou_EuroVis15", "raidou_eurovis16", "raidou_miccai16", "raidou_pingu2020", "raidou_previs2021", "raidou_RO2019", "raidou_shonan167", "raidou_slicedice", "raidou_star2019", "raidou_vcbm14", "raidou_vis14", "raidou_vis15", "raidou_visgap2020", "raidou2018_rv3", "raidou2018visualflatter", "raidou2019_prsps", "rasch-2016-imgses", "Rau08", "Rautek_Peter_2014_TUC", "Rautek_Peter_2014_VSA", "rautek-2005-dvr", "Rautek-2007-O3D", "Rautek-2007-SLI", "Rautek-2008-IDS", "Rautek-2008-kav", "Rautek-2008-VF", "rautek-2009-vmv", "RAUTEK06", "Rautek06Vis", "Rautek06VMLS", "rautek2010", "Red_Andreas_2015_FFT", "Reh_Andreas_VoP", "reh-2013", "reina-2020-mtv", "Reisacher_Matthias_CPW", "Reisacher2016", "Reiter_2009_IXIA", "Reiter2017CVAP", "Rezk06Vis", "Ribicic_2012_SUS", "Ribicic_2012_VAS", "Ribicic-2010-CRS", "Riegelnegg_2019", "rinortner_susanne-2019-vpicc", "rinortner_susanne-2019-vpicc", "Rippberger_2019", "rippl-2023-atg", "ritzberger-2010-nar", "Ropinski-2012-UBT", "rozana-2026-vcfd", "rraidou_clinical", "rraidou_EG17", "rraidou_phdbook", "rsabin-2013", "ruiz-2008-OVR", "ruiz-2008-SEV", "samoul-2019-cnp", "Sanjin_Rados_RV", "Sarkis_2021", "Sbardellati-2019-vcbm", "Sbardellati-2019-vcbm", "sbardellati-2021-eveos", "scharsach-2005-adv", "Schernthaner-2017-MCP", "schindler_2020vis", "Schindler-2022-eurovis", "schindler2020", "schleicher-2011-VLSC", "Schmidlehner_Sandra_SbC", "schmidlehner2021", "schmidt-2011-mt", "schmidt-phd", "schmidt-phd", "schoellhuber-2008-asc", "scholz_2021", "Schrempf_2018", "Schrempf_2020", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "schuh-2018-mesh-blending", "schultes_lampi", "Schulze_Florian_2013_CMI", "schwankl-2013-smis", "seyfert-2017", "shakhova-2023-atp", "sietzen-2019-wnn", "sietzen-2019-wnn", "sietzen-2021-perturber", "sietzen-2022-vacnnr", "sietzen-ifv-2019", "sifuentes-2018-crowd", "SifuentesGangl2017FIS", "sikachev_peter_2010_STLCI", "sikachev_peter-2011-dfc", "sikachev_peter-2011-incshad", "sikachev_peter-2011-metavis", "sikachev_peter-2011-protovis", "sikachev-2010-DFC", "sikachev-2010-ill_vis_vol_ren", "Sippl_Sebastian_EFG", "smiech-2018-tei", "Smisek_Michal_A3D", "Sollboeck_2011_FSS", "sollboeck-2011", "Solteszova-2009-VQN", "solteszova-2010-MOS", "Solteszova2016", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "sorger-2019-odn", "sorger-2021-egonet", "Soros_AVN_2011", "Soros-AV-2010", "Spechtenhauser_Florian_2016", "spegel-gruenberger-2020", "Spelitz2020", "spoerk-2010-hpgpu", "Stabel_2012_UDM", "stappen_2017_animatedcomic", "Staudacher_2022", "staudacher_florian-2016-topo3d", "stehno-2011-RVD", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "STEINLECHNER-2019-ICT", "StickmanMax-shoetta-kampfer", "stoff-2025-pvu", "stoff-concepMap-2021", "StrakaVis2004", "stritzel2022", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "suntinger-2008-etet", "suntinger-2008-tet", "Swoboda_Nicolas_VIT", "Swoboda2020", "szabo_patrik-2022-tour", "szabo-thesis", "takahashi-2019-acdt", "tekaya-2025-amo", "tekaya-2025-amo", "termeer-2006-000", "termeer-2007-covicad", "termeer-2008-scmr", "termeer-2008-vis", "termeer-2009-cvc", "termeer-2009-scmr", "textures-3d-printing", "thesis-kronsteiner", "thesis-tekaya", "Thomas-2018", "Thurner-2005-IVR", "toth-2007-ndd", "TR-186-2-05-01", "TR-186-2-05-02", "TR-186-2-05-03", "TR-186-2-05-04", "TR-186-2-05-06", "TR-186-2-05-07", "TR-186-2-05-08", "TR-186-2-06-01", "TR-186-2-06-02", "TR-186-2-06-03", "TR-186-2-06-04", "TR-186-2-07-02", "TR-186-2-07-03", "TR-186-2-07-04", "TR-186-2-07-05", "TR-186-2-07-06", "TR-186-2-07-07", "TR-186-2-07-08", "TR-186-2-07-10", "TR-186-2-07-11", "TR-186-2-07-12", "TR-186-2-08-01", "TR-186-2-08-02", "TR-186-2-08-03", "TR-186-2-08-04", "TR-186-2-08-05", "TR-186-2-08-06", "TR-186-2-08-07", "TR-186-2-08-08", "TR-186-2-08-10", "TR-186-2-08-11", "TR-186-2-08-12", "TR-186-2-08-14", "TR-186-2-09-01", "TR-186-2-15-03", "TR1862162", "Tramberger_2018", "Tramberger2017BCS", "Trautner_Thomas_2014_VAE", "trautner-2018-imd", "trautner-2018-imd", "travnicek-2017-thm", "Trenkwalder-2004-MAR", "tretyak-2025-tacmedvr", "Troidl_2019", "Troidl_2021", "Troidl_2022", "turner-aso", "tut-eg-2006", "tut-siggraph-2006", "tut-vis-2006", "tut-vis-2007", "tweebo-2014", "ulschmid-2024-reo", "ulschmid-2025-apc", "unger_2017", "unger-2019_vcp", "Unger2020", "unterguggenberger-2024-fropo", "usul-thesis", "vad_2015_phd", "Vad_Viktor_2015_RVV", "vad-2016-bre", "vaico", "varchola_andrej-2012-fetoscopic", "Vasileva_2022", "Vasileva-2018", "vessel2003", "Viola_2013_IDV", "Viola_Ivan_2013_CAI", "Viola_Ivan_2013_D3D", "Viola_Ivan_2013_DC", "Viola_Ivan_2013_GS", "Viola_Ivan_2013_HQ3", "Viola_Ivan_2013_RMA", "Viola_Ivan_2013_RSb", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_DAC", "Viola_Ivan_IIP", "Viola_Ivan_UVP", "Viola_Ivan_VDP", "Viola-05-Smart", "Viola-2003-GPU", "Viola-2003-Har", "viola-2003-hbn", "Viola-2003-NON", "viola-2004-gbf", "Viola-2004-GPU", "viola-2004-har", "viola-2004-har2", "viola-2004-idv", "viola-2004-imp", "Viola-2004-ImpX", "Viola-2004-ImpX2", "viola-2005-imp", "viola-2006-FoA", "viola-evr", "Viola-Pondering-2017", "viola-popular-article-2006", "Viola-vistutillustrativevis", "vis-foa", "VisWeek-Tutorial-2012-Uncertainty", "vitruvian_2019", "voglreiter-2023-tro", "Vucenovic_2022", "vucini_2006", "vucini_2008_rnp", "vucini_2009", "vucini_erald-2007-FRI", "vucini-2009-phd", "vucini-2011", "Wagner_032017", "walchhofer_ar_flowmaps", "walchhofer-tso", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "Waldin_Nicholas_2017_FlickerObserver", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2017-thesis", "waldin-2019-ccm", "waldin-2019-ccm", "Waldner_2017_11", "Waldner_2017_11", "waldner-2013-facetCloudsGI", "waldner-2013-ubiWM", "waldner-2014-af", "waldner-2014-ghi", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "waser_2011_VSD", "Waser-2010-WL", "webGPU_aggregateVis-2023", "weiner_2011", "Weissenboeck_2019", "Weissenboeck_2019_PhD", "weissenboeck-2014", "Wihann_2017", "wolf-2023-cc", "wolf-2024-jhd", "Woschizka_2021", "wu-2017-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-shonan", "wu-2018-story", "wu-2019-bmc", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-smwp", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg", "wu-2021", "wu-2021-vi", "xmastree2002", "xmastree2005", "ymca", "YOGHOURDJIAN2019", "Zambal-2003-SWA", "zambal-2005-3dact", "Zaufel_2021", "zauner-2013-svkinect", "zechmeister2020", "Zeng_2021", "Zhu-2014-flowvis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Workgroup&id=vis", "__class": "Workgroup" }, { "id": "deskollage", "workgroup_id": "vis", "drupal_id": 4198, "drupal_path": "/research/projects/deskollage", "name": "Visual Information Foraging on the Desktop", "name_de": null, "short_title": "deskollage", "website": null, "status": "active", "short_abstract": "The goal of this project is to design and develop novel interactive visualization techniques to support knowledge workers in making sense of their unstructured, dynamic information collections. ", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. On the one hand, the studies show that, in some situations, interactive visualization can be less efficient than working with unprocessed text-based information. On the other hand, the studies also show that combining automatic data analysis with interactive visualization can lead to more unexpected findings, especially when exploring large data. The extent of manual information organization varies with the task: the less users know about the gathered information, the more automatic organization they expect. \n\nIn summary, this project contributed novel user interface concepts and design guidelines for user interfaces supporting information foraging and sensemaking. The techniques and study results were published at high-ranking peer-reviewed venues, and it can be expected that the findings of this project shape the way how users seek and organize their information in the future. \n\n", "start_date": "2015-12-01", "end_date": "2018-12-31", "leader_id": 1110, "logo": { "name": "logo.png", "path": "project:deskollage", "type": "image/png", "size": 331697, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/deskollage/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "T 752-N30", "comment": null } ], "research_areas": [ "InfoVis" ], "publications": [ "2019-ic", "byska-2019-mdfc", "casellato-2016-pkg", "cizmic-2018-evd", "donabauer-2015-asc", "dworschak-2016-szcm", "edlinger-2018-vwr", "georgiev-2019-cbg", "geymayer-2017-std", "gundacker-2020-wlm", "gusenbauer-2018", "hromniak-2019-vcn", "Koszticsak-2017-ewt", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "polatsek-2018-stv", "samoul-2019-cnp", "sietzen-2019-wnn", "sietzen-ifv-2019", "smiech-2018-tei", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "trautner-2018-imd", "unger-2019_vcp", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg" ], "url": "https://www.cg.tuwien.ac.at/research/projects/deskollage", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/waldin-2019-ccm/", "__class": "Publication" }, { "id": "kouril-2018-LoL", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "Labels on Levels: Labeling of Multi-Scale Multi-Instance and Crowded 3D Biological Environments", "date": "2019-01", "abstract": "Labeling is intrinsically important for exploring and understanding complex environments and models in a variety of domains. We present a method for interactive labeling of crowded 3D scenes containing very many instances of objects spanning multiple scales in size. In contrast to previous labeling methods, we target cases where many instances of dozens of types are present and where the hierarchical structure of the objects in the scene presents an opportunity to choose the most suitable level for each placed label. Our solution builds on and goes beyond labeling techniques in medical 3D visualization, cartography, and biological illustrations from books and prints. In contrast to these techniques, the main characteristics of our new technique are: 1) a novel way of labeling objects as part of a bigger structure when appropriate, 2) visual clutter reduction by labeling only representative instances for each type of an object, and a strategy of selecting those. The appropriate level of label is chosen by analyzing the scene's depth buffer and the scene objects' hierarchy tree. We address the topic of communicating the parent-children relationship between labels by employing visual hierarchy concepts adapted from graphic design. Selecting representative instances considers several criteria tailored to the character of the data and is combined with a greedy optimization approach. We demonstrate the usage of our method with models from mesoscale biology where these two characteristics-multi-scale and multi-instance-are abundant, along with the fact that these scenes are extraordinarily dense.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "preview", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 580, "image_height": 416, "name": "kouril-2018-LoL-preview.png", "type": "image/png", "size": 528337, "path": "Publication:kouril-2018-LoL", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/kouril-2018-LoL/kouril-2018-LoL-preview.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/kouril-2018-LoL/kouril-2018-LoL-preview:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1383, "drupal_id": 1132, "orcid_id": null, "website": 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This applies to scientists trying to make sense of their experiments and simulations, to bankers and traders trying to understand the dynamics of the financial markets, and to large enterprises which need to understand the principles behind demand and supply—to name just a few examples. The basic problem in all these cases is that people need to identify important and/or unexpected features in large simulated or captured datasets. Visualization is the domain that facilitates this process of sense-making by dramatically simplifying the process of obtaining an understanding of the data—by representing data visually and thus amplifying people’s cognition. This inherent capability of (good) visualization techniques to amplify human cognition, however, is no longer enough to be able to make sense of today’s huge datasets. 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In living systems, one molecule is commonly involved in several distinct physiological functions. The roles of molecules are commonly summarized in pathway diagrams, which, however, are abstract, hierarchically nested and thus is difficult to comprehend especially by non-expert audience. The primary goal of this research in visualization is to intuitively support the comprehensive understanding of relationships among biological networks using interactively computed illustrations. Illustrations, especially in textbooks of biology are carefully designed to clearly present reactions between organs as well as interactions within cells. Automatic generation of illustrative visualizations of biological networks is thus the technical content of this proposal. Automatic generation of hand-drawn illustrations has been a challenging task due to the difficulty of algorithmically describing a human creative process such as evaluating and selecting significant information and composing meaningful explanations in a visually plausible manner. The project also involves experts from several disciplines including network and medical visualization, data mining, systems biology as well as perceptual psychology. The result will provide a new direction for physiological process analysis and accelerate the knowledge transfer not only within experts but also to the public. Acknowledgment: The project has received funding from the European Union Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 747985.

\r\n", "abstract": "

In living systems, one molecule is commonly involved in several distinct physiological functions. The roles of molecules are commonly summarized in pathway diagrams, which, however, are abstract, hierarchically nested and thus is difficult to comprehend especially by non-expert audience. The primary goal of this research in visualization is to intuitively support the comprehensive understanding of relationships among biological networks using interactively computed illustrations. Illustrations, especially in textbooks of biology are carefully designed to clearly present reactions between organs as well as interactions within cells. Automatic generation of illustrative visualizations of biological networks is thus the technical content of this proposal. Automatic generation of hand-drawn illustrations has been a challenging task due to the difficulty of algorithmically describing a human creative process such as evaluating and selecting significant information and composing meaningful explanations in a visually plausible manner. The project also involves experts from several disciplines including network and medical visualization, data mining, systems biology as well as perceptual psychology. The result will provide a new direction for physiological process analysis and accelerate the knowledge transfer not only within experts but also to the public. Acknowledgment: The project has received funding from the European Union Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 747985.

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"Groeller_2012_ViV", "Groeller_2012_VV", "Groeller_2014_CaQ", "Groeller_2014_CQV", "Groeller_2014_CV", "Groeller_2014_RWA", "Groeller_2014_STC", "Groeller_2014_UPS", "Groeller_2014_VND", "Groeller_2016_I1", "Groeller_2016_I2", "Groeller_2016_I3", "Groeller_2016_I4", "Groeller_2016_I5", "Groeller_2016_I6", "Groeller_2016_I7", "Groeller_2016_I8", "Groeller_2016_P1", "Groeller_2016_P2", "Groeller_2016_P3", "Groeller_2016_P4", "Groeller_2016_P6", "Groeller_2016_P7", "Groeller_2021_11", "Groeller_2021_BVM", "Groeller_2021-10", "Groeller_Edi_2013_TVC", "Groeller_Edi_2013_VCQ", "Groeller_Edi_2013TVCK", "Groeller_Edi_VKA", "Groeller_Eduard_2014_THS", "Groeller_Eduard_2014_TSP", "Groeller_Eduard_2014_UCT", "Groeller_Eduard_2015_SMV", "Groeller_Eduard_2015_TCU", "Groeller_V1_2020", "Groeller_V2_2020", "Groeller_V3_2020", "Groeller_V42020", "Groeller_V5_2020", "groeller-1987-opt", "groeller-1988-duale", "groeller-1988-using", "groeller-1991-frac", "groeller-1991-temp", "groeller-1992-frac", "groeller-1992-fractals", "groeller-1992-fraktale", "groeller-1992-vis", "groeller-1993-acc", "groeller-1993-cha", "groeller-1993-coh", "groeller-1993-coh1", "groeller-1993-daten", "groeller-1993-dist", "groeller-1993-disto", "groeller-1993-eff", "groeller-1993-exp", "groeller-1993-frak", "groeller-1993-grund", "groeller-1993-oct", "Groeller-1994-AIV", "groeller-1994-appl", "Groeller-1994-AVT", "groeller-1994-coh", "Groeller-1994-CSA", "groeller-1994-ext", "Groeller-1994-HIS", "groeller-1994-hyper", "Groeller-1994-IDN", "groeller-1994-int", "Groeller-1994-ITV", "groeller-1994-mod", "Groeller-1994-MRN", "groeller-1994-tech", "groeller-1994-vis", "groeller-1995-appl", "groeller-1995-attract", "Groeller-1995-CCG", "groeller-1995-dyn", "Groeller-1995-GOW", "Groeller-1995-IED", "groeller-1995-inter", "groeller-1995-lok", "groeller-1995-mod", "groeller-1995-non", "Groeller-1995-SDC", "groeller-1995-vis", "groeller-1996-ACE", "groeller-1996-avn", "Groeller-1998-TunVis", "Groeller-1998-VAD", "Groeller-1998-VDS", "Groeller-1999-Dat", "Groeller-1999-Vis", "Groeller-2000-Vis", "Groeller-2001-IDV", "groeller-2002-anw", "Groeller-2002-Ins", "groeller-2002-med", "groeller-2002-wiss", "groeller-2003-fea", "groeller-2003-med", "groeller-2003-scie", "groeller-2003-vol", "groeller-2004-efficient", "groeller-2004-imp", "groeller-2004-sci", "groeller-2005-abs", "groeller-2005-dia", "groeller-2005-foc", "groeller-2005-imp", "groeller-2005-impo", "groeller-2005-proc", "groeller-2005-sma", "groeller-2005-smar", "groeller-2005-volg", "groeller-2006-cgf", "groeller-2006-civ", "groeller-2006-ivt", "groeller-2006-tvcg", "groeller-2007-csu", "groeller-2007-fci", "groeller-2007-mva", "groeller-2007-vis", "groeller-2007-visII", "groeller-2007-vws", "groeller-2008-att2", "groeller-2008-How", "groeller-2008-hsp", "groeller-2008-irs", "groeller-2008-kav2", "groeller-2008-kav3", "groeller-2008-kav4", "groeller-2008-lsy", "Groeller-2010-CVC", "groeller-2010-How", "Groeller-2010-IFI", 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Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n", "website": "https://www.cg.tuwien.ac.at/research/area/BioVis", "teaser": { "name": "teaser.png", "path": "research_area:BioVis", "type": "image/png", "size": 16330957, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/BioVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "amirkhanov-2019-manylands", "byska-2019-mdfc", "cellVIEW_2015", "cmolik-2020-tvcg", "Dietrich_1", "dietrich-2016-viseq2", "Ehlers_PhD", "ehlers-2025-ait", "eschner-2023-ims", "eschner-blur-2022", "Escribano_2017", "Furmanova_2018", "Gehrer-2017", "Gehrer-2017-molmach", "glinzner-2016-tex", "Halladjian_2020", "kapferer-2017-godot", "klein_2017_IM", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koch-2018-sso", "Kolesar-Fractional-2016", "kolesar-ivan-2014-polymers", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kozlikova-Visualization-2016b", "Krone2016VABC", "Kugler_2019", "lemuzic_2015_timelapse", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lipp-2017-mgpu", "lipp-2017-vulkan", "Manczarski-2016", "manylands_award", "Miao_2019", "miao_inria_2017", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-xmas-card-2016", "Mitterhofer_2017", "nguyen_2020-covid", "Nowak_2020", "raidou_2019_springer", "raidou_shonan167", "raidou2018visualflatter", "rasch-2016-imgses", "Reisacher2016", "rinortner_susanne-2019-vpicc", "Sarkis_2021", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2013-neuromap", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "stappen_2017_animatedcomic", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "trautner-2018-imd", "unger-2019_vcp", "vad_2015_phd", "vad_viktor-2017-WVE", "vad-2016-bre", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "waldin-2019-ccm", "waldner-2014-af", "Weissenboeck_2019", "wu-2017-dagstuhl", "wu-2018-metabo", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg" ], "projects": [ "BioNetIllustration", "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=BioVis", "__class": "ResearchArea" }, { "id": "IllVis", "drupal_id": 4131, "name": "Illustrative Visualization", "short_abstract": "In this research area, we develop rendering methods that are inspired by scientific illustrations, in order to make complex biological information more intuitive to understand and more pleasant to read.", "abstract": "Scientific illustration is concerned with researching ways in which complex biological and medical data can be abstracted in order to convey a desired information that would otherwise be impossible or hard to retrieve from the original data. Illustrators apply such techniques, for instance, to present non-important parts of an organ in a simplified way, while using detailed representations to put the focus of attention on a region where a tumor might be situated.\n\nTo identify such meaningful visual abstractions for visualization, their effectiveness for human perception and cognition has to be assessed, and they have to be formalized in order to make them applicable in rendering algorithms. In this project, we try to advance the understanding of procedural visual abstraction of complex physiological processes that describe the complex machinery of biological life.", "website": "https://www.cg.tuwien.ac.at/research/area/IllVis", "teaser": { "name": "teaser.jpg", "path": "research_area:IllVis", "type": "image/jpeg", "size": 34861, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/IllVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "antes-2026-maa", "Antonini2020", "Balabanian-2010-IIV", "Balduz_01", "Bayat_2019", "Bechtold2020", "Birkeland-2012-IMC", "brandstaetter_01", "bruckner-2005-ICV", "bruckner-2006-ICE", "bruckner-2007-STF", "bruckner-2008-IIV", "bruckner-2010-HVC", "bruckner-2010-IFC", "cellVIEW_2015", "Chen-Information-2016", "Deutsch-2018", "Dhanoa_2021", "Dhanoa2024", "dietrich-2016-viseq2", 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"xmastree2002", "xmastree2005", "ymca", "YOGHOURDJIAN2019", "Zambal-2003-SWA", "zambal-2005-3dact", "Zaufel_2021", "zauner-2013-svkinect", "zechmeister2020", "Zeng_2021", "Zhu-2014-flowvis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Workgroup&id=vis", "__class": "Workgroup" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/Miao_2019/", "__class": "Publication" }, { "id": "klein_2019_MSA_Poster", "type_id": "poster", "tu_id": null, "repositum_id": null, "title": "A Multi-Scale Animation Framework for Biological Fibrous Structures", "date": "2019", "abstract": "Fibrous structures are ubiquitous in cell biology and play essential structural and functional roles in the life cycle of a cell. They are long polymers, such as DNA carrying genetic information, or filaments forming the cytoskeleton, crucial for cell division and maintaining the cell shape. In order to disseminate new findings of such structures to peers or a general audience, animated 3D models of these structures have to be created, as they are too small to be imaged with microscopes. However, this is a tedious task carried out by scientific animators, who manually create expressive visual representations of biological phenomena. In this work, we present a novel concept which simplifies the process of animating multi-scale procedural models of biological fibrous structures. In contrast with existing work in the domain of molecular visualization, our approach can also capture dynamics, which are important to show when communicating biological processes.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 900, "image_height": 1269, "name": "klein_2019_MSA_Poster-image.jpg", "type": "image/jpeg", "size": 642687, "path": "Publication:klein_2019_MSA_Poster", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/klein_2019_MSA_Poster/klein_2019_MSA_Poster-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/klein_2019_MSA_Poster/klein_2019_MSA_Poster-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1285, "drupal_id": 1146, "orcid_id": null, "website": 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"cornel-2022-wih", "Cornel2016CFM", "Groeller_2014_RWA", "kerbl-2022-trienc", "Konev-FCV2018", "kroesl-2019-MoD", "rauer-zechmeister-2024-h3p" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "Cornel_Daniel_2015_VOC", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "CORNEL-2017-FRS", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "CORNEL-2019-IVF", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Cornel2016CFM", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "zechmeister2020", "field_id": "co_supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=877", "__class": "Author" }, { "id": 798, "drupal_id": 714, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/JürgenWaser", "firstname": "Jürgen", "lastname": "Waser", "searchname": "Jürgen Waser", "is_teacher": false, "name": "Jürgen Waser", "publications": [ "Cornel_Daniel_2015_VOC", "CORNEL-2019-IVF", "cornel-2022-wih", "Cornel2016CFM", "fuchs_vhml", "Groeller_2011_NR", "Groeller_2014_RWA", "Konev-FCV2018", "kroesl-2019-MoD", "rauer-zechmeister-2024-h3p", "Ribicic_2012_SUS", "Ribicic_2012_VAS", "waser_2011_VSD", "Waser-2010-WL" ], "publications_first": [], "project_leader": [ "Scenario Pool" ], "publication_field": [ { "publ_id": "Groeller_2011_NR", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Gurbat_2011_SBS", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "Matusich-2017-01", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "Ribicic-2010-CRS", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Waser-2010-WL", "field_id": "lecturer", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=798", "__class": "Author" } ], "doi": "https://doi.org/10.1016/j.cag.2018.07.004", "issn": "0097-8493", "journal": "Computers & Graphics", "number": "5", "open_access": "no", "pages": "25–35", "pages_from": "25", "pages_to": "35", "volume": "75", "research_areas": [ { "id": "IllVis", "drupal_id": 4131, "name": "Illustrative Visualization", "short_abstract": "In this research area, we develop rendering methods that are inspired by scientific illustrations, in order to make complex biological information more intuitive to understand and more pleasant to read.", "abstract": "Scientific illustration is concerned with researching ways in which complex biological and medical data can be abstracted in order to convey a desired information that would otherwise be impossible or hard to retrieve from the original data. Illustrators apply such techniques, for instance, to present non-important parts of an organ in a simplified way, while using detailed representations to put the focus of attention on a region where a tumor might be situated.\n\nTo identify such meaningful visual abstractions for visualization, their effectiveness for human perception and cognition has to be assessed, and they have to be formalized in order to make them applicable in rendering algorithms. In this project, we try to advance the understanding of procedural visual abstraction of complex physiological processes that describe the complex machinery of biological life.", "website": "https://www.cg.tuwien.ac.at/research/area/IllVis", "teaser": { "name": "teaser.jpg", "path": "research_area:IllVis", "type": "image/jpeg", "size": 34861, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/IllVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "antes-2026-maa", "Antonini2020", "Balabanian-2010-IIV", "Balduz_01", "Bayat_2019", "Bechtold2020", "Birkeland-2012-IMC", "brandstaetter_01", "bruckner-2005-ICV", "bruckner-2006-ICE", "bruckner-2007-STF", "bruckner-2008-IIV", "bruckner-2010-HVC", "bruckner-2010-IFC", "cellVIEW_2015", "Chen-Information-2016", "Deutsch-2018", "Dhanoa_2021", "Dhanoa2024", "dietrich-2016-viseq2", "donabauer_2019_1", "eg-tut2005-iv", "eschner-2023-ims", "Essler2022", "gangl-2018-gpsart", "Gehrer_Daniel_CUI", "Gehrer-2017-molmach", "gerl-2006-vhi", "Gogel2020", "Groeller_2011_IPV", "Groeller_2016_I3", "Groeller_2016_I6", "Groeller_2016_I7", "Groeller_2016_I8", "Groeller_V1_2020", "groeller-2006-ivt", "groeller-2007-fci", "groeller-2008-irs", "Groeller-2010-IFI", "gruber-2025-vps", "Halladjian_2020", "haushofer-2018-skinning", "Heim_2020", "horvath-2018-ism", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "Knapp_2017_CVR", "Koeppel2020", "kolesar-ivan-2014-polymers", "Konev-FCV2018", "Koszticsak-2017-ewt", "Kouril_2017_11", "kouril-2020-hyperlabels", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "kroesl_x_card_2017", "Lackner_2022", "Langer_Edith_IR1", "lawonn-2018-illvisstar", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "LeMuzic_2016_PhD", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "Leutschacher_2022", "ludwig-2012-MT", "Manczarski-2016", "Matusich-2017-01", "Mautner 2020", "Mayr-2017-1", "Melo_2018_11", "Meusburger_2020", "Miao_2019", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao2018Dimsum", "Michl_2017_CSV", "mindek-2015-mc", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-2019-mci", "mindek-xmas-card-2016", "Moellinger_Christian_IDE2", "Niedermayer_2018", "Ortner_PhD", "Ortner2020", "pahr-2021-vologram", "Panayotov", "patel_daniel_2007_IRSD", "Pauschenwein_2022", "Peter_2012_AIV", "plank-2017-sldg", "prost-2016-molecule", "purgathofer-2008-cgi", "Radwan-2017-Occ", "Rautek-2007-SLI", "Rautek-2008-IDS", "Rautek-2008-VF", "Reichinger_2016", "Reichinger_Fuhrmann_2016", "Reisacher_Matthias_CPW", "Reisacher2016", "Riegelnegg_2019", "rippl-2023-atg", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "schindler_2020vis", "schmidlehner2021", "scholz_2021", "Schrempf_2020", "schultes_lampi", "seyfert-2017", "sikachev-2010-ill_vis_vol_ren", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "Spechtenhauser_Florian_2016", "stappen_2017_animatedcomic", "Stoll2020", "sturl_2016_dynlabels", "Swoboda2020", "szabo_patrik-2022-tour", "takahashi-2019-acdt", "Thomas-2018", "TR-186-2-07-08", "Troidl_2021", "Troidl_2022", "tut-eg-2006", "tut-siggraph-2006", "tut-vis-2006", "tut-vis-2007", "Unger2020", "Vasileva_2022", "Viola_Ivan_2013_SVA", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "viola-evr", "Viola-Pondering-2017", "Viola-vistutillustrativevis", "Waldin_Nicholas_2016_Colormaps", "waldin-2019-ccm", "Waldner_2017_11", "Wihann_2017", "Woschizka_2021", "wu-2019-bmc", "wu-2019-report", "Zaufel_2021", "zechmeister2020", "Zeng_2021", "Zusag-2017-Bach" ], "projects": [ "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=IllVis", "__class": "ResearchArea" }, { "id": "Rendering", "drupal_id": 4134, "name": "Rendering", "short_abstract": "In this area, we concentrate on algorithms that synthesize images to depict 3D models or scenes, often by simulating or approximating the physics of light.", "abstract": "The rendering of 3D models and scenes has been a major, long-standing challenge in computer graphics that can be divided into two major subfields. Real-time rendering refers to the real-time synthesis of images on commodity graphics hardware to facilitate interaction for visualizations or computer games. The field of physically based rendering focuses on algorithms that accurately simulate the physics of light for use in the movie industry, architectural visualizations, etc. Compared to real-time rendering methods, these algorithms generally require a considerable amount of time (i.e., hours up to days) to generate acceptable results.\n\nIn the context of real-time rendering, our work revolves around the development of algorithms to achieve higher visual quality. Furthermore, we work on techniques to accelerate physically based rendering algorithms to make them viable for interactive rendering. Another aspect of our research work revolves around tools that facilitate the work of content creators.", "website": "https://www.cg.tuwien.ac.at/research/area/Rendering", "teaser": { "name": "teaser.png", "path": "research_area:Rendering", "type": "image/png", "size": 5244928, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Rendering/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "2011scherzerE", "2018_Mautner_Praktikum", "ABG25", "Adorjan-2015", "agyemang-2021-bsdfproxyppg", "Ams25", "antes-g", "arikan-2014-pcvis", "arikan-2015-dmrt", "Artusi-2003-Del", "ASCHL-2022-OTV", "Auzinger_2012_AAA", "Auzinger_2012_GeigerCam", "Auzinger_2013_AnaVis", "Auzinger_2013_NSAA", "Auzinger_2013_SAR", "Auzinger_2014_DCGI", "Auzinger_2014_UJA", "Auzinger-2015-IST", "bagar2010", "balvan-g", "Bauer_Dominik_2018_VR", "BAUER-2024-PWG", "BAUER-2025-PCW", "bernhard-2011-bmtf", "bernhard-2014-GTOM", "bhagvat-09-frusta", "birsak-2013-sta", "Bittner-2001-Vis", "Bittner-2003-Vis", "Bittner-2004-CHC", "bittner-2005-egsr", "BITTNER-2009-AGVS", "BITTNER-2009-GEFOC", "bittner-2011-scc", "BOKSANSKY-2019-RTS", "brandmair-2025-rub", "brugger-2020-tdp", "brugger-2020-tsdpbr", "Brusi-2001-Opt", "CADIK-2006-IAQ", "CADIK-2008-EHD", "cardoso-2021-cost", "cardoso-2022-rtpercept", "cardoso-2024-r-c", "cardoso-thesis", "cech-2023-taa", "celarek_adam-2019-qelta", "CELAREK-2017-QCL", "CHARALAMBOS-2007-HLOD", "charpenay-2014-sgn", "Che-2025", "cline-09-poisson", "CORNEL-2017-FRS", "CORNEL-2019-IVF", "Derflinger-2026-RTTW2", "Devlin-2002-STA", "dodik-2017-pcbpt", "dworschak-2024-aml", "ecormier-nocca-2025-sls", "eichner-2024-erv", "eickmeyer-2027-tcd", "EISEMANN-2011-RTS", "EISEMANN-2012-ERT", "EISEMANN-2013-ERT", "elagabani-2025-ieh", "Erhardt_Seirlehner-2024-TamashiiIntegration", "ERLER-2017-HVR", "ESBERGER-2016-AHO", "ESCHNER-2019-GDT", "fink-2012-cg1", "Fischer-2018-sssvr", "FRAISS-2017-PCU", "FRAISS-2022-CGMM", "freude_2020_rs", "FREUDE-2015-phd", "freude-2023-prh", "freude-2023-sem", "freude-2025-iso", "freude-2025-ras", "GAMPER-2018-OSG", "GANTNER-2018-ARO", "GANTNER-2019-CRS", "gersthofer_2017_COP", "geyer-2018-apbf", "GIEGL-2006-QVS", "GIEGL-2007-FVS", "GIEGL-2007-QV1", "GIEGL-2007-UNP", "gilmutdinov-2022-aomlbwug", "glanz-2017-pbrcomparison", "goel-2024-rdr", "gramegna-rfr", "GRELAUD-2009-EPA", "GRIESHOFER-2018-GOS", "Grisenti-2026-HSHPG", "Groeller_2016_P3", "Grossfurtner-2023-paego", "Gruber2019", "guerrero-2008-sli", "Habel_07_xms", "Habel_08_SSH", "Habel_09_PGT", "Habel_2007_IAG", "Habel_2007_RTT", "Habel_2009_PhD", "Habel_2012_PSP", "Habel_LSN_2011", "Habel_RAV_2010", "Habel-09-RAT", "Habel-09-THB", "Habel-2010-EIN", "HAFNER-2015-FEM", "HANN_2022_IPT", "hasbay-2026-tfo", "havran-2005-egsr", "havran-2005-sccg", "havran-2006-tut", "hecher-2012-MH", "hecher-2014-MH", "heinz-2019-psi", "hladky-2022-QS", "hofer_kerstin-2023-sketch2model", "horvath_imp", "houska-2020-IPGM", "huber-2025-esl", "huerbe-2019-BA", "intel2016", "ioannis-2026-sro", "JAHRMANN-2013-IGR", "JAHRMANN-2015-GRASS", "JAHRMANN-2016-IGR", "JAHRMANN-2017-RRTG", "jeschke-05-AIP", "jeschke-05-ARI", "jeschke-05-ISTAR", "jeschke-09-praguetalk", "jeschke-09-rendering", "Jeschke-2002-LEMA", "Jeschke-2002-TDMR", "JESCHKE-2007-ISC", "jeschke-2010-diff", "jeschke-2011-est", "Jimenez_SSS_2015", "KAFKA-2014-19MRD", "Kathi-2018-VRB", "Keilman2022", "Kellner-2021-DA", "kendlbacher-2016", "kerbl_2019_planet_poster", "kerbl_2021_hdg", "kerbl-2020-improvencoding", "kerbl-2022-trienc", "kerbl-2024-ah3", "kimmersdorfer-2024-vcpr", "kimmersdorfer-fancyMaps-2023", "KLAUS-2020-PCC", "klein_2019_PHD", "klein_2019_PMP", "klein-2020-rtgi", "knecht_2013_RSM", "knecht_martin_2010_DIR", "knecht_martin_2012_BRDFEstimation", "knecht_martin_2012_RSMR", "knecht_martin_2013_ReflRefrObjsMR", "knecht_martin-2011-FPSPAR", "knecht-2007-ao", "knecht-2011-CBCM", "koch-2019-PR", "KOCH-2021-GVS", "KOCH-2021-GVSDA", "KOEPPEL-2025-Nearfield", "Koeppl-2023-DLO", "Komon2022", "Konev-FCV2018", "Kovacs_2017", "kovacs-2025-pf", "KREUZER-2015-DPA", "KREUZER-2017-PBF", "kristmann-2022-occ", "kristmann-2023-vkl", "KRISTMANN-24-JPG", "kroesl-2017-LiteMaker", "kroesl-2018-DC", "kroesl-2018-TVS", "kroesl-2019-ICthroughVR", "kroesl-2019-ThesisFF", "KROESL-2020-SVI", "kroesl-2020-XREye", "KUE11", "Kugler-2021", "Lan25", "leopold-2019-vox", "Liang-2023-TVR", "lipp-2019-rtxq3", "LIPP-2020-PHD", "lipp-2024-val", "Luidolt-2020-DA", "luidolt-2020-lightperceptionVR", "luksch_2020", "LUKSCH-2013-FLM", "LUKSCH-2014-RTR", "LUKSCH-2019-IGI", "Mantler-06-landscape", "MANTLER-2007-DMBBC", "matt2011", "MATTAUSCH-2006-AVC", "mattausch-2007-iav", "MATTAUSCH-2007-OSP", "mattausch-2008-CHC", "mattausch-2010-tao", "mattausch-2010-var", "Mattausch-2010-vcr", "MATTAUSCH-2012-EOV", "MATTAUSCH-2012-TIS", "MATTAUSCH-2013-FSBE", "MATTAUSCH-2015-CHCRT", "Mazza_2021_05", "Meier_2024_WIALT", "MEINDL-2015-OSR", "metzger-2024-smv", "mindek-2017-marion", "mindek-xmas-card-2016", "murturi_PGG", "muth-2026-clouds", "neumann-2006-gamma", "OPPITZ-2017-3DM", "oppitz-2023-ais", "OPPTIZ-2018-IVRL", "OTEPKA-2020-PPC", "ott-rgi", "ott-va", "panfili-2019-VAVR", "panfili-2021-myop", "PB-VRVis-2018-005", "pegrisch_2018_uvs", "PERNDORFER-2015-ECS", "pernsteiner-2022-msh", "pernsteinre_jakob_2020_eechc", "PETER-2023-PSW", "pichler_2022_fro", "pirraku-f", "pistellato-2023-elp", "pogrzebacz-2023-vkl", "pointner_michael-2017-baa", "preiner_2010_GIPC", "preiner_2017_phd", "preiner11IR", "preissegger-2025-vrh", "Preymann-2022-pytamashii", "probst-2023-para", "prost-2016-molecule", "PROST-2017-RTL", "PROST-2019-RTPAL", "Przemyslaw_Gora_2016_UVU", "purgathofer-2004-real", "purgathofer-2004-some", "Purgathofer-2005-Ros", "Purgathofer-2005-Tub", "Purgathofer-2006-VRVis", "radax-2008-ir", "Rainer_2017", "Rait2022", "Reisner_Irene_2013_R3D", "reznicek-2020-fpgaray", "ROEGNER-2014-TUI", "ROEGNER-2015-IBR", "roth_2021_vdst", "roth_vdi", "roth-2023-vlk", "rumpelnik_martin_2020_PRM", "Rumpelnik_Martin-2020-NPR", "rumpler_2019_PPC", "Rumpler-2019-PPC", "RUMPLER-2021-VOGL", "SAKAI-2015-EAPI", "sakai-2021-eif", "sakai-2024-asa", "sakai-2025-stater", "sakai-thesis", "schedl-2012-dof", "schedl-2013-gP4", "SCHEIBLAUER-2015-WFC", "scherzer_2010a", "Scherzer-2007-PCS", "SCHERZER-2008-FSR", "scherzer-2009-isvc", "SCHERZER-2012-TCM", "scherzer-eg2010", "scherzer-thesis", "scherzer2010b", "scherzer2010d", "scherzer2010e", "scherzer2011c", "scherzer2011d", "SCHOBER-2006-IVSA", "SCHUETZ-2015-HQP", "SCHUETZ-2016-POT", "schuetz-2018-PPC", "schuetz-2019-CLOD", "schuetz-2019-LCO", "SCHUETZ-2019-PCC", "SCHUETZ-2020-MPC", "schuetz-2020-PPC", "SCHUETZ-2021-DISS", "SCHUETZ-2021-PCC", "SCHUETZ-2022-PCC", "SCHUETZ-2023-LOD", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "schuetz-mb", "schwaerzler_2018_phd", "SCHWAERZLER-2012-FAS", "SCHWAERZLER-2013-FPCSS", "Schwengerer_Mathias-2022-BGL", 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"werdermann-va", "WESSNER-2019-PCW", "wiesinger_2020_odpr", "wiesinger-2023-gcg", "Wilkie-2001-Ori", "Wilkie-2004-AMS", "wilkie-2006-dfs", "wilkie-2009-cc", "Wimmer-1999-FWIa", "Wimmer-1999-FWIb", "Wimmer-2001-Poi", "Wimmer-2003-RTE", "Wimmer-2004-LSPM", "Wimmer-2005-HOQ", "WIMMER-2006-PSM", "WIMMER-2006-SIV", "WIMMER-2007-GAR", "WIMMER-2007-RTR", "WIMMER-2008-ART", "WIMMER-2008-CAR", "WIMMER-2008-PVR", "WIMMER-2009-ARTR", "WIMMER-2009-ARTR2", "WIMMER-2009-ARTR3", "WIMMER-2009-CSR", "WIMMER-2009-VCCG", "WIMMER-2016-HARVEST4D", "WIMMER-2019-CGSG", "WIMMER-2020-ASG", "Win25", "winklmueller-2025-ims", "wonka-2000-VisP", "Wonka-2001-Ins", "WONKA-2006-GVS", "x-mas-2013", "zeilinger_matthias-2020-baa", "Zezulka_Matthias-2023-MatLabOptInterface", "Zezulka-2024-FTS", "Zezulka-2025-NRL", "Zezulka-2026-FGTS", "zotti-2005-lum", "zotti-2006-pla", "zotti-2007-PhD", "zotti-2007-wscg", "ZOTTI-2016-VAA", "ZOTTI-2017-BM", "ZOTTI-2017-TSP", "zsolnai-2018-gms", "zsolnai-feher-thesis-2019", 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The VRVis K1 Research Center is the leading application oriented research center in the area of virtual reality (VR) and visualization (Vis) in Austria and is internationally recognized. You can find extensive Information about the VRVis-Center here

\r\n", "abstract": "

The VRVis K1 Research Center is the leading application oriented research center in the area of virtual reality (VR) and visualization (Vis) in Austria and is internationally recognized. You can find extensive Information about the VRVis-Center here

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It is often addressed through the means of level of detail\nschemes coupled with an appropriate coloring of the visualized structures. Ambient occlusion and shadows are often used to\nimprove the depth perception. However, when used excessively, these techniques are sources of visual clutter themselves. In\nthis paper we present a new approach to screen-space illumination algorithms suitable for use in illustrative visualization. The\nillumination effect can be controlled so that desired levels of semantic scene organization cast shadows while other remain\nflat. This way the illumination design can be parameterized to keep visual clutter, originating from illumination, to a minimum,\nwhile also guiding the user in a multiscale model exploration. We achieve this by selectively applying occlusion shading based\non the inherent semantics of the visualized hierarchically-organized data. The technique is in principle generally applicable\nto any hierarchically organized 3D scene and has been demonstrated on an exemplary scene from integrative structural biology.\n", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2120, "image_height": 734, "name": "koch_bernhard_2018-1-image.JPG", "type": "image/jpeg", "size": 371526, "path": "Publication:koch_bernhard_2018-1", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/koch_bernhard_2018-1/koch_bernhard_2018-1-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/koch_bernhard_2018-1/koch_bernhard_2018-1-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1604, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Thomas 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"url": "https://www.cg.tuwien.ac.at/research/publications/2018/koch_bernhard_2018-1/", "__class": "Publication" }, { "id": "Miao2018FDN", "type_id": "poster", "tu_id": null, "repositum_id": null, "title": "A Preview to Adenita: Visualization and Modeling of DNA Nanostructures", "date": "2018-06-08", "abstract": "We present Adenita, an open-source software that aims to provide an integrated in silico\ndesign toolkit for DNA Nanostructures. It facilitates the modular assembly of pre-existing\nand de novo designs, regardless of the used approach. Adenita is being developed in the\ncontext of the MARA project [1], a highly ambitious project aiming to produce a DNA\nnanorobot capable of targeted cell lyses. Currently, the existing design and visualization\ntools are insufficient to solve the specific challenges in our project. We aim to overcome\nthese limitations with Adenita, a new semi-automated approach that we are developing as\nthe MARA project advances. Adenita integrates visualizations [2] with user interactions and\nalgorithms in a semi-manual approach. At the core, we use a hierarchical data model that\nenables us to combine both a top-down (DAEDALUS [3]) and a bottom-up (caDNAno [4])\ndesign approach of the DNA Nanostructure. From the DNA data model, we create smooth\nvisualizations that depict the structure in multiple scales from its atomic details to a highlevel\ngeometric representation of the target shape. In addition, we employ different layouts\nfor the same structure [5]: 3D structural representations, 2D caDNAno-style diagrams, and\n1D display of the linear sequences. Creators enable the parametrized generation of\nstructural motifs, while Manipulators facilitate the advanced modifications of the structural\nproperties, such as connecting components and adding bridging strands. Analysis of the\ndesigns is still in a preliminary phase, but it already enables the straightforward estimation\nof distances and the melting temperatures [6] of binding regions. The first DNA\nnanostructures that we designed with the new tool are now under experimental evaluation.\n", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 857, "image_height": 1242, "name": "Miao2018FDN-image.png", "type": "image/png", "size": 1074408, "path": "Publication:Miao2018FDN", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/Miao2018FDN/Miao2018FDN-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/Miao2018FDN/Miao2018FDN-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1474, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Elisa", "lastname": "De Llano", "searchname": "Elisa De Llano", "is_teacher": false, "name": "Elisa De Llano", "publications": [ "miao_nantech_2019", "miao_nar_2020", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1474", "__class": "Author" }, { "id": 1263, "drupal_id": 863, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/HaichaoMiao", "firstname": "Haichao", "lastname": "Miao", "searchname": "Haichao Miao", "is_teacher": false, "name": "Haichao Miao", "publications": [ "gadllah_2016", "gall_2016", "Halladjian_2020", "Miao_2015_VCBM", "miao_2016_cgf", "Miao_2019", "Miao_Haichao_2015_VQC", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_plitvice_2018", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2017", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "Sarkis_2021", "Sbardellati-2019-vcbm", "wu-2019-report", "wu-2021", "wu-2021-vi" ], "publications_first": [], "project_leader": [], 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modern biological research domain experts have to deal with complex and large data collections and simulations. Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n", "website": "https://www.cg.tuwien.ac.at/research/area/BioVis", "teaser": { "name": "teaser.png", "path": "research_area:BioVis", "type": "image/png", "size": 16330957, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/BioVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "amirkhanov-2019-manylands", "byska-2019-mdfc", "cellVIEW_2015", "cmolik-2020-tvcg", "Dietrich_1", "dietrich-2016-viseq2", "Ehlers_PhD", "ehlers-2025-ait", "eschner-2023-ims", "eschner-blur-2022", "Escribano_2017", "Furmanova_2018", "Gehrer-2017", "Gehrer-2017-molmach", "glinzner-2016-tex", "Halladjian_2020", "kapferer-2017-godot", "klein_2017_IM", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koch-2018-sso", "Kolesar-Fractional-2016", "kolesar-ivan-2014-polymers", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kozlikova-Visualization-2016b", "Krone2016VABC", "Kugler_2019", "lemuzic_2015_timelapse", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lipp-2017-mgpu", "lipp-2017-vulkan", "Manczarski-2016", "manylands_award", "Miao_2019", "miao_inria_2017", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-xmas-card-2016", "Mitterhofer_2017", "nguyen_2020-covid", "Nowak_2020", "raidou_2019_springer", "raidou_shonan167", "raidou2018visualflatter", "rasch-2016-imgses", "Reisacher2016", "rinortner_susanne-2019-vpicc", "Sarkis_2021", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2013-neuromap", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "stappen_2017_animatedcomic", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "trautner-2018-imd", "unger-2019_vcp", "vad_2015_phd", "vad_viktor-2017-WVE", "vad-2016-bre", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "waldin-2019-ccm", "waldner-2014-af", "Weissenboeck_2019", "wu-2017-dagstuhl", "wu-2018-metabo", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg" ], "projects": [ "BioNetIllustration", "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=BioVis", "__class": "ResearchArea" }, { "id": "IllVis", "drupal_id": 4131, "name": "Illustrative Visualization", "short_abstract": "In this research area, we develop rendering methods that are inspired by scientific illustrations, in order to make complex biological information more intuitive to understand and more pleasant to read.", "abstract": "Scientific illustration is concerned with researching ways in which complex biological and medical data can be abstracted in order to convey a desired information that would otherwise be impossible or hard to retrieve from the original data. Illustrators apply such techniques, for instance, to present non-important parts of an organ in a simplified way, while using detailed representations to put the focus of attention on a region where a tumor might be situated.\n\nTo identify such meaningful visual abstractions for visualization, their effectiveness for human perception and cognition has to be assessed, and they have to be formalized in order to make them applicable in rendering algorithms. In this project, we try to advance the understanding of procedural visual abstraction of complex physiological processes that describe the complex machinery of biological life.", "website": "https://www.cg.tuwien.ac.at/research/area/IllVis", "teaser": { "name": "teaser.jpg", "path": "research_area:IllVis", "type": "image/jpeg", "size": 34861, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/IllVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "antes-2026-maa", "Antonini2020", "Balabanian-2010-IIV", "Balduz_01", "Bayat_2019", "Bechtold2020", "Birkeland-2012-IMC", "brandstaetter_01", "bruckner-2005-ICV", "bruckner-2006-ICE", "bruckner-2007-STF", "bruckner-2008-IIV", "bruckner-2010-HVC", "bruckner-2010-IFC", "cellVIEW_2015", "Chen-Information-2016", "Deutsch-2018", "Dhanoa_2021", "Dhanoa2024", "dietrich-2016-viseq2", "donabauer_2019_1", "eg-tut2005-iv", "eschner-2023-ims", "Essler2022", "gangl-2018-gpsart", "Gehrer_Daniel_CUI", "Gehrer-2017-molmach", "gerl-2006-vhi", "Gogel2020", "Groeller_2011_IPV", "Groeller_2016_I3", "Groeller_2016_I6", "Groeller_2016_I7", "Groeller_2016_I8", "Groeller_V1_2020", "groeller-2006-ivt", "groeller-2007-fci", "groeller-2008-irs", "Groeller-2010-IFI", "gruber-2025-vps", "Halladjian_2020", "haushofer-2018-skinning", "Heim_2020", "horvath-2018-ism", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "Knapp_2017_CVR", "Koeppel2020", "kolesar-ivan-2014-polymers", "Konev-FCV2018", "Koszticsak-2017-ewt", "Kouril_2017_11", "kouril-2020-hyperlabels", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "kroesl_x_card_2017", "Lackner_2022", "Langer_Edith_IR1", "lawonn-2018-illvisstar", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "LeMuzic_2016_PhD", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "Leutschacher_2022", "ludwig-2012-MT", "Manczarski-2016", "Matusich-2017-01", "Mautner 2020", "Mayr-2017-1", "Melo_2018_11", "Meusburger_2020", "Miao_2019", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao2018Dimsum", "Michl_2017_CSV", "mindek-2015-mc", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-2019-mci", "mindek-xmas-card-2016", "Moellinger_Christian_IDE2", "Niedermayer_2018", "Ortner_PhD", "Ortner2020", "pahr-2021-vologram", "Panayotov", "patel_daniel_2007_IRSD", "Pauschenwein_2022", "Peter_2012_AIV", "plank-2017-sldg", "prost-2016-molecule", "purgathofer-2008-cgi", "Radwan-2017-Occ", "Rautek-2007-SLI", "Rautek-2008-IDS", "Rautek-2008-VF", "Reichinger_2016", "Reichinger_Fuhrmann_2016", "Reisacher_Matthias_CPW", "Reisacher2016", "Riegelnegg_2019", "rippl-2023-atg", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "schindler_2020vis", "schmidlehner2021", "scholz_2021", "Schrempf_2020", "schultes_lampi", "seyfert-2017", "sikachev-2010-ill_vis_vol_ren", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "Spechtenhauser_Florian_2016", "stappen_2017_animatedcomic", "Stoll2020", "sturl_2016_dynlabels", "Swoboda2020", "szabo_patrik-2022-tour", "takahashi-2019-acdt", "Thomas-2018", "TR-186-2-07-08", "Troidl_2021", "Troidl_2022", "tut-eg-2006", "tut-siggraph-2006", "tut-vis-2006", "tut-vis-2007", "Unger2020", "Vasileva_2022", "Viola_Ivan_2013_SVA", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "viola-evr", "Viola-Pondering-2017", "Viola-vistutillustrativevis", "Waldin_Nicholas_2016_Colormaps", "waldin-2019-ccm", "Waldner_2017_11", "Wihann_2017", "Woschizka_2021", "wu-2019-bmc", "wu-2019-report", "Zaufel_2021", "zechmeister2020", "Zeng_2021", "Zusag-2017-Bach" ], "projects": [ "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=IllVis", "__class": "ResearchArea" }, { "id": "InfoVis", "drupal_id": 4128, "name": "Information Visualization and Visual Analytics", "short_abstract": "In this research area, our focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning. ", "abstract": "

Data and information created by various processes (e.g., simulations) is getting larger, and more and more complex. We use interactive visualization and analysis techniques to facilitate exploration of complex parameter spaces (e.g., to analyze and compare parameters for automotive engineering, reconstruction algorithms, or geometry generators) or unstructured information collections (e.g., annotated digital documents or image collections). Our research focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning.

\r\n", "website": "https://www.cg.tuwien.ac.at/research/area/InfoVis", "teaser": { "name": "teaser.png", "path": "research_area:InfoVis", "type": "image/png", "size": 60875, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/InfoVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "8564188", "arbesser_ba_2023", "Arleo-2019-vis", "Batik-2021", "batik-2021-gd", "bayat-2022-mva", "beham-2014-cupid", "bhore-2021-issac", "birsak-2014-agtb", "birsak-2017-dpe", "borgo-2013-gly", "borondy2022", "Braunsperger-2025_bsc", "Bruckner_Stefan_2015_VAS", "bugnar-esk-2021", "byska-2019-mdfc", "Cai_2018", "casellato-2016-pkg", "Chen-Information-2016", "cizmic-2018-evd", "cmolik-2020-tvcg", "Cornel_2020", "daae-lampe-2010-dif", "Deutsch-2018", "Diehl_2015", "Diehl_2021", "dworschak-2016-szcm", "Eckelt_2018_01", "edlinger-2018-vwr", "ehlers-2024-vgs", "eichner-2024-erv", "eitler-2024-sos", "eiweck-hnv-2021", "ellhotka-2025-ipo", "eschner-2023-evl", "eschner-2025-ide", "Escribano_2017", "fourousan2021", "furmanova_2020", "Gadllah_Hani_2016", "Gall2020", "Ganuza_ML_2015_ISA", "georgiev-2019-cbg", "geyer_lukas_2015_prj", "geymayer-2017-std", "Groeller_2011_CW", "Groeller_2011_NR", "Groeller_2014_RWA", "Groeller_2016_P1", "Groeller_2016_P2", "Groeller_2016_P4", "Groeller_2016_P6", "Groeller_2021-10", "Groeller_V2_2020", "Groeller_V3_2020", "Groeller_V5_2020", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", "gundacker-2020-wlm", "gusenbauer-2018", "gusenbauer-2018-P", "Heim_2021", "heim-2024-accustripes", "heim-gall-2020-dde", "Heinzl2021", "holzer-edo", "hromniak-2019-vcn", "huber-2025-eed", "Iijima-2020-iV", "indirectBiasLanguageModels-2023", "irendorfer-2024-uat", "karnik-09-shapegrammar", "Kehrer-2010-mom", "kehrer-2012-mod", "kehrer-2013-SBC", "Kehrer-2013-STAR", "klaffenboeck-2024-rva", "klaffenboeck-thesis", "Klein_Tobias_2015TIV", "klein-2016-WCL", "knoetzl_alexander-2025-prj", "koeppel-2021", "Kolter_2021", "komon-2025-webigeo", "komon-kimmersdorfer-2025-weBIGeo", "Konyha_2013_IVA", "korpitsch-2021-lov", "Kuroko-2020-iV", "Laschober-2018", "li-2019-gdc", "lippeck-2022-mna", "louis-alexandre_dit_petit-frere-2022-veo", "magg2022", "mahler-2021-mdar", "martorell2022", "maruyama-2019-iv", "Matkovic_Kresimir_2015_", "Matkovic-2014-ieee", "matt-2024-cvil", "matt-2025-scv", "mayr-2021-wec", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "medeiros-2023-gwf", "meka-2024-lpi", "melcher-2024-asi", "Miao_2015_VCBM", "miao_2016_cgf", "Miao_Haichao_2015_VQC", "miao2018Dimsum", "mizuno-2019-eurovis", "Muehlbacher_diss_2018", "musleh_maath_2021_mam", "musleh_maath-2021-mam1", "musleh_maath-2021-mam2", "Musleh_PhD", "musleh-2022-mam5", "musleh-2025-trustme", "Neubauer2020", "Nowak_2021", "ortner-2016-tunnel", "ortner-2016-visaware", "pahr-2024-ieo", "PH-2011-LDS", "Pilizar_-2020-bachelor", "pirch_2021_VRN", "pointner_simon-2020", "polatsek-2018-stv", "Presch_2020", "Priselac2021", "Purchase-2020-gd", "Purgathofer-2017-China1", "Purgathofer-2017-China2", "Purgathofer-2017-VC-Interface", "raidou_2019_pelvisrunner", "raidou_2019_preha", "raidou_2019_springer", "raidou_bestphd", "raidou_EuroVis15", "raidou_eurovis16", "raidou_miccai16", "raidou_pingu2020", "raidou_previs2021", "raidou_vcbm14", "raidou_vis14", "raidou_vis15", "raidou_visgap2020", "raidou2019_prsps", "Ribicic_2012_VAS", "Rippberger_2019", "rozana-2026-vcfd", "sakr_sherif-2020-cacm", "samoul-2019-cnp", "sbardellati-2021-eveos", "schmidt-phd", "sietzen-2019-wnn", "sietzen-2021-perturber", "sietzen-2022-vacnnr", "sietzen-ifv-2019", "sikachev_peter-2011-protovis", "smiech-2018-tei", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger-2013-neuromap", "sorger-2015-litevis", "sorger-2015-taxintec", "sorger-2017-thesis", "sorger-2019-odn", "sorger-2021-egonet", "spegel-gruenberger-2020", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "STEINLECHNER-2019-ICT", "steinschorn-2025-parameter", "stoff-2025-pvu", "stoff-concepMap-2021", "stritzel2022", "Strohmayer-2018-BT", "takahashi-2019-acdt", "tekaya-2025-amo", "Thomas-2018", "TR1862162", "Troidl_2019", "turner-aso", "unger-2019_vcp", "vad_viktor-2017-WVE", "vaico", "Vasileva-2018", "vasileva-2019-smw", "Wagner_032017", "wagner-2024-par", "walchhofer_ar_flowmaps", "waldin-2019-ccm", "waldner-2013-facetCloudsGI", "waldner-2013-ubiWM", "waldner-2014-ghi", "waldner-2017-vph", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "waser_2011_VSD", "webGPU_aggregateVis-2023", "wolf-2023-cc", "wolf-2024-jhd", "wu-2017-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-shonan", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-smwp", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-eurovis-star", "wu-2020-tvcg", "ymca", "YOGHOURDJIAN2019" ], "projects": [ "BioNetIllustration", "d10206", "d10413", "d10450", "d9282", "d9522", "d9555", "deskollage", "Scenario Pool" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=InfoVis", "__class": "ResearchArea" } ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "Image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 3302, "image_height": 1884, "name": "miao2018Dimsum-Image.png", "type": "image/png", "size": 2858278, "path": "Publication:miao2018Dimsum", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/miao2018Dimsum/miao2018Dimsum-Image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/miao2018Dimsum/miao2018Dimsum-Image:thumb{{size}}.png" }, { "description": null, "filetitle": "Paper", "main_file": true, "use_in_gallery": true, "access": "public", "preview_image_width": 3302, "preview_image_height": 1884, "name": "miao2018Dimsum-Paper.pdf", "type": 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"video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2018/miao2018Dimsum/miao2018Dimsum-Recording:video.mp4" }, { "description": null, "filetitle": "Video", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 3302, "preview_image_height": 1884, "name": "miao2018Dimsum-Video.mp4", "type": "video/mp4", "size": 97832153, "path": "Publication:miao2018Dimsum", "preview_name": "miao2018Dimsum-Video:preview.png", "preview_type": "image/png", "preview_size": 2858278, "url": "https://www.cg.tuwien.ac.at/research/publications/2018/miao2018Dimsum/miao2018Dimsum-Video.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/miao2018Dimsum/miao2018Dimsum-Video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2018/miao2018Dimsum/miao2018Dimsum-Video:video.mp4" } ], "projects_workgroups": [ { "id": "Illustrare", "workgroup_id": "vis", "drupal_id": 4189, "drupal_path": "/research/projects/Illustrare", "name": "ILLUSTRARE: Integrative Visual Abstraction of Molecular Data", "name_de": null, "short_title": "Illustrare", "website": null, "status": "active", "short_abstract": "FWF - I 2953-N31\nIntegrative Visual Abstraction of Molecular Data", "abstract": "In many aspects of our modern lives we face the problem of having to make sense of large amounts of data. This applies to scientists trying to make sense of their experiments and simulations, to bankers and traders trying to understand the dynamics of the financial markets, and to large enterprises which need to understand the principles behind demand and supply—to name just a few examples. The basic problem in all these cases is that people need to identify important and/or unexpected features in large simulated or captured datasets. Visualization is the domain that facilitates this process of sense-making by dramatically simplifying the process of obtaining an understanding of the data—by representing data visually and thus amplifying people’s cognition. This inherent capability of (good) visualization techniques to amplify human cognition, however, is no longer enough to be able to make sense of today’s huge datasets. To be able to see the essential aspects we need dedicated mechanisms that abstract away the (unnecessary) detail to, in turn, allow the user of the visualization to focus on the important elements. The crucial problem in this context is that it is impossible to know what is important and what is not in a general way—importance changes based on the research question, on the application domain, on the data size, on the user, on the specific situation, etc. Visualization technology therefore needs to support dynamic change of visual abstraction of the data to reflect these contextual changes. The fundamental research challenge in visualization for us is to get an understanding of what (visual) abstraction really is, what it means, how it can be controlled, and how it is, can be, and should be used in visualization.\n", "start_date": "2017-01-01", "end_date": "2019-12-31", "leader_id": 171, "logo": { "name": "logo.jpg", "path": "project:Illustrare", "type": "image/jpeg", "size": 95116, "orig_name": "logo.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/Illustrare/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "I 2953-N31", "comment": null } ], "research_areas": [ "BioVis", "IllVis" ], "publications": [ "Halladjian_2020", "kouril-2018-LoL", "lawonn-2018-illvisstar", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "Viola-Pondering-2017" ], "url": "https://www.cg.tuwien.ac.at/research/projects/Illustrare", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/miao2018Dimsum/", "__class": "Publication" }, { "id": "wu-2018-metabo", "type_id": "poster", "tu_id": null, "repositum_id": null, "title": "A Visual Comparison of Hand-Drawn and Machine-Generated Human Metabolic Pathways", "date": "2018-06", "abstract": "This poster abstract presents a visual comparison between three hand-drawn and one machine-generated human metabolic pathway diagrams. The human metabolic pathways, which describe significant biochemical reactions in the human body, have been increasingly investigated due to the development of analysis processes and are compiled into pathway diagrams to provide an overview of reaction in the human body. This complex network includes about 5,000 metabolites and 7,500 reactions, which are hierarchically nested and difficult to visualize. We collect and analyze well-known human metabolic pathway diagrams, and summarize the design choices of these diagrams, respectively. Together with a machine-generated diagram, we can understand the visual complexity of three hand-drawn and one machine-generated diagrams.\n", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 566, "image_height": 800, "name": "wu-2018-metabo-image.png", "type": "image/png", "size": 677575, "path": "Publication:wu-2018-metabo", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-metabo/wu-2018-metabo-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-metabo/wu-2018-metabo-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1464, "drupal_id": 1266, "orcid_id": "0000-0003-1028-0010", "website": "https://www.cg.tuwien.ac.at/staff/Hsiang-YunWu", "firstname": "Hsiang-Yun", "lastname": 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"vad_2015_phd", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Viola_Ivan_2013_HQ3", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Viola-05-Smart", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "viola-2007-ort", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Viola-Pondering-2017", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "vis-foa", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldin-2017-thesis", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Wihann_2017", "field_id": "supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=171", "__class": "Author" } ], "cfp": { "name": "eurovis2018-poster.pdf", "type": "application/pdf", "error": "0", "size": "35735", "orig_name": "eurovis2018-poster.pdf", "ext": "pdf" }, "date_from": "2018-06-04", "date_to": "2018-06-08", "event": "EuroVis", "research_areas": [ { "id": "BioVis", "drupal_id": 4127, "name": "Biological Data Visualization", "short_abstract": "In this research area, we develop new visualization techniques to support biologists in data analysis and create visualizations to disseminate scientific discoveries in biology.", "abstract": "In modern biological research domain experts have to deal with complex and large data collections and simulations. Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n", "website": "https://www.cg.tuwien.ac.at/research/area/BioVis", "teaser": { "name": "teaser.png", "path": "research_area:BioVis", "type": "image/png", "size": 16330957, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/BioVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "amirkhanov-2019-manylands", "byska-2019-mdfc", "cellVIEW_2015", "cmolik-2020-tvcg", "Dietrich_1", "dietrich-2016-viseq2", "Ehlers_PhD", "ehlers-2025-ait", "eschner-2023-ims", "eschner-blur-2022", "Escribano_2017", "Furmanova_2018", "Gehrer-2017", "Gehrer-2017-molmach", "glinzner-2016-tex", "Halladjian_2020", "kapferer-2017-godot", "klein_2017_IM", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koch-2018-sso", "Kolesar-Fractional-2016", "kolesar-ivan-2014-polymers", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kozlikova-Visualization-2016b", "Krone2016VABC", "Kugler_2019", "lemuzic_2015_timelapse", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lipp-2017-mgpu", "lipp-2017-vulkan", "Manczarski-2016", "manylands_award", "Miao_2019", "miao_inria_2017", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-xmas-card-2016", "Mitterhofer_2017", "nguyen_2020-covid", "Nowak_2020", "raidou_2019_springer", "raidou_shonan167", "raidou2018visualflatter", "rasch-2016-imgses", "Reisacher2016", "rinortner_susanne-2019-vpicc", "Sarkis_2021", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2013-neuromap", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "stappen_2017_animatedcomic", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "trautner-2018-imd", "unger-2019_vcp", "vad_2015_phd", "vad_viktor-2017-WVE", "vad-2016-bre", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "waldin-2019-ccm", "waldner-2014-af", "Weissenboeck_2019", "wu-2017-dagstuhl", "wu-2018-metabo", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg" ], "projects": [ "BioNetIllustration", "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=BioVis", "__class": "ResearchArea" }, { "id": "InfoVis", "drupal_id": 4128, "name": "Information Visualization and Visual Analytics", "short_abstract": "In this research area, our focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning. ", "abstract": "

Data and information created by various processes (e.g., simulations) is getting larger, and more and more complex. We use interactive visualization and analysis techniques to facilitate exploration of complex parameter spaces (e.g., to analyze and compare parameters for automotive engineering, reconstruction algorithms, or geometry generators) or unstructured information collections (e.g., annotated digital documents or image collections). Our research focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning.

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"d9522", "d9555", "deskollage", "Scenario Pool" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=InfoVis", "__class": "ResearchArea" } ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 566, "image_height": 800, "name": "wu-2018-metabo-image.png", "type": "image/png", "size": 677575, "path": "Publication:wu-2018-metabo", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-metabo/wu-2018-metabo-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-metabo/wu-2018-metabo-image:thumb{{size}}.png" }, { "description": null, "filetitle": "poster", "main_file": true, "use_in_gallery": false, "access": "public", "name": "wu-2018-metabo-poster.pdf", "type": "application/pdf", "size": 85587001, "path": "Publication:wu-2018-metabo", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-metabo/wu-2018-metabo-poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-metabo/wu-2018-metabo-poster:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "BioNetIllustration", "workgroup_id": "vis", "drupal_id": 4196, "drupal_path": "/research/projects/BioNetIllustration", "name": "BioNetIllustration: User Centric Illustrations of Biological Networks", "name_de": null, "short_title": "BioNetIllustration", "website": null, "status": "active", "short_abstract": "

In living systems, one molecule is commonly involved in several distinct physiological functions. The roles of molecules are commonly summarized in pathway diagrams, which, however, are abstract, hierarchically nested and thus is difficult to comprehend especially by non-expert audience. The primary goal of this research in visualization is to intuitively support the comprehensive understanding of relationships among biological networks using interactively computed illustrations. Illustrations, especially in textbooks of biology are carefully designed to clearly present reactions between organs as well as interactions within cells. Automatic generation of illustrative visualizations of biological networks is thus the technical content of this proposal. Automatic generation of hand-drawn illustrations has been a challenging task due to the difficulty of algorithmically describing a human creative process such as evaluating and selecting significant information and composing meaningful explanations in a visually plausible manner. The project also involves experts from several disciplines including network and medical visualization, data mining, systems biology as well as perceptual psychology. The result will provide a new direction for physiological process analysis and accelerate the knowledge transfer not only within experts but also to the public. Acknowledgment: The project has received funding from the European Union Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 747985.

\r\n", "abstract": "

In living systems, one molecule is commonly involved in several distinct physiological functions. The roles of molecules are commonly summarized in pathway diagrams, which, however, are abstract, hierarchically nested and thus is difficult to comprehend especially by non-expert audience. The primary goal of this research in visualization is to intuitively support the comprehensive understanding of relationships among biological networks using interactively computed illustrations. Illustrations, especially in textbooks of biology are carefully designed to clearly present reactions between organs as well as interactions within cells. Automatic generation of illustrative visualizations of biological networks is thus the technical content of this proposal. Automatic generation of hand-drawn illustrations has been a challenging task due to the difficulty of algorithmically describing a human creative process such as evaluating and selecting significant information and composing meaningful explanations in a visually plausible manner. The project also involves experts from several disciplines including network and medical visualization, data mining, systems biology as well as perceptual psychology. The result will provide a new direction for physiological process analysis and accelerate the knowledge transfer not only within experts but also to the public. Acknowledgment: The project has received funding from the European Union Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 747985.

\r\n", "start_date": "2017-06-21", "end_date": "2019-06-20", "leader_id": 1464, "logo": { "name": "logo.png", "path": "project:BioNetIllustration", "type": "image/png", "size": 16337, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/BioNetIllustration/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "Horizon 2020", "contract_number": "747985", "comment": null } ], "research_areas": [ "BioVis", "InfoVis" ], "publications": [ "cmolik-2020-tvcg", "kouril-2018-LoL", "mizuno-2019-eurovis", "Purchase-2020-gd", "rinortner_susanne-2019-vpicc", "Sbardellati-2019-vcbm", "wu-2017-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-shonan", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg", "YOGHOURDJIAN2019" ], "url": "https://www.cg.tuwien.ac.at/research/projects/BioNetIllustration", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-metabo/", "__class": "Publication" }, { "id": "Furmanova_2018", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": null, "title": "COZOID: contact zone identifier for visual analysis of protein-protein interactions", "date": "2018-04", "abstract": "Background: Studying the patterns of protein-protein interactions (PPIs) is fundamental for understanding thestructure and function of protein complexes. The exploration of the vast space of possible mutual configurations ofinteracting proteins and their contact zones is very time consuming and requires the proteomic expert knowledge.Results:In this paper, we propose a novel tool containing a set of visual abstraction techniques for the guidedexploration of PPI configuration space. It helps proteomic experts to select the most relevant configurations andexplore their contact zones at different levels of detail. The system integrates a set of methods that follow and supportthe workflow of proteomics experts. The first visual abstraction method, the Matrix view, is based on customizedinteractive heat maps and provides the users with an overview of all possible residue-residue contacts in all PPIconfigurations and their interactive filtering. In this step, the user can traverse all input PPI configurations and obtain anoverview of their interacting amino acids. Then, the models containing a particular pair of interacting amino acids canbe selectively picked and traversed. Detailed information on the individual amino acids in the contact zones and theirproperties is presented in the Contact-Zone list-view. The list-view provides a comparative tool to rank the best modelsbased on the similarity of their contacts to the template-structure contacts. All these techniques are interactivelylinked with other proposed methods, the Exploded view and the Open-Book view, which represent individualconfigurations in three-dimensional space. These representations solve the high overlap problem associated withmany configurations. Using these views, the structural alignment of the best models can also be visually confirmed.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 223, "image_height": 172, "name": "Furmanova_2018-image.JPG", "type": "image/jpeg", "size": 15338, "path": "Publication:Furmanova_2018", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/Furmanova_2018/Furmanova_2018-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/Furmanova_2018/Furmanova_2018-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1733, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Katarína ", "lastname": "Furmanová", "searchname": "Katarína Furmanová", "is_teacher": false, "name": "Katarína Furmanová", 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Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. 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Although several pathway layout algorithms have been investigated, biologists still prefer to use hand-drawn ones, due to their high visual quality relied on domain knowledge. In this project, we propose a visualization for computing metabolic pathway maps that restrict the grouping structure defined by biologists to rectangles and apply orthogonal-style edge routing to simplify edge orientation. This idea is inspired by concepts from urban planning, where we consider reactions as city blocks and built up roads to connect identical metabolites occurred in multiple categories. We provide a story to present how glucose is broken down to phosphoenolpyruvate to release energy, which is often stored in adenosine triphosphate (ATP) in a human body. 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to disseminate scientific discoveries in biology.", "abstract": "In modern biological research domain experts have to deal with complex and large data collections and simulations. Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n", "website": "https://www.cg.tuwien.ac.at/research/area/BioVis", "teaser": { "name": "teaser.png", "path": "research_area:BioVis", "type": "image/png", "size": 16330957, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/BioVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "amirkhanov-2019-manylands", "byska-2019-mdfc", "cellVIEW_2015", "cmolik-2020-tvcg", "Dietrich_1", "dietrich-2016-viseq2", "Ehlers_PhD", "ehlers-2025-ait", "eschner-2023-ims", "eschner-blur-2022", "Escribano_2017", "Furmanova_2018", "Gehrer-2017", "Gehrer-2017-molmach", "glinzner-2016-tex", "Halladjian_2020", "kapferer-2017-godot", "klein_2017_IM", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koch-2018-sso", "Kolesar-Fractional-2016", "kolesar-ivan-2014-polymers", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kozlikova-Visualization-2016b", "Krone2016VABC", "Kugler_2019", "lemuzic_2015_timelapse", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lipp-2017-mgpu", "lipp-2017-vulkan", "Manczarski-2016", "manylands_award", "Miao_2019", "miao_inria_2017", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-xmas-card-2016", "Mitterhofer_2017", "nguyen_2020-covid", "Nowak_2020", "raidou_2019_springer", "raidou_shonan167", "raidou2018visualflatter", "rasch-2016-imgses", "Reisacher2016", "rinortner_susanne-2019-vpicc", "Sarkis_2021", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2013-neuromap", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "stappen_2017_animatedcomic", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "trautner-2018-imd", "unger-2019_vcp", "vad_2015_phd", "vad_viktor-2017-WVE", "vad-2016-bre", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "waldin-2019-ccm", "waldner-2014-af", "Weissenboeck_2019", "wu-2017-dagstuhl", "wu-2018-metabo", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg" ], "projects": [ "BioNetIllustration", "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=BioVis", "__class": "ResearchArea" }, { "id": "InfoVis", "drupal_id": 4128, "name": "Information Visualization and Visual Analytics", "short_abstract": "In this research area, our focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning. ", "abstract": "

Data and information created by various processes (e.g., simulations) is getting larger, and more and more complex. We use interactive visualization and analysis techniques to facilitate exploration of complex parameter spaces (e.g., to analyze and compare parameters for automotive engineering, reconstruction algorithms, or geometry generators) or unstructured information collections (e.g., annotated digital documents or image collections). Our research focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning.

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"eiweck-hnv-2021", "ellhotka-2025-ipo", "eschner-2023-evl", "eschner-2025-ide", "Escribano_2017", "fourousan2021", "furmanova_2020", "Gadllah_Hani_2016", "Gall2020", "Ganuza_ML_2015_ISA", "georgiev-2019-cbg", "geyer_lukas_2015_prj", "geymayer-2017-std", "Groeller_2011_CW", "Groeller_2011_NR", "Groeller_2014_RWA", "Groeller_2016_P1", "Groeller_2016_P2", "Groeller_2016_P4", "Groeller_2016_P6", "Groeller_2021-10", "Groeller_V2_2020", "Groeller_V3_2020", "Groeller_V5_2020", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", "gundacker-2020-wlm", "gusenbauer-2018", "gusenbauer-2018-P", "Heim_2021", "heim-2024-accustripes", "heim-gall-2020-dde", "Heinzl2021", "holzer-edo", "hromniak-2019-vcn", "huber-2025-eed", "Iijima-2020-iV", "indirectBiasLanguageModels-2023", "irendorfer-2024-uat", "karnik-09-shapegrammar", "Kehrer-2010-mom", "kehrer-2012-mod", "kehrer-2013-SBC", "Kehrer-2013-STAR", "klaffenboeck-2024-rva", "klaffenboeck-thesis", "Klein_Tobias_2015TIV", "klein-2016-WCL", "knoetzl_alexander-2025-prj", "koeppel-2021", "Kolter_2021", "komon-2025-webigeo", "komon-kimmersdorfer-2025-weBIGeo", "Konyha_2013_IVA", "korpitsch-2021-lov", "Kuroko-2020-iV", "Laschober-2018", "li-2019-gdc", "lippeck-2022-mna", "louis-alexandre_dit_petit-frere-2022-veo", "magg2022", "mahler-2021-mdar", "martorell2022", "maruyama-2019-iv", "Matkovic_Kresimir_2015_", "Matkovic-2014-ieee", "matt-2024-cvil", "matt-2025-scv", "mayr-2021-wec", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "medeiros-2023-gwf", "meka-2024-lpi", "melcher-2024-asi", "Miao_2015_VCBM", "miao_2016_cgf", "Miao_Haichao_2015_VQC", "miao2018Dimsum", "mizuno-2019-eurovis", "Muehlbacher_diss_2018", "musleh_maath_2021_mam", "musleh_maath-2021-mam1", "musleh_maath-2021-mam2", "Musleh_PhD", "musleh-2022-mam5", "musleh-2025-trustme", "Neubauer2020", "Nowak_2021", "ortner-2016-tunnel", "ortner-2016-visaware", "pahr-2024-ieo", "PH-2011-LDS", "Pilizar_-2020-bachelor", "pirch_2021_VRN", 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"steinboeck-2018-lbg", "STEINLECHNER-2019-ICT", "steinschorn-2025-parameter", "stoff-2025-pvu", "stoff-concepMap-2021", "stritzel2022", "Strohmayer-2018-BT", "takahashi-2019-acdt", "tekaya-2025-amo", "Thomas-2018", "TR1862162", "Troidl_2019", "turner-aso", "unger-2019_vcp", "vad_viktor-2017-WVE", "vaico", "Vasileva-2018", "vasileva-2019-smw", "Wagner_032017", "wagner-2024-par", "walchhofer_ar_flowmaps", "waldin-2019-ccm", "waldner-2013-facetCloudsGI", "waldner-2013-ubiWM", "waldner-2014-ghi", "waldner-2017-vph", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "waser_2011_VSD", "webGPU_aggregateVis-2023", "wolf-2023-cc", "wolf-2024-jhd", "wu-2017-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-shonan", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-smwp", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-eurovis-star", "wu-2020-tvcg", "ymca", "YOGHOURDJIAN2019" ], "projects": [ "BioNetIllustration", "d10206", "d10413", "d10450", "d9282", "d9522", "d9555", "deskollage", "Scenario Pool" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=InfoVis", "__class": "ResearchArea" } ], "keywords": [], "weblinks": [ { "href": "https://vimeo.com/258174044", "caption": null, "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "wu-2018-story-image.png", "type": "image/png", "size": 91891, "path": "Publication:wu-2018-story", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-story/wu-2018-story-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-story/wu-2018-story-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": 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"https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-story/wu-2018-story-video:video.mp4" } ], "projects_workgroups": [ { "id": "BioNetIllustration", "workgroup_id": "vis", "drupal_id": 4196, "drupal_path": "/research/projects/BioNetIllustration", "name": "BioNetIllustration: User Centric Illustrations of Biological Networks", "name_de": null, "short_title": "BioNetIllustration", "website": null, "status": "active", "short_abstract": "

In living systems, one molecule is commonly involved in several distinct physiological functions. The roles of molecules are commonly summarized in pathway diagrams, which, however, are abstract, hierarchically nested and thus is difficult to comprehend especially by non-expert audience. The primary goal of this research in visualization is to intuitively support the comprehensive understanding of relationships among biological networks using interactively computed illustrations. Illustrations, especially in textbooks of biology are carefully designed to clearly present reactions between organs as well as interactions within cells. Automatic generation of illustrative visualizations of biological networks is thus the technical content of this proposal. Automatic generation of hand-drawn illustrations has been a challenging task due to the difficulty of algorithmically describing a human creative process such as evaluating and selecting significant information and composing meaningful explanations in a visually plausible manner. The project also involves experts from several disciplines including network and medical visualization, data mining, systems biology as well as perceptual psychology. The result will provide a new direction for physiological process analysis and accelerate the knowledge transfer not only within experts but also to the public. Acknowledgment: The project has received funding from the European Union Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 747985.

\r\n", "abstract": "

In living systems, one molecule is commonly involved in several distinct physiological functions. The roles of molecules are commonly summarized in pathway diagrams, which, however, are abstract, hierarchically nested and thus is difficult to comprehend especially by non-expert audience. The primary goal of this research in visualization is to intuitively support the comprehensive understanding of relationships among biological networks using interactively computed illustrations. Illustrations, especially in textbooks of biology are carefully designed to clearly present reactions between organs as well as interactions within cells. Automatic generation of illustrative visualizations of biological networks is thus the technical content of this proposal. Automatic generation of hand-drawn illustrations has been a challenging task due to the difficulty of algorithmically describing a human creative process such as evaluating and selecting significant information and composing meaningful explanations in a visually plausible manner. The project also involves experts from several disciplines including network and medical visualization, data mining, systems biology as well as perceptual psychology. The result will provide a new direction for physiological process analysis and accelerate the knowledge transfer not only within experts but also to the public. Acknowledgment: The project has received funding from the European Union Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 747985.

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The way users observe a visualization is affected by salient stimuli in a scene as well as by domain knowledge, interest, and the task. While recent saliency models manage to predict the users’ visual attention in visualizations during exploratory analysis, there is little evidence how much influence bottom-up saliency has on task-based visual analysis. Therefore, we performed an eye-tracking study with 47 users to determine the users’ path of attention when solving three low-level analytical tasks using 30 different charts from the MASSVIS database [1]. We also compared our task-based eye tracking data to the data from the original memorability experiment by Borkin et al. [2]. We found that solving a task leads to more consistent viewing patterns compared to exploratory visual analysis. However, bottom-up saliency of a visualization has negligible influence on users’ fixations and task efficiency when performing a low-level analytical task. Also, the efficiency of visual search for an extreme target data point is barely influenced by the target’s bottom-up saliency. Therefore, we conclude that bottom-up saliency models tailored towards information visualization are not suitable for predicting visual attention when performing task-based visual analysis. 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", "abstract": "

Data and information created by various processes (e.g., simulations) is getting larger, and more and more complex. We use interactive visualization and analysis techniques to facilitate exploration of complex parameter spaces (e.g., to analyze and compare parameters for automotive engineering, reconstruction algorithms, or geometry generators) or unstructured information collections (e.g., annotated digital documents or image collections). Our research focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning.

\r\n", "website": "https://www.cg.tuwien.ac.at/research/area/InfoVis", "teaser": { "name": "teaser.png", "path": "research_area:InfoVis", "type": "image/png", "size": 60875, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/InfoVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "8564188", "arbesser_ba_2023", "Arleo-2019-vis", "Batik-2021", "batik-2021-gd", "bayat-2022-mva", "beham-2014-cupid", "bhore-2021-issac", "birsak-2014-agtb", "birsak-2017-dpe", "borgo-2013-gly", "borondy2022", "Braunsperger-2025_bsc", "Bruckner_Stefan_2015_VAS", "bugnar-esk-2021", "byska-2019-mdfc", "Cai_2018", "casellato-2016-pkg", "Chen-Information-2016", "cizmic-2018-evd", "cmolik-2020-tvcg", "Cornel_2020", "daae-lampe-2010-dif", "Deutsch-2018", "Diehl_2015", "Diehl_2021", "dworschak-2016-szcm", "Eckelt_2018_01", "edlinger-2018-vwr", "ehlers-2024-vgs", "eichner-2024-erv", "eitler-2024-sos", "eiweck-hnv-2021", "ellhotka-2025-ipo", "eschner-2023-evl", "eschner-2025-ide", "Escribano_2017", "fourousan2021", "furmanova_2020", "Gadllah_Hani_2016", "Gall2020", "Ganuza_ML_2015_ISA", "georgiev-2019-cbg", "geyer_lukas_2015_prj", "geymayer-2017-std", "Groeller_2011_CW", "Groeller_2011_NR", "Groeller_2014_RWA", "Groeller_2016_P1", "Groeller_2016_P2", "Groeller_2016_P4", "Groeller_2016_P6", "Groeller_2021-10", "Groeller_V2_2020", "Groeller_V3_2020", "Groeller_V5_2020", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", "gundacker-2020-wlm", "gusenbauer-2018", "gusenbauer-2018-P", "Heim_2021", "heim-2024-accustripes", "heim-gall-2020-dde", "Heinzl2021", "holzer-edo", "hromniak-2019-vcn", "huber-2025-eed", "Iijima-2020-iV", "indirectBiasLanguageModels-2023", "irendorfer-2024-uat", "karnik-09-shapegrammar", "Kehrer-2010-mom", "kehrer-2012-mod", "kehrer-2013-SBC", "Kehrer-2013-STAR", "klaffenboeck-2024-rva", "klaffenboeck-thesis", "Klein_Tobias_2015TIV", "klein-2016-WCL", "knoetzl_alexander-2025-prj", "koeppel-2021", "Kolter_2021", "komon-2025-webigeo", "komon-kimmersdorfer-2025-weBIGeo", "Konyha_2013_IVA", "korpitsch-2021-lov", "Kuroko-2020-iV", "Laschober-2018", "li-2019-gdc", "lippeck-2022-mna", "louis-alexandre_dit_petit-frere-2022-veo", "magg2022", "mahler-2021-mdar", "martorell2022", "maruyama-2019-iv", "Matkovic_Kresimir_2015_", "Matkovic-2014-ieee", "matt-2024-cvil", "matt-2025-scv", "mayr-2021-wec", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "medeiros-2023-gwf", "meka-2024-lpi", "melcher-2024-asi", "Miao_2015_VCBM", "miao_2016_cgf", "Miao_Haichao_2015_VQC", "miao2018Dimsum", "mizuno-2019-eurovis", "Muehlbacher_diss_2018", "musleh_maath_2021_mam", "musleh_maath-2021-mam1", "musleh_maath-2021-mam2", "Musleh_PhD", "musleh-2022-mam5", "musleh-2025-trustme", "Neubauer2020", "Nowak_2021", "ortner-2016-tunnel", "ortner-2016-visaware", "pahr-2024-ieo", "PH-2011-LDS", "Pilizar_-2020-bachelor", "pirch_2021_VRN", "pointner_simon-2020", "polatsek-2018-stv", "Presch_2020", "Priselac2021", "Purchase-2020-gd", "Purgathofer-2017-China1", "Purgathofer-2017-China2", "Purgathofer-2017-VC-Interface", "raidou_2019_pelvisrunner", "raidou_2019_preha", "raidou_2019_springer", "raidou_bestphd", "raidou_EuroVis15", "raidou_eurovis16", "raidou_miccai16", "raidou_pingu2020", "raidou_previs2021", "raidou_vcbm14", "raidou_vis14", "raidou_vis15", "raidou_visgap2020", "raidou2019_prsps", "Ribicic_2012_VAS", "Rippberger_2019", "rozana-2026-vcfd", "sakr_sherif-2020-cacm", "samoul-2019-cnp", "sbardellati-2021-eveos", "schmidt-phd", "sietzen-2019-wnn", "sietzen-2021-perturber", "sietzen-2022-vacnnr", "sietzen-ifv-2019", "sikachev_peter-2011-protovis", "smiech-2018-tei", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger-2013-neuromap", "sorger-2015-litevis", "sorger-2015-taxintec", "sorger-2017-thesis", "sorger-2019-odn", "sorger-2021-egonet", "spegel-gruenberger-2020", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "STEINLECHNER-2019-ICT", "steinschorn-2025-parameter", "stoff-2025-pvu", "stoff-concepMap-2021", "stritzel2022", "Strohmayer-2018-BT", "takahashi-2019-acdt", "tekaya-2025-amo", "Thomas-2018", "TR1862162", "Troidl_2019", "turner-aso", "unger-2019_vcp", "vad_viktor-2017-WVE", "vaico", "Vasileva-2018", "vasileva-2019-smw", "Wagner_032017", "wagner-2024-par", "walchhofer_ar_flowmaps", "waldin-2019-ccm", "waldner-2013-facetCloudsGI", "waldner-2013-ubiWM", "waldner-2014-ghi", "waldner-2017-vph", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "waser_2011_VSD", "webGPU_aggregateVis-2023", "wolf-2023-cc", "wolf-2024-jhd", "wu-2017-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-shonan", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-smwp", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-eurovis-star", "wu-2020-tvcg", "ymca", "YOGHOURDJIAN2019" ], "projects": [ "BioNetIllustration", "d10206", "d10413", "d10450", "d9282", "d9522", "d9555", "deskollage", "Scenario Pool" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=InfoVis", "__class": "ResearchArea" }, { "id": "Perception", "drupal_id": 4136, "name": "Perception", "short_abstract": "In this area, our research focuses on understanding and using the capabilities of human perception for designing high-quality graphics algorithms and effective visualizations.", "abstract": "

In computer graphics we produce images, videos, visualizations and other content that is perceived by humans. By understanding the limits of human perception, we can design and optimize rendering algorithms that perfectly fit users' needs, tailor visualizations to make data better understandable, and effectively draw the user's attention to important information.

\r\n", "website": "https://www.cg.tuwien.ac.at/research/area/Perception", "teaser": { "name": "teaser.PNG", "path": "research_area:Perception", "type": "image/png", "size": 259428, "orig_name": "teaser.PNG", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Perception/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend", "vis" ], "publications": [ "antes-2026-maa", "bernhard-2011-maicg", "bernhard-2014-EFD", "bernhard-2014-GTOM", "bernhard-2016-gft", "birkeland_aasmund_2014_pums", "cardoso-2022-rtpercept", "cardoso-thesis", "ERLER-2017-HVR", "eschner-2023-ims", "eschner-blur-2022", "georgiev-2019-cbg", "Groeller_2016_P7", "grossmann-2021-layout", "hecher-2012-MH", "hecher-2014-MH", "HECHER-2017-HDY", "huerbe-2019-BA", "Kathi-2018-VRB", "koch-2019-PR", "Koszticsak-2017-ewt", "kraehsmaier-dsc", "KREUZER-2017-PBF", "kristmann-2022-occ", "kroesl-2018-DC", "kroesl-2018-TVS", "kroesl-2019-ICthroughVR", "kroesl-2019-ThesisFF", "kroesl-2020-XREye", "Laschober-2018", "Luidolt-2020-DA", "luidolt-2020-lightperceptionVR", "mayr-2021-wec", "mindek-2017-dsn", "pahr-2024-ieo", "panfili-2019-VAVR", "panfili-2021-myop", "plank-2017-sldg", "polatsek-2018-stv", "Reichinger-2016-spaghetti", "schindler_2020vis", "schuller_reichl-2019-avt", "Semmelrath-2022-IRS", "stappen_SteFAS", "steinkellner-2022-dll", "sundstedt-2013-vag", "thesis-kronsteiner", "trautner-2018-imd", "Vasylevska_Khrystyna-2019-TEFVR", "viola-evr", "Waldin_Nicholas_2016_Colormaps", "Waldin_Nicholas_2016_Individualization", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2017-thesis", "waldner-2013-facetCloudsGI", "waldner-2014-af", "waldner-2017-vph", "waldner-2019-rld" ], "projects": [ "CROSSMOD" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Perception", "__class": "ResearchArea" } ], "keywords": [ "Information visualization", "Eye-tracking experiment", "Saliency", "Visual attention", "Low-level analytical tasks" ], "weblinks": [ { "href": "https://www.sciencedirect.com/science/article/pii/S0097849318300104", "caption": null, "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "graphical abstract", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 591, "image_height": 584, "name": "polatsek-2018-stv-graphical abstract.png", "type": "image/png", "size": 193042, "path": "Publication:polatsek-2018-stv", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/polatsek-2018-stv/polatsek-2018-stv-graphical abstract.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/polatsek-2018-stv/polatsek-2018-stv-graphical abstract:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "polatsek-2018-stv-paper.pdf", "type": "application/pdf", "size": 3228380, "path": "Publication:polatsek-2018-stv", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/polatsek-2018-stv/polatsek-2018-stv-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/polatsek-2018-stv/polatsek-2018-stv-paper:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "vis", "drupal_id": 1354, "name": "Visualization Group", "website": "https://www.cg.tuwien.ac.at/group/Visualization-Group", "projects": [ "ADAPT", "AngioVis", "Animated Cell Tab development", "AutARG", "avr", "BioNetIllustration", "COMRADE", "d10027", "d10162", "d10164", "d10206", "d10214", "d10413", "d10450", "d10489", "d4328", "d4335", "d4534", "d9275", "d9282", "d9522", "d9555", "d9671", "d9951", "deskollage", "diagvis", "exvisation", "Illustrare", "illvisation", "KASI", "ManyViews", "NeuroViewer", "ProcessIllVis", "ProKeyAnim", "PVG", "Scale-VS", "Scenario Pool", "Semantic Steering", "Sim-CT", "Smart-CT", "Smile Analytics", "ViMaL", "VISAR" ], "research_areas": [ "BioVis", "IllVis", "InfoVis", "MedVis", "NetVis", "Perception", "VisMat", "VR" ], "publications": [ "2013_Viola_Ivan_2013_MTS", "2015-image-coll", "2017-kouril-illcell", "2019-ic", "AA2020", "aigner-2025-vhv", "alacruzECR2004", "alacruzVisSym2004", "Alharbi_2021", "Alsallakh_2012_RCW", "alsallakh-2009-iva", "altendorfer-2008-vts", "amabili2021", "amirkhanov_2012", "amirkhanov_2012heur", "amirkhanov-2011", "amirkhanov-2014-ama", "amirkhanov-2018-withteeth", "amirkhanov-2021-diss", "amirkhanov2010AMA", "ammer-2008-lst", "An-2018-CHI", "AndreUrsits_2013_APP", "antes-2023-vhv", "Antonini2020", "arbesser_ba_2023", "Artner-2004-Hig", "Artner-2005-Hig", "Artner-2005-Thesis", "audioflow", "Auzinger_Mistelbauer_2013_CSR", "balabanian-2007-ant", "balabanian-2008-hvv", "Balabanian-2010-IIV", "Balabanian-2010-PSDSV", "Balduz_01", "Basch_2011_ATA", "Bauer_David_2018", "Bauer_Johannes_2014_IWB", "bauer-2015-cbfd", "Bayat_2019", "bayer-2015-gapaot", "bbeer-2013", "Bechtold2020", "Beer_2011_DVE", "Beham_Michael_PSC", "beham-2014-cupid", "bernhard-2006-dvrcta", "bernhard-2014-GTOM", "bernhard-2016-gft", "Bernold_2019", "bernold-2019-epr", "bhore-2021-issac", "birkeland_aasmund_2014_pums", "Birkeland-2012-IMC", "BirsakHanzl-2009", "boeroendy-2022-uio", "boesch_2014_browserHistoryVis", "borgo-2013-gly", "borondy2022", "bouzari-thesis", "bramberger-3pv", "Brandorff-08-OV", "brandorff-2009-erv", "brandstaetter_01", "brandstaetter-2007-vosd", "Brandstaetter2020", "Braunsperger-2025_bsc", "breitenecker-2020-bct", "bront-2023-svo", "brucker-2010-RES", "Bruckner_Stefan_2015_VAS", "bruckner-2004-EVV", "bruckner-2005-AIV", "bruckner-2005-ATI", "bruckner-2005-ICV", "bruckner-2005-vid", "bruckner-2005-VIS", "bruckner-2006-EVV", "bruckner-2006-ICE", "bruckner-2007-EDF", "bruckner-2007-STF", "bruckner-2008-IIV", "bruckner-2008-IVV", "bruckner-2009-BVQ", "bruckner-2009-IVV", "bruckner-2010-HVC", "bruckner-2010-IFC", "bruckner-2010-ISM", "bruckner-2010-SES", "Bruckner-2012-VEA", "buerger_raphael_2006_3dpoly", "Buerger-2007-cmv", "Buerger-2007-eurovis", "buerger-2007-star", "bugnar-esk-2021", "burns-2007-fea", "bydlinski-2015-gapaot", "byska-2019-mdfc", "Cai_2018", "Caic2021", "Carata_2011_IVE", "carbesser-2013", "casellato-2016-pkg", "cellVIEW_2015", "cizmic-2018-evd", "cmolik-2020-tvcg", "Cornel_2020", "Cornel_Daniel_2015_VOC", "Cornel2016CFM", "coto-2005-MAC", "Cruz-thesis", "Csebfalvi-2002-FPVF", "Csebfalvi-2002-SBICG", "Csebfalvi-2002-Smo", "Csebfalvi-2012-IOM", "Csuk_2011", "daae-lampe-2010-dif", "dataset-christmastree", "dataset-present", "dataset-stagbeetle", "Deutsch-2018", "Dhanoa_2021", "dhanoa-2025-ave", "Dhanoa2024", "Diehl_2015", "Diehl_2021", "Diehl-2017-Albero", "Dietrich_1", "dietrich-2016-viseq2", "diss-thesis-bratislava", "diss-thesis-magdeburg", "diss-thesis-siegen", "djuric-2020-wvo", "donabauer_2019_1", "donabauer-2015-asc", "draeger-2005-chain", "dworschak-2016-szcm", "dworschak-2016-szcm", "dworschak-2024-aml", "Eckelt_2017", "Eckelt_2018_01", "Edi_2019_10_01", "edlinger-2018-vwr", "eg-tut2005-iv", "Ehlers_PhD", "ehlers-2023-iro", "ehlers-2024-mmm", "ehlers-2024-vgs", "ehlers-2025-ait", "Eichner2022", "eitler-2024-sos", "eiweck-hnv-2021", "ellhotka-2025-ipo", "emsenhuber-2008-vhd", "erler-2025-lidarscout", "eschner-2023-evl", "eschner-2023-ims", "eschner-2025-ide", "eschner-blur-2022", "Escribano_2017", "Essler2022", "EuroVis2018-ShortPapers-Karall", "EuroVis2018-ShortPapers-Reiter", "facial2004", "Fechter_2011_DBS", "filipovic-2014-dect", "FISCHL-2012-CTASEG", "fmistelbauer-2014-ad", "fmistelbauer-2014-adict", "Ford-2012-HRV", "fourousan2021", "freiler-2008-ste", "fritz-2009-ieq", "Froehler_Berhnard_2015_ESM", "froschauer-2009-iod", "Fruehstueck_Anna_2015_DOM", "fuchs_raphael_2007_par", "fuchs_vhml", "fuchs-2008-del", "fuchs-vortex", "furmanova_2020", "gadllah_2016", "Gadllah_Hani_2016", "gall_2016", "Gall_2017", "gall_alexander_2016BA", "gall-2025-marv", "Gall2020", "Gall2021", "gangl-2018-gpsart", "Ganglberger-2022-cg", "ganglberger2019", "Ganuza", "Ganuza_2015", "Ganuza_MJ_2015_AVe", "Ganuza_ML_2015_ISA", "Ganuza-2017-IVCSGM", "Gavrilescu_2011_VGP", "gavrilescu-2008-vsc", "gavrilescu-2009-postrend", "Gavrilescu-2010-CIE", "Gehrer_Daniel_CUI", "Gehrer-2017", "Gehrer-2017-molmach", "georgiev-2019-cbg", "gerl-2006-vhi", "geymayer-2017-std", "Gietl_2020", "Gillmann2021", "glanznig-2009-LAMC", "glinzner-2016-tex", "goel-2024-rdr", "Gogel2020", "gostler-2015-3dp", "grammatikaki-2025-htr", "grammatikaki-thesis", "grimm-2004-arefined", "GRIMM-2004-FDMX-P", "grimm-2004-memory", "GRIMM-2004-PPC", "grimm-2004-volume", "Groeller_2011_CVC", "Groeller_2011_CW", "Groeller_2011_GBC", "Groeller_2011_HP", "Groeller_2011_HSU", "Groeller_2011_IPV", "Groeller_2011_IVP", "Groeller_2011_NR", "Groeller_2011_NSM", "Groeller_2011_VCD", "Groeller_2011_VSD", "Groeller_2011_VSD", "Groeller_2011_VSD", "Groeller_2011_VSS", "Groeller_2012_KAV", "Groeller_2012_VBP", "Groeller_2012_ViV", "Groeller_2012_VV", "Groeller_2014_CaQ", "Groeller_2014_CQV", "Groeller_2014_CV", "Groeller_2014_RWA", "Groeller_2014_STC", "Groeller_2014_UPS", "Groeller_2014_VND", "Groeller_2016_I2", "Groeller_2016_I7", "Groeller_2016_I8", "Groeller_2016_P2", "Groeller_2016_P4", "Groeller_2016_P6", "Groeller_2016_P7", "Groeller_2021_11", "Groeller_2021_BVM", "Groeller_2021-10", "Groeller_Edi_2013_TVC", "Groeller_Edi_2013_VCQ", "Groeller_Edi_2013TVCK", "Groeller_Edi_VKA", "Groeller_Eduard_2014_THS", "Groeller_Eduard_2014_TSP", "Groeller_Eduard_2014_UCT", "Groeller_Eduard_2015_SMV", "Groeller_Eduard_2015_TCU", "Groeller_V1_2020", "Groeller_V2_2020", "Groeller_V3_2020", "Groeller_V42020", "Groeller_V5_2020", "groeller-2004-efficient", "groeller-2004-imp", "groeller-2004-sci", "groeller-2005-dia", "Groeller-2010-CVC", "Groeller-2010-IFI", "Groeller-2010-IVVI", "Groeller-2011-HSH", "Groeller-2017-ARTORW", "Groeller-2017-AVC", "Groeller-2017-IVAMCS", 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"wu-2018-story", "wu-2019-bmc", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-smwp", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg", "wu-2021", "wu-2021-vi", "xmastree2002", "xmastree2005", "ymca", "YOGHOURDJIAN2019", "Zambal-2003-SWA", "zambal-2005-3dact", "Zaufel_2021", "zauner-2013-svkinect", "zechmeister2020", "Zeng_2021", "Zhu-2014-flowvis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Workgroup&id=vis", "__class": "Workgroup" }, { "id": "deskollage", "workgroup_id": "vis", "drupal_id": 4198, "drupal_path": "/research/projects/deskollage", "name": "Visual Information Foraging on the Desktop", "name_de": null, "short_title": "deskollage", "website": null, "status": "active", "short_abstract": "The goal of this project is to design and develop novel interactive visualization techniques to support knowledge workers in making sense of their unstructured, dynamic information collections. ", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. On the one hand, the studies show that, in some situations, interactive visualization can be less efficient than working with unprocessed text-based information. On the other hand, the studies also show that combining automatic data analysis with interactive visualization can lead to more unexpected findings, especially when exploring large data. The extent of manual information organization varies with the task: the less users know about the gathered information, the more automatic organization they expect. \n\nIn summary, this project contributed novel user interface concepts and design guidelines for user interfaces supporting information foraging and sensemaking. The techniques and study results were published at high-ranking peer-reviewed venues, and it can be expected that the findings of this project shape the way how users seek and organize their information in the future. \n\n", "start_date": "2015-12-01", "end_date": "2018-12-31", "leader_id": 1110, "logo": { "name": "logo.png", "path": "project:deskollage", "type": "image/png", "size": 331697, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/deskollage/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "T 752-N30", "comment": null } ], "research_areas": [ "InfoVis" ], "publications": [ "2019-ic", "byska-2019-mdfc", "casellato-2016-pkg", "cizmic-2018-evd", "donabauer-2015-asc", "dworschak-2016-szcm", "edlinger-2018-vwr", "georgiev-2019-cbg", "geymayer-2017-std", "gundacker-2020-wlm", "gusenbauer-2018", "hromniak-2019-vcn", "Koszticsak-2017-ewt", "mazurek-2017-sio", 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"TR-186-2-08-03", "TR-186-2-08-04", "TR-186-2-08-05", "TR-186-2-08-06", "TR-186-2-08-07", "TR-186-2-08-08", "TR-186-2-08-10", "TR-186-2-08-11", "TR-186-2-08-12", "TR-186-2-08-14", "TR-186-2-09-01", "TR-186-2-15-03", "TR1862162", "Tramberger_2018", "Tramberger2017BCS", "Trautner_Thomas_2014_VAE", "trautner-2018-imd", "trautner-2018-imd", "travnicek-2017-thm", "Trenkwalder-2004-MAR", "tretyak-2025-tacmedvr", "Troidl_2019", "Troidl_2021", "Troidl_2022", "turner-aso", "tut-eg-2006", "tut-siggraph-2006", "tut-vis-2006", "tut-vis-2007", "tweebo-2014", "ulschmid-2024-reo", "ulschmid-2025-apc", "unger_2017", "unger-2019_vcp", "Unger2020", "unterguggenberger-2024-fropo", "usul-thesis", "vad_2015_phd", "Vad_Viktor_2015_RVV", "vad-2016-bre", "vaico", "varchola_andrej-2012-fetoscopic", "Vasileva_2022", "Vasileva-2018", "vessel2003", "Viola_2013_IDV", "Viola_Ivan_2013_CAI", "Viola_Ivan_2013_D3D", "Viola_Ivan_2013_DC", "Viola_Ivan_2013_GS", "Viola_Ivan_2013_HQ3", "Viola_Ivan_2013_RMA", "Viola_Ivan_2013_RSb", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_DAC", "Viola_Ivan_IIP", "Viola_Ivan_UVP", "Viola_Ivan_VDP", "Viola-05-Smart", "Viola-2003-GPU", "Viola-2003-Har", "viola-2003-hbn", "Viola-2003-NON", "viola-2004-gbf", "Viola-2004-GPU", "viola-2004-har", "viola-2004-har2", "viola-2004-idv", "viola-2004-imp", "Viola-2004-ImpX", "Viola-2004-ImpX2", "viola-2005-imp", "viola-2006-FoA", "viola-evr", "Viola-Pondering-2017", "viola-popular-article-2006", "Viola-vistutillustrativevis", "vis-foa", "VisWeek-Tutorial-2012-Uncertainty", "vitruvian_2019", "voglreiter-2023-tro", "Vucenovic_2022", "vucini_2006", "vucini_2008_rnp", "vucini_2009", "vucini_erald-2007-FRI", "vucini-2009-phd", "vucini-2011", "Wagner_032017", "walchhofer_ar_flowmaps", "walchhofer-tso", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "Waldin_Nicholas_2017_FlickerObserver", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2017-thesis", "waldin-2019-ccm", "waldin-2019-ccm", "Waldner_2017_11", "Waldner_2017_11", "waldner-2013-facetCloudsGI", "waldner-2013-ubiWM", "waldner-2014-af", "waldner-2014-ghi", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "waser_2011_VSD", "Waser-2010-WL", "webGPU_aggregateVis-2023", "weiner_2011", "Weissenboeck_2019", "Weissenboeck_2019_PhD", "weissenboeck-2014", "Wihann_2017", "wolf-2023-cc", "wolf-2024-jhd", "Woschizka_2021", "wu-2017-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-shonan", "wu-2018-story", "wu-2019-bmc", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-smwp", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg", "wu-2021", "wu-2021-vi", "xmastree2002", "xmastree2005", "ymca", "YOGHOURDJIAN2019", "Zambal-2003-SWA", "zambal-2005-3dact", "Zaufel_2021", "zauner-2013-svkinect", "zechmeister2020", "Zeng_2021", "Zhu-2014-flowvis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Workgroup&id=vis", "__class": "Workgroup" }, { "id": "Illustrare", "workgroup_id": "vis", "drupal_id": 4189, "drupal_path": "/research/projects/Illustrare", "name": "ILLUSTRARE: Integrative Visual Abstraction of Molecular Data", "name_de": null, "short_title": "Illustrare", "website": null, "status": "active", "short_abstract": "FWF - I 2953-N31\nIntegrative Visual Abstraction of Molecular Data", "abstract": "In many aspects of our modern lives we face the problem of having to make sense of large amounts of data. This applies to scientists trying to make sense of their experiments and simulations, to bankers and traders trying to understand the dynamics of the financial markets, and to large enterprises which need to understand the principles behind demand and supply—to name just a few examples. The basic problem in all these cases is that people need to identify important and/or unexpected features in large simulated or captured datasets. Visualization is the domain that facilitates this process of sense-making by dramatically simplifying the process of obtaining an understanding of the data—by representing data visually and thus amplifying people’s cognition. This inherent capability of (good) visualization techniques to amplify human cognition, however, is no longer enough to be able to make sense of today’s huge datasets. To be able to see the essential aspects we need dedicated mechanisms that abstract away the (unnecessary) detail to, in turn, allow the user of the visualization to focus on the important elements. The crucial problem in this context is that it is impossible to know what is important and what is not in a general way—importance changes based on the research question, on the application domain, on the data size, on the user, on the specific situation, etc. Visualization technology therefore needs to support dynamic change of visual abstraction of the data to reflect these contextual changes. The fundamental research challenge in visualization for us is to get an understanding of what (visual) abstraction really is, what it means, how it can be controlled, and how it is, can be, and should be used in visualization.\n", "start_date": "2017-01-01", "end_date": "2019-12-31", "leader_id": 171, "logo": { "name": "logo.jpg", "path": "project:Illustrare", "type": "image/jpeg", "size": 95116, "orig_name": "logo.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/Illustrare/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "I 2953-N31", "comment": null } ], "research_areas": [ "BioVis", "IllVis" ], "publications": [ "Halladjian_2020", "kouril-2018-LoL", "lawonn-2018-illvisstar", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "Viola-Pondering-2017" ], "url": "https://www.cg.tuwien.ac.at/research/projects/Illustrare", "__class": "Project" }, { "id": "illvisation", "workgroup_id": "vis", "drupal_id": 4171, "drupal_path": "/research/projects/illvisation", "name": "Visual Computing: Illustrative Visualization", "name_de": null, "short_title": "illvisation", "website": null, "status": "active", "short_abstract": "

The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/

\r\n\r\n

Prototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/

\r\n\r\n

cellVIEW

\r\n\r\n

cellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.

\r\n\r\n

Invited Talks

\r\n\r\n

18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness

\r\n", "abstract": "

The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/

\r\n\r\n

Prototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/

\r\n\r\n

cellVIEW

\r\n\r\n

cellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.

\r\n\r\n

Invited Talks

\r\n\r\n

18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness

\r\n", "start_date": "2013-01-01", "end_date": "2020-12-31", "leader_id": 171, "logo": { "name": "logo.png", "path": "project:illvisation", "type": "image/png", "size": 58061, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/illvisation/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "eu7", "contract_number": "PCIG13-GA-2013-618680", "comment": null }, { "id": "WWTF", "contract_number": "VRG11-010", "comment": null } ], "research_areas": [ "BioVis", "IllVis" ], "publications": [ "2013_Viola_Ivan_2013_MTS", "2017-kouril-illcell", "bernhard-2014-GTOM", "bernhard-2016-gft", "birkeland_aasmund_2014_pums", "boesch_2014_browserHistoryVis", "cellVIEW_2015", "Cornel2016CFM", "Diehl_2015", "dietrich-2016-viseq2", "dworschak-2016-szcm", "Gadllah_Hani_2016", "gangl-2018-gpsart", "Gehrer_Daniel_CUI", "Gehrer-2017-molmach", "glinzner-2016-tex", "Groeller_2016_I7", "horvath-2018-ism", "kapferer-2017-godot", "koch-2018-sso", "koehle-2013-sgv", "kolesar-ivan-2014-polymers", "kouril-2015-maya2cellview", "Krone2016VABC", "Langer_Maximillian_DMV", "lemuzic_2015_timelapse", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lemuzic-mindek-sorger-cgfcc", "lipp-2017-mgpu", "lipp-2017-vulkan", "miao_tvcg_2017", "miao_tvcg_2018", "mindek-2015-mc", "mindek-2016-utah-talk", "mindek-2017-dsn", "mindek-2017-marion", "mindek-2018-fyi", "mindek-2019-mci", "moerth-2018-tpose", "Plank_Pascal_2015_HVP", "plank-2017-sldg", "puenguentzky-2014-ht", "rasch-2016-imgses", "Reisacher_Matthias_CPW", "Reisacher2016", "Sbardellati-2019-vcbm", "seyfert-2017", "sifuentes-2018-crowd", "Solteszova2016", "sorger-2016-fowardabstraction", "textures-3d-printing", "vad-2016-bre", "Viola_2013_IDV", "Viola_Ivan_2013_CAI", "Viola_Ivan_2013_D3D", "Viola_Ivan_2013_DC", "Viola_Ivan_2013_GS", "Viola_Ivan_2013_HQ3", "Viola_Ivan_2013_RMA", "Viola_Ivan_2013_RSb", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_DAC", "Viola_Ivan_IIP", "Viola_Ivan_UVP", "Viola_Ivan_VDP", "viola-evr", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2017-thesis", "waldner-2013-facetCloudsGI", "waldner-2013-ubiWM", "waldner-2014-af", "waldner-2014-ghi", "wu-2019-bmc" ], "url": "https://www.cg.tuwien.ac.at/research/projects/illvisation", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/miao_tvcg_2018/", "__class": "Publication" }, { "id": "klein_2017_IM", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "Instant Construction and Visualization of Crowded Biological Environments", "date": "2018", "abstract": "We present the first approach to integrative structural modeling of the biological mesoscale within an interactive visual environment. These complex models can comprise up to millions of molecules with defined atomic structures, locations, and interactions. Their construction has previously been attempted only within a non-visual and non-interactive environment. Our solution unites the modeling and visualization aspect, enabling interactive construction of atomic resolution mesoscale models of large portions of a cell. We present a novel set of GPU algorithms that build the basis for the rapid construction of complex biological structures. These structures consist of multiple membrane-enclosed compartments including both soluble molecules and fibrous structures. The compartments are defined using volume voxelization of triangulated meshes. For membranes, we present an extension of the Wang\nTile concept that populates the bilayer with individual lipids. Soluble molecules are populated within compartments using the Halton\nsequence for their distribution. Fibrous structures, such as RNA or actin filaments, are created by self-avoiding random walks. Resulting overlaps of molecules are resolved by a forced-based system. Our approach opens new possibilities to the world of interactive\nconstruction of cellular compartments. We demonstrate its effectiveness by showcasing scenes of different scale and complexity that\ncomprise blood plasma, mycoplasma, and HIV.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "preview_image_width": 1726, "preview_image_height": 760, "name": "klein_2017_IM-image.png", "type": "image/png", "size": null, "path": "Publication:klein_2017_IM", "preview_name": "klein_2017_IM-image:preview.png", "preview_type": "image/png", "preview_size": 706858, "url": "https://www.cg.tuwien.ac.at/research/publications/2018/klein_2017_IM/klein_2017_IM-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/klein_2017_IM/klein_2017_IM-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1285, "drupal_id": 1146, "orcid_id": null, "website": 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Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. 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"Author" }, { "id": 563, "drupal_id": null, "orcid_id": null, "website": "http://isgwww.cs.uni-magdeburg.de/isg/bernhard.html", "firstname": "Bernhard", "lastname": "Preim", "searchname": "Bernhard Preim", "is_teacher": false, "name": "Bernhard Preim", "publications": [ "bruckner-2010-IFC", "eg-tut2005-iv", "furmanova-2024-bvp", "Gillmann2021", "lawonn-2018-illvisstar", "lee-2022-p", "miao_tvcg_2017", "Muigg-2008-four", "preim-2009-sve", "preim-2023-vva", "raidou_2020Onc", "raidou_star2019", "tut-eg-2006", "tut-vis-2006", "Viola-vistutillustrativevis" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "amirkhanov-2021-diss", "field_id": "reviewer_2", "ordernum": 0 }, { "publ_id": "Groeller_2016_P4", "field_id": "lecturer", "ordernum": 1 }, { "publ_id": "karimov-2016-GIVE", "field_id": "reviewer_2", "ordernum": 0 }, { "publ_id": "kouril-2021-phdthesis", "field_id": "reviewer_2", "ordernum": 0 }, { "publ_id": "schlachter-2022-vcm", "field_id": "reviewer_2", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=563", "__class": "Author" }, { "id": 960, "drupal_id": null, "orcid_id": null, "website": "https://tobias.isenberg.cc/", "firstname": "Tobias", "lastname": "Isenberg", "searchname": "Tobias Isenberg", "is_teacher": false, "name": "Tobias Isenberg", "publications": [ "Halladjian_2020", "kouril-2020-hyperlabels", "kouril-2021-molecumentary", "lawonn-2018-illvisstar", "Miao_2019", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "Peter_2012_AIV", "Sarkis_2021", "Viola-Pondering-2017" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "Viola-Pondering-2017", "field_id": "lecturer", "ordernum": 1 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=960", "__class": "Author" } ], "doi": "10.1111/cgf.13322", "issn": "1467-8659", "journal": "Computer Graphics Forum", "number": "NN", "open_access": "no", "pages": "n/a–n/a", "research_areas": [ { "id": "IllVis", "drupal_id": 4131, "name": "Illustrative Visualization", "short_abstract": "In this research area, we develop rendering methods that are inspired by scientific illustrations, in order to make complex biological information more intuitive to understand and more pleasant to read.", "abstract": "Scientific illustration is concerned with researching ways in which complex biological and medical data can be abstracted in order to convey a desired information that would otherwise be impossible or hard to retrieve from the original data. Illustrators apply such techniques, for instance, to present non-important parts of an organ in a simplified way, while using detailed representations to put the focus of attention on a region where a tumor might be situated.\n\nTo identify such meaningful visual abstractions for visualization, their effectiveness for human perception and cognition has to be assessed, and they have to be formalized in order to make them applicable in rendering algorithms. In this project, we try to advance the understanding of procedural visual abstraction of complex physiological processes that describe the complex machinery of biological life.", "website": "https://www.cg.tuwien.ac.at/research/area/IllVis", "teaser": { "name": "teaser.jpg", "path": "research_area:IllVis", "type": "image/jpeg", "size": 34861, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/IllVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "antes-2026-maa", "Antonini2020", "Balabanian-2010-IIV", "Balduz_01", "Bayat_2019", "Bechtold2020", "Birkeland-2012-IMC", "brandstaetter_01", "bruckner-2005-ICV", "bruckner-2006-ICE", "bruckner-2007-STF", "bruckner-2008-IIV", "bruckner-2010-HVC", "bruckner-2010-IFC", "cellVIEW_2015", "Chen-Information-2016", "Deutsch-2018", "Dhanoa_2021", "Dhanoa2024", "dietrich-2016-viseq2", "donabauer_2019_1", "eg-tut2005-iv", "eschner-2023-ims", "Essler2022", "gangl-2018-gpsart", "Gehrer_Daniel_CUI", "Gehrer-2017-molmach", "gerl-2006-vhi", "Gogel2020", "Groeller_2011_IPV", "Groeller_2016_I3", "Groeller_2016_I6", "Groeller_2016_I7", "Groeller_2016_I8", "Groeller_V1_2020", "groeller-2006-ivt", "groeller-2007-fci", "groeller-2008-irs", "Groeller-2010-IFI", "gruber-2025-vps", "Halladjian_2020", "haushofer-2018-skinning", "Heim_2020", "horvath-2018-ism", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "Knapp_2017_CVR", "Koeppel2020", "kolesar-ivan-2014-polymers", "Konev-FCV2018", "Koszticsak-2017-ewt", "Kouril_2017_11", "kouril-2020-hyperlabels", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "kroesl_x_card_2017", "Lackner_2022", "Langer_Edith_IR1", "lawonn-2018-illvisstar", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "LeMuzic_2016_PhD", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "Leutschacher_2022", "ludwig-2012-MT", "Manczarski-2016", "Matusich-2017-01", "Mautner 2020", "Mayr-2017-1", "Melo_2018_11", "Meusburger_2020", "Miao_2019", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao2018Dimsum", "Michl_2017_CSV", "mindek-2015-mc", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-2019-mci", "mindek-xmas-card-2016", "Moellinger_Christian_IDE2", "Niedermayer_2018", "Ortner_PhD", "Ortner2020", "pahr-2021-vologram", "Panayotov", "patel_daniel_2007_IRSD", "Pauschenwein_2022", "Peter_2012_AIV", "plank-2017-sldg", "prost-2016-molecule", "purgathofer-2008-cgi", "Radwan-2017-Occ", "Rautek-2007-SLI", "Rautek-2008-IDS", "Rautek-2008-VF", "Reichinger_2016", "Reichinger_Fuhrmann_2016", "Reisacher_Matthias_CPW", "Reisacher2016", "Riegelnegg_2019", "rippl-2023-atg", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "schindler_2020vis", "schmidlehner2021", "scholz_2021", "Schrempf_2020", "schultes_lampi", "seyfert-2017", "sikachev-2010-ill_vis_vol_ren", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "Spechtenhauser_Florian_2016", "stappen_2017_animatedcomic", "Stoll2020", "sturl_2016_dynlabels", "Swoboda2020", "szabo_patrik-2022-tour", "takahashi-2019-acdt", "Thomas-2018", "TR-186-2-07-08", "Troidl_2021", "Troidl_2022", "tut-eg-2006", "tut-siggraph-2006", "tut-vis-2006", "tut-vis-2007", "Unger2020", "Vasileva_2022", "Viola_Ivan_2013_SVA", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "viola-evr", "Viola-Pondering-2017", "Viola-vistutillustrativevis", "Waldin_Nicholas_2016_Colormaps", "waldin-2019-ccm", "Waldner_2017_11", "Wihann_2017", "Woschizka_2021", "wu-2019-bmc", "wu-2019-report", "Zaufel_2021", "zechmeister2020", "Zeng_2021", "Zusag-2017-Bach" ], "projects": [ "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=IllVis", "__class": "ResearchArea" } ], "keywords": [ "scientific visualization", "visualization", "Categories and SubjectDescriptors (according to ACM CCS): I.3.3 [Computer Graphics]:Picture/Image GenerationLine and curve generation" ], "weblinks": [], "files": [], "projects_workgroups": [ { "id": "Illustrare", "workgroup_id": "vis", "drupal_id": 4189, "drupal_path": "/research/projects/Illustrare", "name": "ILLUSTRARE: Integrative Visual Abstraction of Molecular Data", "name_de": null, "short_title": "Illustrare", "website": null, "status": "active", "short_abstract": "FWF - I 2953-N31\nIntegrative Visual Abstraction of Molecular Data", "abstract": "In many aspects of our modern lives we face the problem of having to make sense of large amounts of data. This applies to scientists trying to make sense of their experiments and simulations, to bankers and traders trying to understand the dynamics of the financial markets, and to large enterprises which need to understand the principles behind demand and supply—to name just a few examples. The basic problem in all these cases is that people need to identify important and/or unexpected features in large simulated or captured datasets. Visualization is the domain that facilitates this process of sense-making by dramatically simplifying the process of obtaining an understanding of the data—by representing data visually and thus amplifying people’s cognition. This inherent capability of (good) visualization techniques to amplify human cognition, however, is no longer enough to be able to make sense of today’s huge datasets. To be able to see the essential aspects we need dedicated mechanisms that abstract away the (unnecessary) detail to, in turn, allow the user of the visualization to focus on the important elements. The crucial problem in this context is that it is impossible to know what is important and what is not in a general way—importance changes based on the research question, on the application domain, on the data size, on the user, on the specific situation, etc. Visualization technology therefore needs to support dynamic change of visual abstraction of the data to reflect these contextual changes. The fundamental research challenge in visualization for us is to get an understanding of what (visual) abstraction really is, what it means, how it can be controlled, and how it is, can be, and should be used in visualization.\n", "start_date": "2017-01-01", "end_date": "2019-12-31", "leader_id": 171, "logo": { "name": "logo.jpg", "path": "project:Illustrare", "type": "image/jpeg", "size": 95116, "orig_name": "logo.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/Illustrare/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "I 2953-N31", "comment": null } ], "research_areas": [ "BioVis", "IllVis" ], "publications": [ "Halladjian_2020", "kouril-2018-LoL", "lawonn-2018-illvisstar", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "Viola-Pondering-2017" ], "url": "https://www.cg.tuwien.ac.at/research/projects/Illustrare", 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"url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=608", "__class": "Author" } ], "date_from": "2017", "date_to": "2017", "event": "SIGGRAPH Asia 2017 Course 0023", "location": "Bangkok, Thailand", "research_areas": [], "keywords": [], "weblinks": [ { "href": "https://sa2017.siggraph.org/attendees/courses?view=session&sid=9", "caption": "SIGGRAPH Asia 2017 Course Information", "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "course notes", "main_file": true, "use_in_gallery": false, "access": "public", "name": "sbert-2017-sa_course_0023-course notes.pdf", "type": "application/pdf", "size": 10503939, "path": "Publication:sbert-2017-sa_course_0023", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/sbert-2017-sa_course_0023/sbert-2017-sa_course_0023-course notes.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/sbert-2017-sa_course_0023/sbert-2017-sa_course_0023-course notes:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2017/sbert-2017-sa_course_0023/", "__class": "Publication" }, { "id": "Viola-Pondering-2017", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "Pondering the Concept of Abstraction in (Illustrative) Visualization", "date": "2017-09-04", "abstract": "We explore the concept of abstraction as it is used in visualization, with the ultimate goal of understanding and formally defining it. Researchers so far have used the concept of abstraction largely by intuition without a precise meaning. This lack of specificity\nleft questions on the characteristics of abstraction, its variants, its control, or its ultimate potential for visualization and, in particular, illustrative visualization mostly unanswered. In this paper we thus provide a first formalization of the abstraction concept and discuss how this formalization affects the application of abstraction in a variety of visualization scenarios. Based on this discussion, we derive a number of open questions still waiting to be answered, thus formulating a research agenda for the use of abstraction for the visual representation and exploration of data. This paper, therefore, is intended to provide a contribution to the discussion of the theoretical foundations of our field, rather than attempting to provide a completed and final theory.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 4283, "image_height": 3539, "name": "Viola-Pondering-2017-image.jpg", "type": "image/jpeg", "size": 447826, "path": "Publication:Viola-Pondering-2017", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/Viola-Pondering-2017/Viola-Pondering-2017-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/Viola-Pondering-2017/Viola-Pondering-2017-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 171, "drupal_id": 168, "orcid_id": "0000-0003-4248-6574", "website": 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"ordernum": 1 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=960", "__class": "Author" } ], "number": "99", "open_access": "yes", "research_areas": [ { "id": "IllVis", "drupal_id": 4131, "name": "Illustrative Visualization", "short_abstract": "In this research area, we develop rendering methods that are inspired by scientific illustrations, in order to make complex biological information more intuitive to understand and more pleasant to read.", "abstract": "Scientific illustration is concerned with researching ways in which complex biological and medical data can be abstracted in order to convey a desired information that would otherwise be impossible or hard to retrieve from the original data. Illustrators apply such techniques, for instance, to present non-important parts of an organ in a simplified way, while using detailed representations to put the focus of attention on a region where a tumor might be situated.\n\nTo identify such meaningful visual abstractions for visualization, their effectiveness for human perception and cognition has to be assessed, and they have to be formalized in order to make them applicable in rendering algorithms. In this project, we try to advance the understanding of procedural visual abstraction of complex physiological processes that describe the complex machinery of biological life.", "website": "https://www.cg.tuwien.ac.at/research/area/IllVis", "teaser": { "name": "teaser.jpg", "path": "research_area:IllVis", "type": "image/jpeg", "size": 34861, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/IllVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "antes-2026-maa", "Antonini2020", "Balabanian-2010-IIV", "Balduz_01", "Bayat_2019", "Bechtold2020", "Birkeland-2012-IMC", "brandstaetter_01", "bruckner-2005-ICV", "bruckner-2006-ICE", "bruckner-2007-STF", "bruckner-2008-IIV", "bruckner-2010-HVC", "bruckner-2010-IFC", "cellVIEW_2015", "Chen-Information-2016", "Deutsch-2018", "Dhanoa_2021", "Dhanoa2024", "dietrich-2016-viseq2", "donabauer_2019_1", "eg-tut2005-iv", "eschner-2023-ims", "Essler2022", "gangl-2018-gpsart", "Gehrer_Daniel_CUI", "Gehrer-2017-molmach", "gerl-2006-vhi", "Gogel2020", "Groeller_2011_IPV", "Groeller_2016_I3", "Groeller_2016_I6", "Groeller_2016_I7", "Groeller_2016_I8", "Groeller_V1_2020", "groeller-2006-ivt", "groeller-2007-fci", "groeller-2008-irs", "Groeller-2010-IFI", "gruber-2025-vps", "Halladjian_2020", "haushofer-2018-skinning", "Heim_2020", "horvath-2018-ism", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "Knapp_2017_CVR", "Koeppel2020", "kolesar-ivan-2014-polymers", "Konev-FCV2018", "Koszticsak-2017-ewt", "Kouril_2017_11", "kouril-2020-hyperlabels", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "kroesl_x_card_2017", "Lackner_2022", "Langer_Edith_IR1", "lawonn-2018-illvisstar", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "LeMuzic_2016_PhD", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "Leutschacher_2022", "ludwig-2012-MT", 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"seyfert-2017", "sikachev-2010-ill_vis_vol_ren", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "Spechtenhauser_Florian_2016", "stappen_2017_animatedcomic", "Stoll2020", "sturl_2016_dynlabels", "Swoboda2020", "szabo_patrik-2022-tour", "takahashi-2019-acdt", "Thomas-2018", "TR-186-2-07-08", "Troidl_2021", "Troidl_2022", "tut-eg-2006", "tut-siggraph-2006", "tut-vis-2006", "tut-vis-2007", "Unger2020", "Vasileva_2022", "Viola_Ivan_2013_SVA", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "viola-evr", "Viola-Pondering-2017", "Viola-vistutillustrativevis", "Waldin_Nicholas_2016_Colormaps", "waldin-2019-ccm", "Waldner_2017_11", "Wihann_2017", "Woschizka_2021", "wu-2019-bmc", "wu-2019-report", "Zaufel_2021", "zechmeister2020", "Zeng_2021", "Zusag-2017-Bach" ], "projects": [ "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=IllVis", "__class": "ResearchArea" } ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 4283, "image_height": 3539, "name": "Viola-Pondering-2017-image.jpg", "type": "image/jpeg", "size": 447826, "path": "Publication:Viola-Pondering-2017", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/Viola-Pondering-2017/Viola-Pondering-2017-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/Viola-Pondering-2017/Viola-Pondering-2017-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": false, "use_in_gallery": false, "access": "public", "name": "Viola-Pondering-2017-paper.pdf", "type": "application/pdf", "size": 61554037, "path": "Publication:Viola-Pondering-2017", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/Viola-Pondering-2017/Viola-Pondering-2017-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/Viola-Pondering-2017/Viola-Pondering-2017-paper:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "Illustrare", "workgroup_id": "vis", "drupal_id": 4189, "drupal_path": "/research/projects/Illustrare", "name": "ILLUSTRARE: Integrative Visual Abstraction of Molecular Data", "name_de": null, "short_title": "Illustrare", "website": null, "status": "active", "short_abstract": "FWF - I 2953-N31\nIntegrative Visual Abstraction of Molecular Data", "abstract": "In many aspects of our modern lives we face the problem of having to make sense of large amounts of data. This applies to scientists trying to make sense of their experiments and simulations, to bankers and traders trying to understand the dynamics of the financial markets, and to large enterprises which need to understand the principles behind demand and supply—to name just a few examples. The basic problem in all these cases is that people need to identify important and/or unexpected features in large simulated or captured datasets. Visualization is the domain that facilitates this process of sense-making by dramatically simplifying the process of obtaining an understanding of the data—by representing data visually and thus amplifying people’s cognition. This inherent capability of (good) visualization techniques to amplify human cognition, however, is no longer enough to be able to make sense of today’s huge datasets. To be able to see the essential aspects we need dedicated mechanisms that abstract away the (unnecessary) detail to, in turn, allow the user of the visualization to focus on the important elements. The crucial problem in this context is that it is impossible to know what is important and what is not in a general way—importance changes based on the research question, on the application domain, on the data size, on the user, on the specific situation, etc. Visualization technology therefore needs to support dynamic change of visual abstraction of the data to reflect these contextual changes. The fundamental research challenge in visualization for us is to get an understanding of what (visual) abstraction really is, what it means, how it can be controlled, and how it is, can be, and should be used in visualization.\n", "start_date": "2017-01-01", "end_date": "2019-12-31", "leader_id": 171, "logo": { "name": "logo.jpg", "path": "project:Illustrare", "type": "image/jpeg", "size": 95116, "orig_name": "logo.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/Illustrare/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "I 2953-N31", "comment": null } ], "research_areas": [ "BioVis", "IllVis" ], "publications": [ "Halladjian_2020", "kouril-2018-LoL", "lawonn-2018-illvisstar", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "Viola-Pondering-2017" ], "url": "https://www.cg.tuwien.ac.at/research/projects/Illustrare", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2017/Viola-Pondering-2017/", "__class": "Publication" }, { "id": "Groeller-2017-PTPMD", "type_id": "poster", "tu_id": null, "repositum_id": null, "title": "AnimoAminoMiner: Exploration of Protein Tunnels and their Properties in Molecular Dynamics", "date": "2017-07-24", "abstract": null, "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1254, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Jan", "lastname": "Byska", "searchname": "Jan Byska", "is_teacher": false, "name": "Jan Byska", "publications": [ "byska-2019-mdfc", "Furmanova_2018", "Groeller-2017-PTPMD", "raidou_pingu2020", "sMolBoxes_2022", "vad_viktor-2017-WVE", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "byska-2019-mdfc", "field_id": 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"field_id": "lecturer", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1194", "__class": "Author" } ], "research_areas": [ { "id": "BioVis", "drupal_id": 4127, "name": "Biological Data Visualization", "short_abstract": "In this research area, we develop new visualization techniques to support biologists in data analysis and create visualizations to disseminate scientific discoveries in biology.", "abstract": "In modern biological research domain experts have to deal with complex and large data collections and simulations. Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n", "website": "https://www.cg.tuwien.ac.at/research/area/BioVis", "teaser": { "name": "teaser.png", "path": "research_area:BioVis", "type": "image/png", "size": 16330957, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/BioVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "amirkhanov-2019-manylands", "byska-2019-mdfc", "cellVIEW_2015", "cmolik-2020-tvcg", "Dietrich_1", "dietrich-2016-viseq2", "Ehlers_PhD", "ehlers-2025-ait", "eschner-2023-ims", "eschner-blur-2022", "Escribano_2017", "Furmanova_2018", "Gehrer-2017", "Gehrer-2017-molmach", "glinzner-2016-tex", "Halladjian_2020", "kapferer-2017-godot", "klein_2017_IM", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koch-2018-sso", "Kolesar-Fractional-2016", "kolesar-ivan-2014-polymers", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kozlikova-Visualization-2016b", "Krone2016VABC", "Kugler_2019", "lemuzic_2015_timelapse", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lipp-2017-mgpu", "lipp-2017-vulkan", "Manczarski-2016", "manylands_award", "Miao_2019", "miao_inria_2017", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-xmas-card-2016", "Mitterhofer_2017", "nguyen_2020-covid", "Nowak_2020", "raidou_2019_springer", "raidou_shonan167", "raidou2018visualflatter", "rasch-2016-imgses", "Reisacher2016", "rinortner_susanne-2019-vpicc", "Sarkis_2021", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2013-neuromap", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "stappen_2017_animatedcomic", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "trautner-2018-imd", "unger-2019_vcp", "vad_2015_phd", "vad_viktor-2017-WVE", "vad-2016-bre", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "waldin-2019-ccm", "waldner-2014-af", "Weissenboeck_2019", "wu-2017-dagstuhl", "wu-2018-metabo", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg" ], "projects": [ "BioNetIllustration", "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=BioVis", "__class": "ResearchArea" }, { "id": "IllVis", "drupal_id": 4131, "name": "Illustrative Visualization", "short_abstract": "In this research area, we develop rendering methods that are inspired by scientific illustrations, in order to make complex biological information more intuitive to understand and more pleasant to read.", "abstract": "Scientific illustration is concerned with researching ways in which complex biological and medical data can be abstracted in order to convey a desired information that would otherwise be impossible or hard to retrieve from the original data. Illustrators apply such techniques, for instance, to present non-important parts of an organ in a simplified way, while using detailed representations to put the focus of attention on a region where a tumor might be situated.\n\nTo identify such meaningful visual abstractions for visualization, their effectiveness for human perception and cognition has to be assessed, and they have to be formalized in order to make them applicable in rendering algorithms. In this project, we try to advance the understanding of procedural visual abstraction of complex physiological processes that describe the complex machinery of biological life.", "website": "https://www.cg.tuwien.ac.at/research/area/IllVis", "teaser": { "name": "teaser.jpg", "path": "research_area:IllVis", "type": "image/jpeg", "size": 34861, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/IllVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "antes-2026-maa", "Antonini2020", "Balabanian-2010-IIV", "Balduz_01", "Bayat_2019", "Bechtold2020", "Birkeland-2012-IMC", "brandstaetter_01", "bruckner-2005-ICV", "bruckner-2006-ICE", "bruckner-2007-STF", "bruckner-2008-IIV", "bruckner-2010-HVC", "bruckner-2010-IFC", "cellVIEW_2015", "Chen-Information-2016", "Deutsch-2018", "Dhanoa_2021", "Dhanoa2024", "dietrich-2016-viseq2", 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"seyfert-2017", "sikachev-2010-ill_vis_vol_ren", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "Spechtenhauser_Florian_2016", "stappen_2017_animatedcomic", "Stoll2020", "sturl_2016_dynlabels", "Swoboda2020", "szabo_patrik-2022-tour", "takahashi-2019-acdt", "Thomas-2018", "TR-186-2-07-08", "Troidl_2021", "Troidl_2022", "tut-eg-2006", "tut-siggraph-2006", "tut-vis-2006", "tut-vis-2007", "Unger2020", "Vasileva_2022", "Viola_Ivan_2013_SVA", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "viola-evr", "Viola-Pondering-2017", "Viola-vistutillustrativevis", "Waldin_Nicholas_2016_Colormaps", "waldin-2019-ccm", "Waldner_2017_11", "Wihann_2017", "Woschizka_2021", "wu-2019-bmc", "wu-2019-report", "Zaufel_2021", "zechmeister2020", "Zeng_2021", "Zusag-2017-Bach" ], "projects": [ "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=IllVis", "__class": "ResearchArea" } ], "keywords": [], "weblinks": [], 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The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/

\r\n\r\n

Prototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/

\r\n\r\n

cellVIEW

\r\n\r\n

cellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.

\r\n\r\n

Invited Talks

\r\n\r\n

18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness

\r\n", "abstract": "

The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/

\r\n\r\n

Prototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/

\r\n\r\n

cellVIEW

\r\n\r\n

cellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.

\r\n\r\n

Invited Talks

\r\n\r\n

18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness

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"id": "BioVis", "drupal_id": 4127, "name": "Biological Data Visualization", "short_abstract": "In this research area, we develop new visualization techniques to support biologists in data analysis and create visualizations to disseminate scientific discoveries in biology.", "abstract": "In modern biological research domain experts have to deal with complex and large data collections and simulations. Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n", "website": "https://www.cg.tuwien.ac.at/research/area/BioVis", "teaser": { "name": "teaser.png", "path": "research_area:BioVis", "type": "image/png", "size": 16330957, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/BioVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "amirkhanov-2019-manylands", "byska-2019-mdfc", "cellVIEW_2015", "cmolik-2020-tvcg", "Dietrich_1", "dietrich-2016-viseq2", "Ehlers_PhD", "ehlers-2025-ait", "eschner-2023-ims", "eschner-blur-2022", "Escribano_2017", "Furmanova_2018", "Gehrer-2017", "Gehrer-2017-molmach", "glinzner-2016-tex", "Halladjian_2020", "kapferer-2017-godot", "klein_2017_IM", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koch-2018-sso", "Kolesar-Fractional-2016", "kolesar-ivan-2014-polymers", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kozlikova-Visualization-2016b", "Krone2016VABC", "Kugler_2019", "lemuzic_2015_timelapse", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lipp-2017-mgpu", "lipp-2017-vulkan", "Manczarski-2016", "manylands_award", "Miao_2019", "miao_inria_2017", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-xmas-card-2016", "Mitterhofer_2017", "nguyen_2020-covid", "Nowak_2020", "raidou_2019_springer", "raidou_shonan167", "raidou2018visualflatter", "rasch-2016-imgses", "Reisacher2016", "rinortner_susanne-2019-vpicc", "Sarkis_2021", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2013-neuromap", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "stappen_2017_animatedcomic", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "trautner-2018-imd", "unger-2019_vcp", "vad_2015_phd", "vad_viktor-2017-WVE", "vad-2016-bre", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "waldin-2019-ccm", "waldner-2014-af", "Weissenboeck_2019", "wu-2017-dagstuhl", "wu-2018-metabo", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg" ], "projects": [ "BioNetIllustration", "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=BioVis", "__class": "ResearchArea" }, { "id": "Modeling", "drupal_id": 4130, "name": "Modeling", "short_abstract": "In this area, we focus on researching methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.", "abstract": "One of the major bottlenecks in the field of computer graphics is the one of content creation, particularly the creation of high-quality 3D geometric models. These models are a demand in many industries, such as entertainment, computer-aided design, urban planning, the fabrication of physical objects, as well as research areas like medical or scientific visualizations and simulations.\n\nWhile rendering - the classical field of computer graphics - has reached very high standards in the recent two decades, the issue of the creation of appropriate digital models is a difficult problem that hardly keeps pace with current demands. Indeed, it is a complex creative process that involves both artistic and technical skills.\n\nTo make this process easier, our goal in this research area is to find new methods and algorithms that facilitate creation, representation, analysis and processing of 3D models.", "website": "https://www.cg.tuwien.ac.at/research/area/Modeling", "teaser": { "name": "teaser.jpg", "path": "research_area:Modeling", "type": "image/jpeg", "size": 190581, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Modeling/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "AA2020", "Adorjan-2015", "aichner-2016-sadf", "arikan-2013-osn", "birsak-thesis", "Birsak2018-SA", "Brandstaetter2020", "brunner_lukas_2022_ssb", "Caic2021", "clemenz_2019_rosy_fields", "DOG10", "dusberger-2010-msm", "eibens-2021-tsgpmg", "eibensteiner-2021-pmcg", "eibner-2009-gpc", "Erhardt_2025_Scutes", "erler_2024_ppsurf", "erler_philipp-2016-femfluid-prakt", "erler_philipp-2017-phd", "erler-2020-p2s", "erler-2025-lidarscout", "fan-2014-scfl", "ferschin-1992-kons", "fiedler-2009-php", "fleiss-2015-da", "GAHR-2013-AGM", "gamsjaeger-2022-proc", "gersthofer-2016-sosob", "gervautz-1989-sol1", "gervautz-1993-use", "griessmair-1989-def1", "groeller-1992-frac", "groeller-1995-mod", "Groeller-1995-SDC", "Grossfurtner-2023-paego", "Guerrero-2014-GRF", "Guerrero-2014-TPS", "guerrero-2015-lsp", "HECHER-2017-HDY", "hiess-1992-comb", "hofer_kerstin-2023-sketch2model", "honic-2020-w78", "HU-2017-ETM", "HUMMEL-2001-MSE", "Ilcik_2015_LAY", "ilcik-2010-ps", "ilcik-2013-cipmi", "ilcik-2014-cgbpmi", "ilcik-2016-cmssg", "ilcik-2021-xmas", "kapferer_2021_advancing", "karnik-09-shapegrammar", "Kellner-2021-DA", "kendlbacher-2016", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koenigsberger-2024-msu", "komon-2025-webigeo", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kraehsmaier-dsc", "kreuzer-2016-isf", 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The goal of our approach is to provide a novel way of generating smoothly animated word clouds to show changes in word frequency via font size. Unlike existing methods, a compact layout, inspired by the popular word cloud generation tool Wordle, is preserved during animation and implemented using web technologies.Word size changes in time are also illustrated via color and word rotation. 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"puenguentzky-2014-ht", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "raidou_vcbm14", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "rasch-2016-imgses", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "rautek-2009-vmv", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Reisacher_Matthias_CPW", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "sbardellati_ba_2018", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "sifuentes-2018-crowd", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "sorger-2017-thesis", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "textures-3d-printing", "field_id": "supervisor", "ordernum": 2 }, { "publ_id": "Thurner-2005-IVR", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "vad_2015_phd", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Viola_Ivan_2013_HQ3", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Viola-05-Smart", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "viola-2007-ort", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Viola-Pondering-2017", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "vis-foa", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldin-2017-thesis", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Wihann_2017", "field_id": "supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=171", "__class": "Author" }, { "id": 1400, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Martin", "lastname": "Seyfert", "searchname": "Martin Seyfert", "is_teacher": false, "name": "Martin Seyfert", "publications": [ "seyfert-2017" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "seyfert-2017", "field_id": "lecturer", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1400", "__class": "Author" } ], "booktitle": "Proceedings of SCCG 2017", "date_from": "2017-05-15", "date_to": "2017-05-17", "doi": "10.1145/3154353.3154358", "editor": "ACM", "event": "SCCG 2017", "isbn": "978-1-4503-5107-2", "lecturer": [ { "id": 1400, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Martin", "lastname": "Seyfert", "searchname": "Martin Seyfert", "is_teacher": false, "name": "Martin Seyfert", "publications": [ "seyfert-2017" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "seyfert-2017", "field_id": "lecturer", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1400", "__class": "Author" } ], "location": "Mikulov", "research_areas": [ { "id": "IllVis", "drupal_id": 4131, "name": "Illustrative Visualization", "short_abstract": "In this research area, we develop rendering methods that are inspired by scientific illustrations, in order to make complex biological information more intuitive to understand and more pleasant to read.", "abstract": "Scientific illustration is concerned with researching ways in which complex biological and medical data can be abstracted in order to convey a desired information that would otherwise be impossible or hard to retrieve from the original data. Illustrators apply such techniques, for instance, to present non-important parts of an organ in a simplified way, while using detailed representations to put the focus of attention on a region where a tumor might be situated.\n\nTo identify such meaningful visual abstractions for visualization, their effectiveness for human perception and cognition has to be assessed, and they have to be formalized in order to make them applicable in rendering algorithms. In this project, we try to advance the understanding of procedural visual abstraction of complex physiological processes that describe the complex machinery of biological life.", "website": "https://www.cg.tuwien.ac.at/research/area/IllVis", "teaser": { "name": "teaser.jpg", "path": "research_area:IllVis", "type": "image/jpeg", "size": 34861, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/IllVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "antes-2026-maa", "Antonini2020", "Balabanian-2010-IIV", "Balduz_01", "Bayat_2019", "Bechtold2020", "Birkeland-2012-IMC", "brandstaetter_01", "bruckner-2005-ICV", "bruckner-2006-ICE", "bruckner-2007-STF", "bruckner-2008-IIV", "bruckner-2010-HVC", "bruckner-2010-IFC", "cellVIEW_2015", "Chen-Information-2016", "Deutsch-2018", "Dhanoa_2021", "Dhanoa2024", "dietrich-2016-viseq2", 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"Manczarski-2016", "Matusich-2017-01", "Mautner 2020", "Mayr-2017-1", "Melo_2018_11", "Meusburger_2020", "Miao_2019", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao2018Dimsum", "Michl_2017_CSV", "mindek-2015-mc", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-2019-mci", "mindek-xmas-card-2016", "Moellinger_Christian_IDE2", "Niedermayer_2018", "Ortner_PhD", "Ortner2020", "pahr-2021-vologram", "Panayotov", "patel_daniel_2007_IRSD", "Pauschenwein_2022", "Peter_2012_AIV", "plank-2017-sldg", "prost-2016-molecule", "purgathofer-2008-cgi", "Radwan-2017-Occ", "Rautek-2007-SLI", "Rautek-2008-IDS", "Rautek-2008-VF", "Reichinger_2016", "Reichinger_Fuhrmann_2016", "Reisacher_Matthias_CPW", "Reisacher2016", "Riegelnegg_2019", "rippl-2023-atg", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "schindler_2020vis", "schmidlehner2021", "scholz_2021", "Schrempf_2020", "schultes_lampi", "seyfert-2017", "sikachev-2010-ill_vis_vol_ren", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "Spechtenhauser_Florian_2016", "stappen_2017_animatedcomic", "Stoll2020", "sturl_2016_dynlabels", "Swoboda2020", "szabo_patrik-2022-tour", "takahashi-2019-acdt", "Thomas-2018", "TR-186-2-07-08", "Troidl_2021", "Troidl_2022", "tut-eg-2006", "tut-siggraph-2006", "tut-vis-2006", "tut-vis-2007", "Unger2020", "Vasileva_2022", "Viola_Ivan_2013_SVA", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "viola-evr", "Viola-Pondering-2017", "Viola-vistutillustrativevis", "Waldin_Nicholas_2016_Colormaps", "waldin-2019-ccm", "Waldner_2017_11", "Wihann_2017", "Woschizka_2021", "wu-2019-bmc", "wu-2019-report", "Zaufel_2021", "zechmeister2020", "Zeng_2021", "Zusag-2017-Bach" ], "projects": [ "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=IllVis", "__class": "ResearchArea" } ], "keywords": [ " tag cloud, animated, dynamic, time-varying, word cloud " ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 642, "image_height": 297, "name": "seyfert-2017-image.bmp", "type": "image/bmp", "size": 572670, "path": "Publication:seyfert-2017", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/seyfert-2017/seyfert-2017-image.bmp", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/seyfert-2017/seyfert-2017-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "seyfert-2017-paper.pdf", "type": "application/pdf", "size": 2618363, "path": "Publication:seyfert-2017", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/seyfert-2017/seyfert-2017-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/seyfert-2017/seyfert-2017-paper:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "illvisation", "workgroup_id": "vis", "drupal_id": 4171, "drupal_path": "/research/projects/illvisation", "name": "Visual Computing: Illustrative Visualization", "name_de": null, "short_title": "illvisation", "website": null, "status": "active", "short_abstract": "

The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/

\r\n\r\n

Prototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/

\r\n\r\n

cellVIEW

\r\n\r\n

cellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.

\r\n\r\n

Invited Talks

\r\n\r\n

18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness

\r\n", "abstract": "

The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/

\r\n\r\n

Prototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/

\r\n\r\n

cellVIEW

\r\n\r\n

cellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.

\r\n\r\n

Invited Talks

\r\n\r\n

18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness

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However, such animations have to be manually authored in 3D modeling software, a time consuming task that has to be repeated from scratch for every new data set, and requires a high level of expertise in illustration, animation, and biology. We therefore propose metamorphers: a set of operations for defining animation states as well as the transitions to them in the form of re-usable story telling templates. The re-usability is two-fold. Firstly, due to their modular nature, metamorphers can be re-used in different combinations to create a wide range of animations. Secondly, due to their abstract nature, metamorphers can be re-used to re-create an intended animation for a wide range of compatible data sets. Metamorphers thereby mask the low level complexity of explicit animation specifications by exploiting the inherent properties of the molecular data, such as the position, size, and hierarchy level of a semantic data subset.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 6011, "image_height": 1167, "name": "sorger_2017_metamorphers-teaser.png", "type": "image/png", "size": 2870066, "path": "Publication:sorger_2017_metamorphers", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/sorger_2017_metamorphers/sorger_2017_metamorphers-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/sorger_2017_metamorphers/sorger_2017_metamorphers-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1072, 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have to deal with complex and large data collections and simulations. Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n", "website": "https://www.cg.tuwien.ac.at/research/area/BioVis", "teaser": { "name": "teaser.png", "path": "research_area:BioVis", "type": "image/png", "size": 16330957, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/BioVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "amirkhanov-2019-manylands", "byska-2019-mdfc", "cellVIEW_2015", "cmolik-2020-tvcg", "Dietrich_1", "dietrich-2016-viseq2", "Ehlers_PhD", "ehlers-2025-ait", "eschner-2023-ims", "eschner-blur-2022", "Escribano_2017", "Furmanova_2018", "Gehrer-2017", "Gehrer-2017-molmach", "glinzner-2016-tex", "Halladjian_2020", "kapferer-2017-godot", "klein_2017_IM", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koch-2018-sso", "Kolesar-Fractional-2016", "kolesar-ivan-2014-polymers", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kozlikova-Visualization-2016b", "Krone2016VABC", "Kugler_2019", "lemuzic_2015_timelapse", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lipp-2017-mgpu", "lipp-2017-vulkan", "Manczarski-2016", "manylands_award", "Miao_2019", "miao_inria_2017", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-xmas-card-2016", "Mitterhofer_2017", "nguyen_2020-covid", "Nowak_2020", "raidou_2019_springer", "raidou_shonan167", "raidou2018visualflatter", "rasch-2016-imgses", "Reisacher2016", "rinortner_susanne-2019-vpicc", "Sarkis_2021", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2013-neuromap", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "stappen_2017_animatedcomic", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "trautner-2018-imd", "unger-2019_vcp", "vad_2015_phd", "vad_viktor-2017-WVE", "vad-2016-bre", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "waldin-2019-ccm", "waldner-2014-af", "Weissenboeck_2019", "wu-2017-dagstuhl", "wu-2018-metabo", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg" ], "projects": [ "BioNetIllustration", "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=BioVis", "__class": "ResearchArea" }, { "id": "IllVis", "drupal_id": 4131, "name": "Illustrative Visualization", "short_abstract": "In this research area, we develop rendering methods that are inspired by scientific illustrations, in order to make complex biological information more intuitive to understand and more pleasant to read.", "abstract": "Scientific illustration is concerned with researching ways in which complex biological and medical data can be abstracted in order to convey a desired information that would otherwise be impossible or hard to retrieve from the original data. Illustrators apply such techniques, for instance, to present non-important parts of an organ in a simplified way, while using detailed representations to put the focus of attention on a region where a tumor might be situated.\n\nTo identify such meaningful visual abstractions for visualization, their effectiveness for human perception and cognition has to be assessed, and they have to be formalized in order to make them applicable in rendering algorithms. In this project, we try to advance the understanding of procedural visual abstraction of complex physiological processes that describe the complex machinery of biological life.", "website": "https://www.cg.tuwien.ac.at/research/area/IllVis", "teaser": { "name": "teaser.jpg", "path": "research_area:IllVis", "type": "image/jpeg", "size": 34861, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/IllVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "antes-2026-maa", "Antonini2020", "Balabanian-2010-IIV", "Balduz_01", "Bayat_2019", "Bechtold2020", "Birkeland-2012-IMC", "brandstaetter_01", "bruckner-2005-ICV", "bruckner-2006-ICE", "bruckner-2007-STF", "bruckner-2008-IIV", "bruckner-2010-HVC", "bruckner-2010-IFC", "cellVIEW_2015", "Chen-Information-2016", "Deutsch-2018", "Dhanoa_2021", "Dhanoa2024", "dietrich-2016-viseq2", "donabauer_2019_1", "eg-tut2005-iv", "eschner-2023-ims", "Essler2022", "gangl-2018-gpsart", "Gehrer_Daniel_CUI", "Gehrer-2017-molmach", "gerl-2006-vhi", "Gogel2020", "Groeller_2011_IPV", "Groeller_2016_I3", "Groeller_2016_I6", "Groeller_2016_I7", "Groeller_2016_I8", "Groeller_V1_2020", "groeller-2006-ivt", "groeller-2007-fci", "groeller-2008-irs", "Groeller-2010-IFI", "gruber-2025-vps", "Halladjian_2020", "haushofer-2018-skinning", "Heim_2020", "horvath-2018-ism", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "Knapp_2017_CVR", "Koeppel2020", "kolesar-ivan-2014-polymers", "Konev-FCV2018", "Koszticsak-2017-ewt", "Kouril_2017_11", "kouril-2020-hyperlabels", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "kroesl_x_card_2017", "Lackner_2022", "Langer_Edith_IR1", "lawonn-2018-illvisstar", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "LeMuzic_2016_PhD", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "Leutschacher_2022", "ludwig-2012-MT", 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Usually, some form of highlighting is used, such as a clearly distinct color or a border around the item. Flicker can also be very salient, but is often perceived as annoying. In this paper, we explore high frequency flicker (60 to 72 Hz) to guide the user's attention in an image. At such high frequencies, the critical flicker frequency (CFF) threshold is reached, which makes the flicker appear to fuse into a stable signal. However, the CFF is not uniform across the visual field, but is higher in the peripheral vision at normal lighting conditions. Through experiments, we show that high frequency flicker can be easily detected by observers in the peripheral vision, but the signal is hardly visible in the foveal vision when users directly look at the flickering patch. We demonstrate that this property can be used to draw the user's attention to important image regions using a standard high refresh-rate computer monitor with minimal visible modifications to the image. In an uncalibrated visual search task, users could in a crowded image easily spot the specified search targets flickering with very high frequency. They also reported that high frequency flicker was distracting when they had to attend to another region, while it was hardly noticeable when looking at the flickering region itself.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1461, "drupal_id": 1003, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/NicholasWaldin", "firstname": "Nicholas", "lastname": "Waldin", "searchname": "Nicholas Waldin", "is_teacher": false, "name": "Nicholas Waldin", "publications": [ "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2016_Colormaps", "Waldin_Nicholas_2016_Individualization", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2017-thesis" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1461", "__class": "Author" }, { "id": 1110, "drupal_id": 625, "orcid_id": 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In computer graphics we produce images, videos, visualizations and other content that is perceived by humans. By understanding the limits of human perception, we can design and optimize rendering algorithms that perfectly fit users' needs, tailor visualizations to make data better understandable, and effectively draw the user's attention to important information.

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"groeller-2004-sci", "groeller-2005-dia", "Groeller-2010-CVC", "Groeller-2010-IFI", "Groeller-2010-IVVI", "Groeller-2011-HSH", "Groeller-2017-ARTORW", "Groeller-2017-AVC", "Groeller-2017-IVAMCS", "Groeller-2017-PTPMD", "Groller_2021-12-03", "Gronde_2008", "Grorller-2010-IVV", "grossmann_2019_pelvisrunner_poster", "Grossmann_MA", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", "grossmann-thesis", "gruber-2025-vps", "Gruenauer-2011-CAT", "Gschwantner_2011_AMQ", "gundacker-2020-wlm", "Gurbat_2011_SBS", "gusenbauer-2018", "gusenbauer-2018", "gusenbauer-2018-P", "gutekunst_2019", "Hadwiger-2002-Fas", "haidacher_2010_statTF", "haidacher-2004-FVV", "haidacher-2005-MND", "haidacher-2007-idr", "haidacher-2008-vcbm", "haidacher-2011-MSM", "haidacher-2011-phd", "haidacher-2011-VAM", "Hainoun2019", "Halladjian_2020", "hanzl-2011", "hartl-2008-vcd", "hartmann-2005-adv", "haushofer-2018-skinning", "Heim_2020", "Heim_2021", "Heim-2017", "heim-2024-accustripes", "heim-gall-2020-dde", "heinzl_2006_RSDVCDM", "heinzl-2006-rep", "heinzl-2008-sam", "Heinzl2021", "Herghelegiu-2012-BPV", "herzberger-2023-swv", "herzberger-2024-roh", "Hirsch_Christian_2015_ABL", "Hladuvka-2002-Exp", "hladuvka-2002-exploiting", "Hochmayr_Manuel_2015_PSE", "hochmayr_manuel-2011-VoRMD", "Hochpoechler_2016_VR", "horvath-2018-ism", "hromniak-2019-vcn", "huber-2025-eed", "Iijima-2020-iV", "indirectBiasLanguageModels-2023", "irendorfer-2024-uat", "irger-2023-ves", "Ismail-2018", "jank-2022-cbf", "Kanitsar-2002-CPR", "Kanitsar-2003-Adva", "Kanitsar-2003-Dem", "Kanitsar-2004-Dia", "Kanitsar-thesis", "kapferer-2017-godot", "Karall2017CVAB", "Karall2018_2", "karimov-2013-vivisection", "karimov-2015-HD", "karimov-2016-GIVE", "karimov-2016-SD", "keglevic_schulz-2011-MB", "Kehrer-2008-hyp", "Kehrer-2010-mom", "kehrer-2011-vai", "kehrer-2012-mod", "kehrer-2013-IVA", "kehrer-2013-SBC", "Kehrer-2013-STAR", "Kehrer-2014-CSD", "kerbl-2024-ah3", "kimmersdorfer-fancyMaps-2023", "Kinkelin_2009", "Kinkelin-2011-VR", "Klaus2024", "Kleber-2004-TFE", "klein_2017_IM", "klein_2019_MSA_Poster", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "Klein_Tobias_2015TIV", "klein-thesis", "Knapp_2017_CVR", "knapp_michael_2004_MAS", "knapp-2004-semi", "koch_bernhard_2018-1", "koch-2018-sso", "koehle-2013-sgv", "koeppel-2021", "Koeppel2020", "Kohlmann-2007-EBV", "kohlmann-2007-livesync", "kohlmann-2008-lse", "kohlmann-2009-cp", "kohlmann-2009-lssl", "kolesar-ivan-2014-polymers", "Kolter_2021", "komon-2025-dco", "komon-2025-webigeo", "komon-2025-webigeo", "komon-kimmersdorfer-2025-weBIGeo", "Konyha_2013_IVA", "korpitsch_thorsten-2019", "korpitsch-2020-cescg", "Korpitsch-2020-wscg", "korpitsch-2021-lov", "Koszticsak-2017-ewt", "Kouril_2017_11", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2018-LoL", "kouril-2018-LoL", "kouril-2020-hyperlabels", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kovacs_PhD", "krakhofer-2015", "Krone2016VABC", "kuehschelm-2005-adv", "Kugler_2019", "Kuroko-2020-iV", "Labschuetz_Matthias_2015_JIT", "Labschuetz_Matthias_2016_AHD", "Labschuetz_Matthias_2016_JIT", "Labschuetz_Matthias_2016_JITT", "Lackner_2022", "LaCruz2004", "Ladstaedter-2009-sim", "Langer_Edith_IR1", "Langer_Maximillian_DMV", "Laschober-2018", "lawonn-2018-illvisstar", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "LeMuzic_2016_PhD", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lemuzic-mindek-sorger-cgfcc", "Leutschacher_2022", "li-2019-gdc", "lie-2009-cri", "lipp-2017-mgpu", "lipp-2017-vulkan", "lippeck-2022-mna", "liu-2014-ac", "lkoell-2014", "ludwig-2012-MT", "Machegger2018DTI", "magg-2021-dva", "magg2021", "mahler-2021-mdar", "major-2010-mrf", "malan_fluoro", "malik-2007-FP", "malik-2009-CVFA", "malik-thesis", "Manczarski-2016", "Marek06", "Maricic_2013_VFE", "martorell2022", "maruyama-2019-iv", "Masopust_2018", "Masterthesis-Viola", "Matkovic_Kresimir_2015_", "matt-2023-vae", "matt-2024-cvil", "matt-2025-scv", "matt-masterthesis", "Mattausch-2003-ISL", "Mattausch-2003-SIE", "Mattausch-2003-Str", "Matusich-2017-01", "Mautner 2020", "Mayr-2017-1", "mayr-2021-wec", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "Mazza_2020", "Mazza_2021_05", "meka-2024-lpi", "Melo_2018_11", "Meusburger_2020", "Miao_2015_VCBM", "Miao_2019", "Miao_Haichao_2015_VQC", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_plitvice_2018", "miao_thesis_2019", "miao_tvcg_2017", "miao_tvcg_2018", "miao_tvcg_2018", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "Michl_2017_CSV", "mindek_peter-2012-visgroupproj", "mindek_peter-2014-cs_kaust", "mindek-2013-cs_cvut", "mindek-2013-csl", "mindek-2013-pel", "mindek-2014-mcs", "mindek-2014-vivi_cvut", "mindek-2015-mc", "mindek-2015-mctalk", "mindek-2016-utah-talk", "mindek-2017-dsn", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-2019-mci", "mindek-thesis", "mistelbauer_2013_SIV", "Mistelbauer_2021", "Mistelbauer_Gabriel_2015_NHR", "Mistelbauer_Gabriel_2016", "mistelbauer-2010-pvv", "mistelbauer-2012-cr", "mistelbauer-2012-ssv", "mistelbauer-2013-cfa", "mistelbauer-2015-abvv", "Mitterhofer_2017", "mizuno-2019-eurovis", "Mlejnek_2004_PF", "Mlejnek_2005_AOEPF", "Mlejnek_2006_MVOA", "Mlejnek-2004-Int", "Mlejnek-2004-ITVAC", "Mlinaric-2015-MT", "Moellinger_Christian_IDE2", "moerth_eric-2016-3DF", "moerth-2018-tpose", "monitzer_2008_FluSi", "Morar_2012_ISB", "Muehlbacher_diss_2018", "mueller-2009-ivs", "Muigg_2011_ISI", "Muigg_2011_VC", "Muigg-2008-four", "muigg-2012-svr", "musleh-2024-conan", "muth-2026-clouds", "Neumann-2002-Fea", "nguyen_2020-covid", "Niedermayer_2018", "Novotny_2013_ASVD", "Nowak_2020", "Nowak_2021", "Oancea_2018_1", "Oancea_Stefan_2016_VOT", "Oancea2018OAK", "oeltze-2013-tut", "opitz-2009-cvv", "Ortner_PhD", "Ortner2020", "Pahr_PhD", "pahr-2021-vologram", "pahr-2024-ieo", "pahr-2024-squishicalization", "pahr-2025-holographs", "pahr-2025-nodkant", "Pahr2020", "Pajer_2012_VoM", "Panayotov", "papantonakis-2024-rmf", "Parzer_2013_IIG", "patel_2009_MC", "patel_daniel_2007_IRSD", "patel-2008-tsa", "patel-2009-evr", "patel-2011-PEA", "Pauschenwein_2022", "Peter_2012_AIV", "Pezenka-2016-MT", "Pfahler_David_2015_IPI", "Pfahler-2016-MT", "PH-2011-LDS", "phd-viola", "Philipp_Hochhauser_2023", "Pilizar_-2020-bachelor", "piringer-2009-hds", "Plank_Pascal_2015_HVP", "plank-2017-sldg", "PMI_AR_2012", "pointner_simon-2020", "polatsek-2018-stv", "polatsek-2018-stv", "Pramerdorfer-2011-PAV", "preim-2009-sve", "Presch_2020", "Priselac2021", "puehringer-2009-sbm", "puenguentzky-2014-ht", "Purchase-2020-gd", "raidou_2018_bladderrunner", "raidou_2019_pelvisrunner", "raidou_2019_preha", "raidou_2019_springer", "raidou_2020Onc", "raidou_EuroVis15", "raidou_eurovis16", "raidou_miccai16", "raidou_pingu2020", "raidou_previs2021", "raidou_RO2019", "raidou_shonan167", "raidou_slicedice", "raidou_star2019", "raidou_vcbm14", "raidou_vis14", "raidou_vis15", "raidou_visgap2020", "raidou2018_rv3", "raidou2018visualflatter", "raidou2019_prsps", "rasch-2016-imgses", "Rau08", "Rautek_Peter_2014_TUC", "Rautek_Peter_2014_VSA", "rautek-2005-dvr", "Rautek-2007-O3D", "Rautek-2007-SLI", "Rautek-2008-IDS", "Rautek-2008-kav", "Rautek-2008-VF", "rautek-2009-vmv", "RAUTEK06", "Rautek06Vis", "Rautek06VMLS", "rautek2010", "Red_Andreas_2015_FFT", "Reh_Andreas_VoP", "reh-2013", "reina-2020-mtv", "Reisacher_Matthias_CPW", "Reisacher2016", "Reiter_2009_IXIA", "Reiter2017CVAP", "Rezk06Vis", "Ribicic_2012_SUS", "Ribicic_2012_VAS", "Ribicic-2010-CRS", "Riegelnegg_2019", "rinortner_susanne-2019-vpicc", "rinortner_susanne-2019-vpicc", "Rippberger_2019", "rippl-2023-atg", "ritzberger-2010-nar", "Ropinski-2012-UBT", "rozana-2026-vcfd", "rraidou_clinical", "rraidou_EG17", "rraidou_phdbook", "rsabin-2013", "ruiz-2008-OVR", "ruiz-2008-SEV", "samoul-2019-cnp", "Sanjin_Rados_RV", "Sarkis_2021", "Sbardellati-2019-vcbm", "Sbardellati-2019-vcbm", "sbardellati-2021-eveos", "scharsach-2005-adv", "Schernthaner-2017-MCP", "schindler_2020vis", "Schindler-2022-eurovis", "schindler2020", "schleicher-2011-VLSC", "Schmidlehner_Sandra_SbC", "schmidlehner2021", "schmidt-2011-mt", "schmidt-phd", "schmidt-phd", "schoellhuber-2008-asc", "scholz_2021", "Schrempf_2018", "Schrempf_2020", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "schuh-2018-mesh-blending", "schultes_lampi", "Schulze_Florian_2013_CMI", "schwankl-2013-smis", "seyfert-2017", "shakhova-2023-atp", "sietzen-2019-wnn", "sietzen-2019-wnn", "sietzen-2021-perturber", "sietzen-2022-vacnnr", "sietzen-ifv-2019", "sifuentes-2018-crowd", "SifuentesGangl2017FIS", "sikachev_peter_2010_STLCI", "sikachev_peter-2011-dfc", "sikachev_peter-2011-incshad", "sikachev_peter-2011-metavis", "sikachev_peter-2011-protovis", "sikachev-2010-DFC", "sikachev-2010-ill_vis_vol_ren", "Sippl_Sebastian_EFG", "smiech-2018-tei", "Smisek_Michal_A3D", "Sollboeck_2011_FSS", "sollboeck-2011", "Solteszova-2009-VQN", "solteszova-2010-MOS", "Solteszova2016", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "sorger-2019-odn", "sorger-2021-egonet", "Soros_AVN_2011", "Soros-AV-2010", "Spechtenhauser_Florian_2016", "spegel-gruenberger-2020", "Spelitz2020", "spoerk-2010-hpgpu", "Stabel_2012_UDM", "stappen_2017_animatedcomic", "Staudacher_2022", "staudacher_florian-2016-topo3d", "stehno-2011-RVD", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "STEINLECHNER-2019-ICT", "StickmanMax-shoetta-kampfer", "stoff-2025-pvu", "stoff-concepMap-2021", "StrakaVis2004", "stritzel2022", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "suntinger-2008-etet", "suntinger-2008-tet", "Swoboda_Nicolas_VIT", "Swoboda2020", "szabo_patrik-2022-tour", "szabo-thesis", "takahashi-2019-acdt", "tekaya-2025-amo", "tekaya-2025-amo", "termeer-2006-000", "termeer-2007-covicad", "termeer-2008-scmr", "termeer-2008-vis", "termeer-2009-cvc", "termeer-2009-scmr", "textures-3d-printing", "thesis-kronsteiner", "thesis-tekaya", "Thomas-2018", "Thurner-2005-IVR", "toth-2007-ndd", "TR-186-2-05-01", "TR-186-2-05-02", "TR-186-2-05-03", "TR-186-2-05-04", "TR-186-2-05-06", "TR-186-2-05-07", "TR-186-2-05-08", "TR-186-2-06-01", "TR-186-2-06-02", "TR-186-2-06-03", "TR-186-2-06-04", "TR-186-2-07-02", "TR-186-2-07-03", "TR-186-2-07-04", "TR-186-2-07-05", "TR-186-2-07-06", "TR-186-2-07-07", "TR-186-2-07-08", "TR-186-2-07-10", "TR-186-2-07-11", "TR-186-2-07-12", "TR-186-2-08-01", "TR-186-2-08-02", "TR-186-2-08-03", "TR-186-2-08-04", "TR-186-2-08-05", "TR-186-2-08-06", "TR-186-2-08-07", "TR-186-2-08-08", "TR-186-2-08-10", "TR-186-2-08-11", "TR-186-2-08-12", "TR-186-2-08-14", "TR-186-2-09-01", "TR-186-2-15-03", "TR1862162", "Tramberger_2018", "Tramberger2017BCS", "Trautner_Thomas_2014_VAE", "trautner-2018-imd", "trautner-2018-imd", "travnicek-2017-thm", "Trenkwalder-2004-MAR", "tretyak-2025-tacmedvr", "Troidl_2019", "Troidl_2021", "Troidl_2022", "turner-aso", "tut-eg-2006", "tut-siggraph-2006", "tut-vis-2006", "tut-vis-2007", "tweebo-2014", "ulschmid-2024-reo", "ulschmid-2025-apc", "unger_2017", "unger-2019_vcp", "Unger2020", "unterguggenberger-2024-fropo", "usul-thesis", "vad_2015_phd", "Vad_Viktor_2015_RVV", "vad-2016-bre", "vaico", "varchola_andrej-2012-fetoscopic", "Vasileva_2022", "Vasileva-2018", "vessel2003", "Viola_2013_IDV", "Viola_Ivan_2013_CAI", "Viola_Ivan_2013_D3D", "Viola_Ivan_2013_DC", "Viola_Ivan_2013_GS", "Viola_Ivan_2013_HQ3", "Viola_Ivan_2013_RMA", "Viola_Ivan_2013_RSb", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_DAC", "Viola_Ivan_IIP", "Viola_Ivan_UVP", "Viola_Ivan_VDP", "Viola-05-Smart", "Viola-2003-GPU", "Viola-2003-Har", "viola-2003-hbn", "Viola-2003-NON", "viola-2004-gbf", "Viola-2004-GPU", "viola-2004-har", "viola-2004-har2", "viola-2004-idv", "viola-2004-imp", "Viola-2004-ImpX", "Viola-2004-ImpX2", "viola-2005-imp", "viola-2006-FoA", "viola-evr", "Viola-Pondering-2017", "viola-popular-article-2006", "Viola-vistutillustrativevis", "vis-foa", "VisWeek-Tutorial-2012-Uncertainty", "vitruvian_2019", "voglreiter-2023-tro", "Vucenovic_2022", "vucini_2006", "vucini_2008_rnp", "vucini_2009", "vucini_erald-2007-FRI", "vucini-2009-phd", "vucini-2011", "Wagner_032017", "walchhofer_ar_flowmaps", "walchhofer-tso", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "Waldin_Nicholas_2017_FlickerObserver", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2017-thesis", "waldin-2019-ccm", "waldin-2019-ccm", "Waldner_2017_11", "Waldner_2017_11", "waldner-2013-facetCloudsGI", "waldner-2013-ubiWM", "waldner-2014-af", "waldner-2014-ghi", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "waser_2011_VSD", "Waser-2010-WL", "webGPU_aggregateVis-2023", "weiner_2011", "Weissenboeck_2019", "Weissenboeck_2019_PhD", "weissenboeck-2014", "Wihann_2017", "wolf-2023-cc", "wolf-2024-jhd", "Woschizka_2021", "wu-2017-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-shonan", "wu-2018-story", "wu-2019-bmc", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-smwp", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg", "wu-2021", "wu-2021-vi", "xmastree2002", "xmastree2005", "ymca", "YOGHOURDJIAN2019", "Zambal-2003-SWA", "zambal-2005-3dact", "Zaufel_2021", "zauner-2013-svkinect", "zechmeister2020", "Zeng_2021", "Zhu-2014-flowvis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Workgroup&id=vis", "__class": "Workgroup" }, { "id": "deskollage", "workgroup_id": "vis", "drupal_id": 4198, "drupal_path": "/research/projects/deskollage", "name": "Visual Information Foraging on the Desktop", "name_de": null, "short_title": "deskollage", "website": null, "status": "active", "short_abstract": "The goal of this project is to design and develop novel interactive visualization techniques to support knowledge workers in making sense of their unstructured, dynamic information collections. ", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. On the one hand, the studies show that, in some situations, interactive visualization can be less efficient than working with unprocessed text-based information. On the other hand, the studies also show that combining automatic data analysis with interactive visualization can lead to more unexpected findings, especially when exploring large data. The extent of manual information organization varies with the task: the less users know about the gathered information, the more automatic organization they expect. \n\nIn summary, this project contributed novel user interface concepts and design guidelines for user interfaces supporting information foraging and sensemaking. The techniques and study results were published at high-ranking peer-reviewed venues, and it can be expected that the findings of this project shape the way how users seek and organize their information in the future. \n\n", "start_date": "2015-12-01", "end_date": "2018-12-31", "leader_id": 1110, "logo": { "name": "logo.png", "path": "project:deskollage", "type": "image/png", "size": 331697, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/deskollage/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "T 752-N30", "comment": null } ], "research_areas": [ "InfoVis" ], "publications": [ "2019-ic", "byska-2019-mdfc", "casellato-2016-pkg", "cizmic-2018-evd", "donabauer-2015-asc", "dworschak-2016-szcm", "edlinger-2018-vwr", "georgiev-2019-cbg", "geymayer-2017-std", "gundacker-2020-wlm", "gusenbauer-2018", "hromniak-2019-vcn", "Koszticsak-2017-ewt", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "polatsek-2018-stv", "samoul-2019-cnp", "sietzen-2019-wnn", "sietzen-ifv-2019", "smiech-2018-tei", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "trautner-2018-imd", "unger-2019_vcp", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg" ], "url": "https://www.cg.tuwien.ac.at/research/projects/deskollage", "__class": "Project" }, { "id": "illvisation", "workgroup_id": "vis", "drupal_id": 4171, "drupal_path": "/research/projects/illvisation", "name": "Visual Computing: Illustrative Visualization", "name_de": null, "short_title": "illvisation", "website": null, "status": "active", "short_abstract": "

The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/

\r\n\r\n

Prototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/

\r\n\r\n

cellVIEW

\r\n\r\n

cellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.

\r\n\r\n

Invited Talks

\r\n\r\n

18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness

\r\n", "abstract": "

The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/

\r\n\r\n

Prototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/

\r\n\r\n

cellVIEW

\r\n\r\n

cellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.

\r\n\r\n

Invited Talks

\r\n\r\n

18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness

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The visual story telling contest motivated us to describe the process of bringing this complex volumetric data \"to life\". We scripted the visual story directly within the current build of our multi-scale visualization. The entire video is therefore rendered in real time. This enabled us to directly show the steps involved in the rendering of our final visualization based on the actual data and the actual algorithms that are applied. The various effects in the video are therefore parameter variables for existing multi-scale visualization functions that change over time. The final result of our visualization was inspired by a rendering of the reference 3D model that was created by a scientific illustrator. The challenge that we overcome in our visualization was to create a rendering of the original data at stable 30 frames per second that matches the offline rendered illustration in visual quality, which helps to clarify the complex 3D arrangements of the inner components of the cell.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 960, "image_height": 540, "name": "mindek-2017-virtualcell-teaser.png", "type": "image/png", "size": 332614, "path": "Publication:mindek-2017-virtualcell", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/mindek-2017-virtualcell/mindek-2017-virtualcell-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/mindek-2017-virtualcell/mindek-2017-virtualcell-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, 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"Wihann_2017", "field_id": "supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=171", "__class": "Author" } ], "note": "submitted to the Pacific Vis 2017 Storytelling Contest", "research_areas": [ { "id": "BioVis", "drupal_id": 4127, "name": "Biological Data Visualization", "short_abstract": "In this research area, we develop new visualization techniques to support biologists in data analysis and create visualizations to disseminate scientific discoveries in biology.", "abstract": "In modern biological research domain experts have to deal with complex and large data collections and simulations. Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n", "website": "https://www.cg.tuwien.ac.at/research/area/BioVis", "teaser": { "name": "teaser.png", "path": "research_area:BioVis", "type": "image/png", "size": 16330957, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/BioVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "amirkhanov-2019-manylands", "byska-2019-mdfc", "cellVIEW_2015", "cmolik-2020-tvcg", "Dietrich_1", "dietrich-2016-viseq2", "Ehlers_PhD", "ehlers-2025-ait", "eschner-2023-ims", "eschner-blur-2022", "Escribano_2017", "Furmanova_2018", "Gehrer-2017", "Gehrer-2017-molmach", "glinzner-2016-tex", "Halladjian_2020", "kapferer-2017-godot", "klein_2017_IM", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koch-2018-sso", "Kolesar-Fractional-2016", "kolesar-ivan-2014-polymers", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kozlikova-Visualization-2016b", "Krone2016VABC", "Kugler_2019", "lemuzic_2015_timelapse", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lipp-2017-mgpu", "lipp-2017-vulkan", "Manczarski-2016", "manylands_award", "Miao_2019", "miao_inria_2017", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-xmas-card-2016", "Mitterhofer_2017", "nguyen_2020-covid", "Nowak_2020", "raidou_2019_springer", "raidou_shonan167", "raidou2018visualflatter", "rasch-2016-imgses", "Reisacher2016", "rinortner_susanne-2019-vpicc", "Sarkis_2021", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2013-neuromap", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "stappen_2017_animatedcomic", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "trautner-2018-imd", "unger-2019_vcp", "vad_2015_phd", "vad_viktor-2017-WVE", "vad-2016-bre", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "waldin-2019-ccm", "waldner-2014-af", "Weissenboeck_2019", "wu-2017-dagstuhl", "wu-2018-metabo", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg" ], "projects": [ "BioNetIllustration", "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=BioVis", "__class": "ResearchArea" }, { "id": "IllVis", "drupal_id": 4131, "name": "Illustrative Visualization", "short_abstract": "In this research area, we develop rendering methods that are inspired by scientific illustrations, in order to make complex biological information more intuitive to understand and more pleasant to read.", "abstract": "Scientific illustration is concerned with researching ways in which complex biological and medical data can be abstracted in order to convey a desired information that would otherwise be impossible or hard to retrieve from the original data. Illustrators apply such techniques, for instance, to present non-important parts of an organ in a simplified way, while using detailed representations to put the focus of attention on a region where a tumor might be situated.\n\nTo identify such meaningful visual abstractions for visualization, their effectiveness for human perception and cognition has to be assessed, and they have to be formalized in order to make them applicable in rendering algorithms. In this project, we try to advance the understanding of procedural visual abstraction of complex physiological processes that describe the complex machinery of biological life.", "website": "https://www.cg.tuwien.ac.at/research/area/IllVis", "teaser": { "name": "teaser.jpg", "path": "research_area:IllVis", "type": "image/jpeg", "size": 34861, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/IllVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "antes-2026-maa", "Antonini2020", "Balabanian-2010-IIV", "Balduz_01", "Bayat_2019", "Bechtold2020", "Birkeland-2012-IMC", "brandstaetter_01", "bruckner-2005-ICV", "bruckner-2006-ICE", "bruckner-2007-STF", "bruckner-2008-IIV", "bruckner-2010-HVC", "bruckner-2010-IFC", "cellVIEW_2015", "Chen-Information-2016", "Deutsch-2018", "Dhanoa_2021", "Dhanoa2024", "dietrich-2016-viseq2", 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"d10027", "d10162", "d10164", "d10206", "d10214", "d10413", "d10450", "d10489", "d4328", "d4335", "d4534", "d9275", "d9282", "d9522", "d9555", "d9671", "d9951", "deskollage", "diagvis", "exvisation", "Illustrare", "illvisation", "KASI", "ManyViews", "NeuroViewer", "ProcessIllVis", "ProKeyAnim", "PVG", "Scale-VS", "Scenario Pool", "Semantic Steering", "Sim-CT", "Smart-CT", "Smile Analytics", "ViMaL", "VISAR" ], "research_areas": [ "BioVis", "IllVis", "InfoVis", "MedVis", "NetVis", "Perception", "VisMat", "VR" ], "publications": [ "2013_Viola_Ivan_2013_MTS", "2015-image-coll", "2017-kouril-illcell", "2019-ic", "AA2020", "aigner-2025-vhv", "alacruzECR2004", "alacruzVisSym2004", "Alharbi_2021", "Alsallakh_2012_RCW", "alsallakh-2009-iva", "altendorfer-2008-vts", "amabili2021", "amirkhanov_2012", "amirkhanov_2012heur", "amirkhanov-2011", "amirkhanov-2014-ama", "amirkhanov-2018-withteeth", "amirkhanov-2021-diss", "amirkhanov2010AMA", "ammer-2008-lst", "An-2018-CHI", "AndreUrsits_2013_APP", "antes-2023-vhv", "Antonini2020", "arbesser_ba_2023", "Artner-2004-Hig", "Artner-2005-Hig", "Artner-2005-Thesis", "audioflow", "Auzinger_Mistelbauer_2013_CSR", "balabanian-2007-ant", "balabanian-2008-hvv", "Balabanian-2010-IIV", "Balabanian-2010-PSDSV", "Balduz_01", "Basch_2011_ATA", "Bauer_David_2018", "Bauer_Johannes_2014_IWB", "bauer-2015-cbfd", "Bayat_2019", "bayer-2015-gapaot", "bbeer-2013", "Bechtold2020", "Beer_2011_DVE", "Beham_Michael_PSC", "beham-2014-cupid", "bernhard-2006-dvrcta", "bernhard-2014-GTOM", "bernhard-2016-gft", "Bernold_2019", "bernold-2019-epr", "bhore-2021-issac", "birkeland_aasmund_2014_pums", "Birkeland-2012-IMC", "BirsakHanzl-2009", "boeroendy-2022-uio", "boesch_2014_browserHistoryVis", "borgo-2013-gly", "borondy2022", "bouzari-thesis", "bramberger-3pv", "Brandorff-08-OV", "brandorff-2009-erv", "brandstaetter_01", "brandstaetter-2007-vosd", "Brandstaetter2020", "Braunsperger-2025_bsc", "breitenecker-2020-bct", "bront-2023-svo", "brucker-2010-RES", "Bruckner_Stefan_2015_VAS", "bruckner-2004-EVV", "bruckner-2005-AIV", "bruckner-2005-ATI", "bruckner-2005-ICV", "bruckner-2005-vid", "bruckner-2005-VIS", "bruckner-2006-EVV", "bruckner-2006-ICE", "bruckner-2007-EDF", "bruckner-2007-STF", "bruckner-2008-IIV", "bruckner-2008-IVV", "bruckner-2009-BVQ", "bruckner-2009-IVV", "bruckner-2010-HVC", "bruckner-2010-IFC", "bruckner-2010-ISM", "bruckner-2010-SES", "Bruckner-2012-VEA", "buerger_raphael_2006_3dpoly", "Buerger-2007-cmv", "Buerger-2007-eurovis", "buerger-2007-star", "bugnar-esk-2021", "burns-2007-fea", "bydlinski-2015-gapaot", "byska-2019-mdfc", "Cai_2018", "Caic2021", "Carata_2011_IVE", "carbesser-2013", "casellato-2016-pkg", "cellVIEW_2015", "cizmic-2018-evd", "cmolik-2020-tvcg", "Cornel_2020", "Cornel_Daniel_2015_VOC", "Cornel2016CFM", "coto-2005-MAC", "Cruz-thesis", "Csebfalvi-2002-FPVF", "Csebfalvi-2002-SBICG", "Csebfalvi-2002-Smo", "Csebfalvi-2012-IOM", "Csuk_2011", "daae-lampe-2010-dif", "dataset-christmastree", "dataset-present", "dataset-stagbeetle", "Deutsch-2018", "Dhanoa_2021", "dhanoa-2025-ave", "Dhanoa2024", "Diehl_2015", "Diehl_2021", "Diehl-2017-Albero", "Dietrich_1", "dietrich-2016-viseq2", "diss-thesis-bratislava", "diss-thesis-magdeburg", "diss-thesis-siegen", "djuric-2020-wvo", "donabauer_2019_1", "donabauer-2015-asc", "draeger-2005-chain", "dworschak-2016-szcm", "dworschak-2016-szcm", "dworschak-2024-aml", "Eckelt_2017", "Eckelt_2018_01", "Edi_2019_10_01", "edlinger-2018-vwr", "eg-tut2005-iv", "Ehlers_PhD", "ehlers-2023-iro", "ehlers-2024-mmm", "ehlers-2024-vgs", "ehlers-2025-ait", "Eichner2022", "eitler-2024-sos", "eiweck-hnv-2021", "ellhotka-2025-ipo", "emsenhuber-2008-vhd", "erler-2025-lidarscout", "eschner-2023-evl", "eschner-2023-ims", "eschner-2025-ide", "eschner-blur-2022", "Escribano_2017", "Essler2022", "EuroVis2018-ShortPapers-Karall", "EuroVis2018-ShortPapers-Reiter", "facial2004", "Fechter_2011_DBS", "filipovic-2014-dect", "FISCHL-2012-CTASEG", "fmistelbauer-2014-ad", "fmistelbauer-2014-adict", "Ford-2012-HRV", "fourousan2021", "freiler-2008-ste", "fritz-2009-ieq", "Froehler_Berhnard_2015_ESM", "froschauer-2009-iod", "Fruehstueck_Anna_2015_DOM", "fuchs_raphael_2007_par", "fuchs_vhml", "fuchs-2008-del", "fuchs-vortex", "furmanova_2020", "gadllah_2016", "Gadllah_Hani_2016", "gall_2016", "Gall_2017", "gall_alexander_2016BA", "gall-2025-marv", "Gall2020", "Gall2021", "gangl-2018-gpsart", "Ganglberger-2022-cg", "ganglberger2019", "Ganuza", "Ganuza_2015", "Ganuza_MJ_2015_AVe", "Ganuza_ML_2015_ISA", "Ganuza-2017-IVCSGM", "Gavrilescu_2011_VGP", "gavrilescu-2008-vsc", "gavrilescu-2009-postrend", "Gavrilescu-2010-CIE", "Gehrer_Daniel_CUI", "Gehrer-2017", "Gehrer-2017-molmach", "georgiev-2019-cbg", "gerl-2006-vhi", "geymayer-2017-std", "Gietl_2020", "Gillmann2021", "glanznig-2009-LAMC", "glinzner-2016-tex", "goel-2024-rdr", "Gogel2020", "gostler-2015-3dp", "grammatikaki-2025-htr", "grammatikaki-thesis", "grimm-2004-arefined", "GRIMM-2004-FDMX-P", "grimm-2004-memory", "GRIMM-2004-PPC", "grimm-2004-volume", "Groeller_2011_CVC", "Groeller_2011_CW", "Groeller_2011_GBC", "Groeller_2011_HP", "Groeller_2011_HSU", "Groeller_2011_IPV", "Groeller_2011_IVP", "Groeller_2011_NR", "Groeller_2011_NSM", "Groeller_2011_VCD", "Groeller_2011_VSD", "Groeller_2011_VSD", "Groeller_2011_VSD", "Groeller_2011_VSS", "Groeller_2012_KAV", "Groeller_2012_VBP", "Groeller_2012_ViV", "Groeller_2012_VV", "Groeller_2014_CaQ", "Groeller_2014_CQV", "Groeller_2014_CV", "Groeller_2014_RWA", "Groeller_2014_STC", "Groeller_2014_UPS", "Groeller_2014_VND", "Groeller_2016_I2", "Groeller_2016_I7", "Groeller_2016_I8", "Groeller_2016_P2", "Groeller_2016_P4", "Groeller_2016_P6", "Groeller_2016_P7", "Groeller_2021_11", "Groeller_2021_BVM", "Groeller_2021-10", "Groeller_Edi_2013_TVC", "Groeller_Edi_2013_VCQ", "Groeller_Edi_2013TVCK", "Groeller_Edi_VKA", "Groeller_Eduard_2014_THS", "Groeller_Eduard_2014_TSP", "Groeller_Eduard_2014_UCT", "Groeller_Eduard_2015_SMV", "Groeller_Eduard_2015_TCU", "Groeller_V1_2020", "Groeller_V2_2020", "Groeller_V3_2020", "Groeller_V42020", "Groeller_V5_2020", "groeller-2004-efficient", "groeller-2004-imp", "groeller-2004-sci", "groeller-2005-dia", "Groeller-2010-CVC", "Groeller-2010-IFI", "Groeller-2010-IVVI", "Groeller-2011-HSH", "Groeller-2017-ARTORW", "Groeller-2017-AVC", "Groeller-2017-IVAMCS", "Groeller-2017-PTPMD", "Groller_2021-12-03", "Gronde_2008", "Grorller-2010-IVV", "grossmann_2019_pelvisrunner_poster", "Grossmann_MA", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", "grossmann-thesis", "gruber-2025-vps", "Gruenauer-2011-CAT", "Gschwantner_2011_AMQ", "gundacker-2020-wlm", "Gurbat_2011_SBS", "gusenbauer-2018", "gusenbauer-2018", "gusenbauer-2018-P", "gutekunst_2019", "Hadwiger-2002-Fas", "haidacher_2010_statTF", "haidacher-2004-FVV", "haidacher-2005-MND", "haidacher-2007-idr", "haidacher-2008-vcbm", "haidacher-2011-MSM", "haidacher-2011-phd", "haidacher-2011-VAM", "Hainoun2019", "Halladjian_2020", "hanzl-2011", "hartl-2008-vcd", "hartmann-2005-adv", "haushofer-2018-skinning", "Heim_2020", "Heim_2021", "Heim-2017", "heim-2024-accustripes", "heim-gall-2020-dde", "heinzl_2006_RSDVCDM", "heinzl-2006-rep", "heinzl-2008-sam", "Heinzl2021", "Herghelegiu-2012-BPV", "herzberger-2023-swv", "herzberger-2024-roh", "Hirsch_Christian_2015_ABL", "Hladuvka-2002-Exp", "hladuvka-2002-exploiting", "Hochmayr_Manuel_2015_PSE", "hochmayr_manuel-2011-VoRMD", "Hochpoechler_2016_VR", "horvath-2018-ism", "hromniak-2019-vcn", "huber-2025-eed", "Iijima-2020-iV", "indirectBiasLanguageModels-2023", "irendorfer-2024-uat", "irger-2023-ves", "Ismail-2018", "jank-2022-cbf", "Kanitsar-2002-CPR", "Kanitsar-2003-Adva", "Kanitsar-2003-Dem", "Kanitsar-2004-Dia", "Kanitsar-thesis", "kapferer-2017-godot", "Karall2017CVAB", "Karall2018_2", "karimov-2013-vivisection", "karimov-2015-HD", "karimov-2016-GIVE", "karimov-2016-SD", "keglevic_schulz-2011-MB", "Kehrer-2008-hyp", "Kehrer-2010-mom", "kehrer-2011-vai", "kehrer-2012-mod", "kehrer-2013-IVA", "kehrer-2013-SBC", "Kehrer-2013-STAR", "Kehrer-2014-CSD", "kerbl-2024-ah3", "kimmersdorfer-fancyMaps-2023", "Kinkelin_2009", "Kinkelin-2011-VR", "Klaus2024", "Kleber-2004-TFE", "klein_2017_IM", "klein_2019_MSA_Poster", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "Klein_Tobias_2015TIV", "klein-thesis", "Knapp_2017_CVR", "knapp_michael_2004_MAS", "knapp-2004-semi", "koch_bernhard_2018-1", "koch-2018-sso", "koehle-2013-sgv", "koeppel-2021", "Koeppel2020", "Kohlmann-2007-EBV", "kohlmann-2007-livesync", "kohlmann-2008-lse", "kohlmann-2009-cp", "kohlmann-2009-lssl", "kolesar-ivan-2014-polymers", "Kolter_2021", "komon-2025-dco", "komon-2025-webigeo", "komon-2025-webigeo", "komon-kimmersdorfer-2025-weBIGeo", "Konyha_2013_IVA", "korpitsch_thorsten-2019", "korpitsch-2020-cescg", "Korpitsch-2020-wscg", "korpitsch-2021-lov", "Koszticsak-2017-ewt", "Kouril_2017_11", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2018-LoL", "kouril-2018-LoL", "kouril-2020-hyperlabels", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kovacs_PhD", "krakhofer-2015", "Krone2016VABC", "kuehschelm-2005-adv", "Kugler_2019", "Kuroko-2020-iV", "Labschuetz_Matthias_2015_JIT", "Labschuetz_Matthias_2016_AHD", "Labschuetz_Matthias_2016_JIT", "Labschuetz_Matthias_2016_JITT", "Lackner_2022", "LaCruz2004", "Ladstaedter-2009-sim", "Langer_Edith_IR1", "Langer_Maximillian_DMV", "Laschober-2018", "lawonn-2018-illvisstar", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "LeMuzic_2016_PhD", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lemuzic-mindek-sorger-cgfcc", "Leutschacher_2022", "li-2019-gdc", "lie-2009-cri", "lipp-2017-mgpu", "lipp-2017-vulkan", "lippeck-2022-mna", "liu-2014-ac", "lkoell-2014", "ludwig-2012-MT", "Machegger2018DTI", "magg-2021-dva", "magg2021", "mahler-2021-mdar", "major-2010-mrf", "malan_fluoro", "malik-2007-FP", "malik-2009-CVFA", "malik-thesis", "Manczarski-2016", "Marek06", "Maricic_2013_VFE", "martorell2022", "maruyama-2019-iv", "Masopust_2018", "Masterthesis-Viola", "Matkovic_Kresimir_2015_", "matt-2023-vae", "matt-2024-cvil", "matt-2025-scv", "matt-masterthesis", "Mattausch-2003-ISL", "Mattausch-2003-SIE", "Mattausch-2003-Str", "Matusich-2017-01", "Mautner 2020", "Mayr-2017-1", "mayr-2021-wec", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "Mazza_2020", "Mazza_2021_05", "meka-2024-lpi", "Melo_2018_11", "Meusburger_2020", "Miao_2015_VCBM", "Miao_2019", "Miao_Haichao_2015_VQC", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_plitvice_2018", "miao_thesis_2019", "miao_tvcg_2017", "miao_tvcg_2018", "miao_tvcg_2018", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "Michl_2017_CSV", "mindek_peter-2012-visgroupproj", "mindek_peter-2014-cs_kaust", "mindek-2013-cs_cvut", "mindek-2013-csl", "mindek-2013-pel", "mindek-2014-mcs", "mindek-2014-vivi_cvut", "mindek-2015-mc", "mindek-2015-mctalk", "mindek-2016-utah-talk", "mindek-2017-dsn", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-2019-mci", "mindek-thesis", "mistelbauer_2013_SIV", "Mistelbauer_2021", "Mistelbauer_Gabriel_2015_NHR", "Mistelbauer_Gabriel_2016", "mistelbauer-2010-pvv", "mistelbauer-2012-cr", "mistelbauer-2012-ssv", "mistelbauer-2013-cfa", "mistelbauer-2015-abvv", "Mitterhofer_2017", "mizuno-2019-eurovis", "Mlejnek_2004_PF", "Mlejnek_2005_AOEPF", "Mlejnek_2006_MVOA", "Mlejnek-2004-Int", "Mlejnek-2004-ITVAC", "Mlinaric-2015-MT", "Moellinger_Christian_IDE2", "moerth_eric-2016-3DF", "moerth-2018-tpose", "monitzer_2008_FluSi", "Morar_2012_ISB", "Muehlbacher_diss_2018", "mueller-2009-ivs", "Muigg_2011_ISI", "Muigg_2011_VC", "Muigg-2008-four", "muigg-2012-svr", "musleh-2024-conan", "muth-2026-clouds", "Neumann-2002-Fea", "nguyen_2020-covid", "Niedermayer_2018", "Novotny_2013_ASVD", "Nowak_2020", "Nowak_2021", "Oancea_2018_1", "Oancea_Stefan_2016_VOT", "Oancea2018OAK", "oeltze-2013-tut", "opitz-2009-cvv", "Ortner_PhD", "Ortner2020", "Pahr_PhD", "pahr-2021-vologram", "pahr-2024-ieo", "pahr-2024-squishicalization", "pahr-2025-holographs", "pahr-2025-nodkant", "Pahr2020", "Pajer_2012_VoM", "Panayotov", "papantonakis-2024-rmf", "Parzer_2013_IIG", "patel_2009_MC", "patel_daniel_2007_IRSD", "patel-2008-tsa", "patel-2009-evr", "patel-2011-PEA", "Pauschenwein_2022", "Peter_2012_AIV", "Pezenka-2016-MT", "Pfahler_David_2015_IPI", "Pfahler-2016-MT", "PH-2011-LDS", "phd-viola", "Philipp_Hochhauser_2023", "Pilizar_-2020-bachelor", "piringer-2009-hds", "Plank_Pascal_2015_HVP", "plank-2017-sldg", "PMI_AR_2012", "pointner_simon-2020", "polatsek-2018-stv", "polatsek-2018-stv", "Pramerdorfer-2011-PAV", "preim-2009-sve", "Presch_2020", "Priselac2021", "puehringer-2009-sbm", "puenguentzky-2014-ht", "Purchase-2020-gd", "raidou_2018_bladderrunner", "raidou_2019_pelvisrunner", "raidou_2019_preha", "raidou_2019_springer", "raidou_2020Onc", "raidou_EuroVis15", "raidou_eurovis16", "raidou_miccai16", "raidou_pingu2020", "raidou_previs2021", "raidou_RO2019", "raidou_shonan167", "raidou_slicedice", "raidou_star2019", "raidou_vcbm14", "raidou_vis14", "raidou_vis15", "raidou_visgap2020", "raidou2018_rv3", "raidou2018visualflatter", "raidou2019_prsps", "rasch-2016-imgses", "Rau08", "Rautek_Peter_2014_TUC", "Rautek_Peter_2014_VSA", "rautek-2005-dvr", "Rautek-2007-O3D", "Rautek-2007-SLI", "Rautek-2008-IDS", "Rautek-2008-kav", "Rautek-2008-VF", "rautek-2009-vmv", "RAUTEK06", "Rautek06Vis", "Rautek06VMLS", "rautek2010", "Red_Andreas_2015_FFT", "Reh_Andreas_VoP", "reh-2013", "reina-2020-mtv", "Reisacher_Matthias_CPW", "Reisacher2016", "Reiter_2009_IXIA", "Reiter2017CVAP", "Rezk06Vis", "Ribicic_2012_SUS", "Ribicic_2012_VAS", "Ribicic-2010-CRS", "Riegelnegg_2019", "rinortner_susanne-2019-vpicc", "rinortner_susanne-2019-vpicc", "Rippberger_2019", "rippl-2023-atg", "ritzberger-2010-nar", "Ropinski-2012-UBT", "rozana-2026-vcfd", "rraidou_clinical", "rraidou_EG17", "rraidou_phdbook", "rsabin-2013", "ruiz-2008-OVR", "ruiz-2008-SEV", "samoul-2019-cnp", "Sanjin_Rados_RV", "Sarkis_2021", "Sbardellati-2019-vcbm", "Sbardellati-2019-vcbm", "sbardellati-2021-eveos", "scharsach-2005-adv", "Schernthaner-2017-MCP", "schindler_2020vis", "Schindler-2022-eurovis", "schindler2020", "schleicher-2011-VLSC", "Schmidlehner_Sandra_SbC", "schmidlehner2021", "schmidt-2011-mt", "schmidt-phd", "schmidt-phd", "schoellhuber-2008-asc", "scholz_2021", "Schrempf_2018", "Schrempf_2020", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "schuh-2018-mesh-blending", "schultes_lampi", "Schulze_Florian_2013_CMI", "schwankl-2013-smis", "seyfert-2017", "shakhova-2023-atp", "sietzen-2019-wnn", "sietzen-2019-wnn", "sietzen-2021-perturber", "sietzen-2022-vacnnr", "sietzen-ifv-2019", "sifuentes-2018-crowd", "SifuentesGangl2017FIS", "sikachev_peter_2010_STLCI", "sikachev_peter-2011-dfc", "sikachev_peter-2011-incshad", "sikachev_peter-2011-metavis", 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"publication_field": [ { "publ_id": "Kolesar-Fractional-2016", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "kolesar-ivan-2014-polymers", "field_id": "lecturer", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1192", "__class": "Author" } ], "number": "1", "pages": "851-860", "volume": "23", "research_areas": [ { "id": "BioVis", "drupal_id": 4127, "name": "Biological Data Visualization", "short_abstract": "In this research area, we develop new visualization techniques to support biologists in data analysis and create visualizations to disseminate scientific discoveries in biology.", "abstract": "In modern biological research domain experts have to deal with complex and large data collections and simulations. Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n", "website": "https://www.cg.tuwien.ac.at/research/area/BioVis", "teaser": { "name": "teaser.png", "path": "research_area:BioVis", "type": "image/png", "size": 16330957, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/BioVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "amirkhanov-2019-manylands", "byska-2019-mdfc", "cellVIEW_2015", "cmolik-2020-tvcg", "Dietrich_1", "dietrich-2016-viseq2", "Ehlers_PhD", "ehlers-2025-ait", "eschner-2023-ims", "eschner-blur-2022", "Escribano_2017", "Furmanova_2018", "Gehrer-2017", "Gehrer-2017-molmach", "glinzner-2016-tex", "Halladjian_2020", "kapferer-2017-godot", "klein_2017_IM", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koch-2018-sso", "Kolesar-Fractional-2016", "kolesar-ivan-2014-polymers", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kozlikova-Visualization-2016b", "Krone2016VABC", "Kugler_2019", "lemuzic_2015_timelapse", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lipp-2017-mgpu", "lipp-2017-vulkan", "Manczarski-2016", "manylands_award", "Miao_2019", "miao_inria_2017", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-xmas-card-2016", "Mitterhofer_2017", "nguyen_2020-covid", "Nowak_2020", "raidou_2019_springer", "raidou_shonan167", "raidou2018visualflatter", "rasch-2016-imgses", "Reisacher2016", "rinortner_susanne-2019-vpicc", "Sarkis_2021", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2013-neuromap", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "stappen_2017_animatedcomic", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "trautner-2018-imd", "unger-2019_vcp", "vad_2015_phd", "vad_viktor-2017-WVE", "vad-2016-bre", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "waldin-2019-ccm", "waldner-2014-af", "Weissenboeck_2019", "wu-2017-dagstuhl", "wu-2018-metabo", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg" ], "projects": [ "BioNetIllustration", "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=BioVis", "__class": "ResearchArea" } ], "keywords": [], "weblinks": [], "files": [], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2017/Kolesar-Fractional-2016/", "__class": "Publication" }, { "id": "mindek-2017-marion", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "Visualization Multi-Pipeline for Communicating Biology", "date": "2017", "abstract": "We propose a system to facilitate biology communication by developing a pipeline to support the instructional visualization of heterogeneous biological data on heterogeneous user-devices. Discoveries and concepts in biology are typically summarized with illustrations assembled manually from the interpretation and application of heterogenous data. The creation of such illustrations is time consuming, which makes it incompatible with frequent updates to the measured data as new discoveries are made. Illustrations are typically non-interactive, and when an illustration is updated, it still has to reach the user. Our system is designed to overcome these three obstacles. It supports the integration of heterogeneous datasets, reflecting the knowledge that is gained from different data sources in biology. After pre-processing the datasets, the system transforms them into visual representations as inspired by scientific illustrations. As opposed to traditional scientific illustration these representations are generated in real-time - they are interactive. The code generating the visualizations can be embedded in various software environments. To demonstrate this, we implemented both a desktop application and a remote-rendering server in which the pipeline is embedded. The remote-rendering server supports multi-threaded rendering and it is able to handle multiple users simultaneously. This scalability to different hardware environments, including multi-GPU setups, makes our system useful for efficient public dissemination of biological discoveries.\n", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "hidden", "image_width": 838, "image_height": 601, "name": "mindek-2017-marion-.png", "type": "image/png", "size": 395582, "path": "Publication:mindek-2017-marion", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/mindek-2017-marion/mindek-2017-marion-.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/mindek-2017-marion/mindek-2017-marion-:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 935, "drupal_id": 45, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/PeterMindek", "firstname": "Peter", "lastname": "Mindek", "searchname": "Peter Mindek", "is_teacher": false, "name": "Peter Mindek", "publications": [ "eschner-2023-ims", "karimov-2013-vivisection", "klein_2019_MSA_Poster", "klein_2019_PGG", "klein_2019_PMP", "koch_bernhard_2018-1", "kouril-2021-molecumentary", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lemuzic-mindek-sorger-cgfcc", "Miao_2019", "mindek_peter-2012-visgroupproj", "mindek_peter-2014-cs_kaust", "mindek-2013-cs_cvut", "mindek-2013-csl", "mindek-2013-pel", "mindek-2014-mcs", "mindek-2014-vivi_cvut", "mindek-2015-mc", "mindek-2015-mctalk", "mindek-2016-utah-talk", "mindek-2017-dsn", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-2019-mci", "mindek-tedx", "mindek-thesis", "mindek-xmas-card-2014", "mindek-xmas-card-2016", "nguyen_2020-covid", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "TR-186-2-15-03", "wu-2021", "wu-2021-vi", "xmas-2012" ], "publications_first": [], "project_leader": [], "publication_field": 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"journal": "IEEE Transactions on Visualization and Computer Graphics", "lecturer": [ { "id": 935, "drupal_id": 45, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/PeterMindek", "firstname": "Peter", "lastname": "Mindek", "searchname": "Peter Mindek", "is_teacher": false, "name": "Peter Mindek", "publications": [ "eschner-2023-ims", "karimov-2013-vivisection", "klein_2019_MSA_Poster", "klein_2019_PGG", "klein_2019_PMP", "koch_bernhard_2018-1", "kouril-2021-molecumentary", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lemuzic-mindek-sorger-cgfcc", "Miao_2019", "mindek_peter-2012-visgroupproj", "mindek_peter-2014-cs_kaust", "mindek-2013-cs_cvut", "mindek-2013-csl", "mindek-2013-pel", "mindek-2014-mcs", "mindek-2014-vivi_cvut", "mindek-2015-mc", "mindek-2015-mctalk", "mindek-2016-utah-talk", "mindek-2017-dsn", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-2019-mci", "mindek-tedx", "mindek-thesis", "mindek-xmas-card-2014", 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in data analysis and create visualizations to disseminate scientific discoveries in biology.", "abstract": "In modern biological research domain experts have to deal with complex and large data collections and simulations. Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n", "website": "https://www.cg.tuwien.ac.at/research/area/BioVis", "teaser": { "name": "teaser.png", "path": "research_area:BioVis", "type": "image/png", "size": 16330957, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/BioVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "amirkhanov-2019-manylands", "byska-2019-mdfc", "cellVIEW_2015", "cmolik-2020-tvcg", "Dietrich_1", "dietrich-2016-viseq2", "Ehlers_PhD", "ehlers-2025-ait", "eschner-2023-ims", "eschner-blur-2022", "Escribano_2017", "Furmanova_2018", "Gehrer-2017", "Gehrer-2017-molmach", "glinzner-2016-tex", "Halladjian_2020", "kapferer-2017-godot", "klein_2017_IM", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koch-2018-sso", "Kolesar-Fractional-2016", "kolesar-ivan-2014-polymers", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kozlikova-Visualization-2016b", "Krone2016VABC", "Kugler_2019", "lemuzic_2015_timelapse", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lipp-2017-mgpu", "lipp-2017-vulkan", "Manczarski-2016", "manylands_award", "Miao_2019", "miao_inria_2017", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-xmas-card-2016", "Mitterhofer_2017", "nguyen_2020-covid", "Nowak_2020", "raidou_2019_springer", "raidou_shonan167", "raidou2018visualflatter", "rasch-2016-imgses", "Reisacher2016", "rinortner_susanne-2019-vpicc", "Sarkis_2021", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2013-neuromap", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "stappen_2017_animatedcomic", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "trautner-2018-imd", "unger-2019_vcp", "vad_2015_phd", "vad_viktor-2017-WVE", "vad-2016-bre", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "waldin-2019-ccm", "waldner-2014-af", "Weissenboeck_2019", "wu-2017-dagstuhl", "wu-2018-metabo", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg" ], "projects": [ "BioNetIllustration", "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=BioVis", "__class": "ResearchArea" }, { "id": "IllVis", "drupal_id": 4131, "name": "Illustrative Visualization", "short_abstract": "In this research area, we develop rendering methods that are inspired by scientific illustrations, in order to make complex biological information more intuitive to understand and more pleasant to read.", "abstract": "Scientific illustration is concerned with researching ways in which complex biological and medical data can be abstracted in order to convey a desired information that would otherwise be impossible or hard to retrieve from the original data. Illustrators apply such techniques, for instance, to present non-important parts of an organ in a simplified way, while using detailed representations to put the focus of attention on a region where a tumor might be situated.\n\nTo identify such meaningful visual abstractions for visualization, their effectiveness for human perception and cognition has to be assessed, and they have to be formalized in order to make them applicable in rendering algorithms. In this project, we try to advance the understanding of procedural visual abstraction of complex physiological processes that describe the complex machinery of biological life.", "website": "https://www.cg.tuwien.ac.at/research/area/IllVis", "teaser": { "name": "teaser.jpg", "path": "research_area:IllVis", "type": "image/jpeg", "size": 34861, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/IllVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "antes-2026-maa", "Antonini2020", "Balabanian-2010-IIV", "Balduz_01", "Bayat_2019", "Bechtold2020", "Birkeland-2012-IMC", "brandstaetter_01", "bruckner-2005-ICV", "bruckner-2006-ICE", "bruckner-2007-STF", "bruckner-2008-IIV", "bruckner-2010-HVC", "bruckner-2010-IFC", "cellVIEW_2015", "Chen-Information-2016", "Deutsch-2018", "Dhanoa_2021", "Dhanoa2024", "dietrich-2016-viseq2", "donabauer_2019_1", "eg-tut2005-iv", "eschner-2023-ims", "Essler2022", "gangl-2018-gpsart", "Gehrer_Daniel_CUI", "Gehrer-2017-molmach", "gerl-2006-vhi", "Gogel2020", "Groeller_2011_IPV", "Groeller_2016_I3", "Groeller_2016_I6", "Groeller_2016_I7", "Groeller_2016_I8", "Groeller_V1_2020", "groeller-2006-ivt", "groeller-2007-fci", "groeller-2008-irs", "Groeller-2010-IFI", "gruber-2025-vps", "Halladjian_2020", "haushofer-2018-skinning", "Heim_2020", "horvath-2018-ism", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "Knapp_2017_CVR", "Koeppel2020", "kolesar-ivan-2014-polymers", "Konev-FCV2018", "Koszticsak-2017-ewt", "Kouril_2017_11", "kouril-2020-hyperlabels", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "kroesl_x_card_2017", "Lackner_2022", "Langer_Edith_IR1", "lawonn-2018-illvisstar", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "LeMuzic_2016_PhD", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "Leutschacher_2022", "ludwig-2012-MT", "Manczarski-2016", "Matusich-2017-01", "Mautner 2020", "Mayr-2017-1", "Melo_2018_11", "Meusburger_2020", "Miao_2019", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao2018Dimsum", "Michl_2017_CSV", "mindek-2015-mc", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-2019-mci", "mindek-xmas-card-2016", "Moellinger_Christian_IDE2", "Niedermayer_2018", "Ortner_PhD", "Ortner2020", "pahr-2021-vologram", "Panayotov", "patel_daniel_2007_IRSD", "Pauschenwein_2022", "Peter_2012_AIV", "plank-2017-sldg", "prost-2016-molecule", "purgathofer-2008-cgi", "Radwan-2017-Occ", "Rautek-2007-SLI", "Rautek-2008-IDS", "Rautek-2008-VF", "Reichinger_2016", "Reichinger_Fuhrmann_2016", "Reisacher_Matthias_CPW", "Reisacher2016", "Riegelnegg_2019", "rippl-2023-atg", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "schindler_2020vis", "schmidlehner2021", "scholz_2021", "Schrempf_2020", "schultes_lampi", "seyfert-2017", "sikachev-2010-ill_vis_vol_ren", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "Spechtenhauser_Florian_2016", "stappen_2017_animatedcomic", "Stoll2020", "sturl_2016_dynlabels", "Swoboda2020", "szabo_patrik-2022-tour", "takahashi-2019-acdt", "Thomas-2018", "TR-186-2-07-08", "Troidl_2021", "Troidl_2022", "tut-eg-2006", "tut-siggraph-2006", "tut-vis-2006", "tut-vis-2007", "Unger2020", "Vasileva_2022", "Viola_Ivan_2013_SVA", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "viola-evr", "Viola-Pondering-2017", "Viola-vistutillustrativevis", "Waldin_Nicholas_2016_Colormaps", "waldin-2019-ccm", "Waldner_2017_11", "Wihann_2017", "Woschizka_2021", "wu-2019-bmc", "wu-2019-report", "Zaufel_2021", "zechmeister2020", "Zeng_2021", "Zusag-2017-Bach" ], "projects": [ "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=IllVis", "__class": "ResearchArea" }, { "id": "Rendering", "drupal_id": 4134, "name": "Rendering", "short_abstract": "In this area, we concentrate on algorithms that synthesize images to depict 3D models or scenes, often by simulating or approximating the physics of light.", "abstract": "The rendering of 3D models and scenes has been a major, long-standing challenge in computer graphics that can be divided into two major subfields. Real-time rendering refers to the real-time synthesis of images on commodity graphics hardware to facilitate interaction for visualizations or computer games. The field of physically based rendering focuses on algorithms that accurately simulate the physics of light for use in the movie industry, architectural visualizations, etc. Compared to real-time rendering methods, these algorithms generally require a considerable amount of time (i.e., hours up to days) to generate acceptable results.\n\nIn the context of real-time rendering, our work revolves around the development of algorithms to achieve higher visual quality. Furthermore, we work on techniques to accelerate physically based rendering algorithms to make them viable for interactive rendering. Another aspect of our research work revolves around tools that facilitate the work of content creators.", "website": "https://www.cg.tuwien.ac.at/research/area/Rendering", "teaser": { "name": "teaser.png", "path": "research_area:Rendering", "type": "image/png", "size": 5244928, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Rendering/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend" ], "publications": [ "2011scherzerE", "2018_Mautner_Praktikum", "ABG25", "Adorjan-2015", "agyemang-2021-bsdfproxyppg", "Ams25", "antes-g", "arikan-2014-pcvis", "arikan-2015-dmrt", "Artusi-2003-Del", "ASCHL-2022-OTV", "Auzinger_2012_AAA", "Auzinger_2012_GeigerCam", "Auzinger_2013_AnaVis", "Auzinger_2013_NSAA", "Auzinger_2013_SAR", "Auzinger_2014_DCGI", "Auzinger_2014_UJA", "Auzinger-2015-IST", "bagar2010", "balvan-g", "Bauer_Dominik_2018_VR", "BAUER-2024-PWG", "BAUER-2025-PCW", "bernhard-2011-bmtf", "bernhard-2014-GTOM", "bhagvat-09-frusta", "birsak-2013-sta", "Bittner-2001-Vis", "Bittner-2003-Vis", "Bittner-2004-CHC", "bittner-2005-egsr", "BITTNER-2009-AGVS", "BITTNER-2009-GEFOC", "bittner-2011-scc", "BOKSANSKY-2019-RTS", "brandmair-2025-rub", "brugger-2020-tdp", "brugger-2020-tsdpbr", "Brusi-2001-Opt", "CADIK-2006-IAQ", "CADIK-2008-EHD", "cardoso-2021-cost", "cardoso-2022-rtpercept", "cardoso-2024-r-c", "cardoso-thesis", "cech-2023-taa", "celarek_adam-2019-qelta", "CELAREK-2017-QCL", "CHARALAMBOS-2007-HLOD", "charpenay-2014-sgn", "Che-2025", "cline-09-poisson", "CORNEL-2017-FRS", "CORNEL-2019-IVF", "Derflinger-2026-RTTW2", "Devlin-2002-STA", "dodik-2017-pcbpt", "dworschak-2024-aml", "ecormier-nocca-2025-sls", "eichner-2024-erv", "eickmeyer-2027-tcd", "EISEMANN-2011-RTS", "EISEMANN-2012-ERT", "EISEMANN-2013-ERT", "elagabani-2025-ieh", "Erhardt_Seirlehner-2024-TamashiiIntegration", "ERLER-2017-HVR", "ESBERGER-2016-AHO", "ESCHNER-2019-GDT", "fink-2012-cg1", "Fischer-2018-sssvr", "FRAISS-2017-PCU", "FRAISS-2022-CGMM", "freude_2020_rs", "FREUDE-2015-phd", "freude-2023-prh", "freude-2023-sem", "freude-2025-iso", "freude-2025-ras", "GAMPER-2018-OSG", "GANTNER-2018-ARO", "GANTNER-2019-CRS", "gersthofer_2017_COP", "geyer-2018-apbf", "GIEGL-2006-QVS", "GIEGL-2007-FVS", "GIEGL-2007-QV1", "GIEGL-2007-UNP", "gilmutdinov-2022-aomlbwug", "glanz-2017-pbrcomparison", "goel-2024-rdr", "gramegna-rfr", "GRELAUD-2009-EPA", "GRIESHOFER-2018-GOS", "Grisenti-2026-HSHPG", "Groeller_2016_P3", "Grossfurtner-2023-paego", "Gruber2019", "guerrero-2008-sli", "Habel_07_xms", "Habel_08_SSH", "Habel_09_PGT", "Habel_2007_IAG", "Habel_2007_RTT", "Habel_2009_PhD", "Habel_2012_PSP", "Habel_LSN_2011", "Habel_RAV_2010", "Habel-09-RAT", "Habel-09-THB", "Habel-2010-EIN", "HAFNER-2015-FEM", "HANN_2022_IPT", "hasbay-2026-tfo", "havran-2005-egsr", "havran-2005-sccg", "havran-2006-tut", "hecher-2012-MH", "hecher-2014-MH", "heinz-2019-psi", "hladky-2022-QS", "hofer_kerstin-2023-sketch2model", "horvath_imp", "houska-2020-IPGM", "huber-2025-esl", "huerbe-2019-BA", "intel2016", "ioannis-2026-sro", "JAHRMANN-2013-IGR", "JAHRMANN-2015-GRASS", "JAHRMANN-2016-IGR", "JAHRMANN-2017-RRTG", "jeschke-05-AIP", "jeschke-05-ARI", "jeschke-05-ISTAR", "jeschke-09-praguetalk", "jeschke-09-rendering", "Jeschke-2002-LEMA", "Jeschke-2002-TDMR", "JESCHKE-2007-ISC", "jeschke-2010-diff", "jeschke-2011-est", "Jimenez_SSS_2015", "KAFKA-2014-19MRD", "Kathi-2018-VRB", "Keilman2022", "Kellner-2021-DA", "kendlbacher-2016", "kerbl_2019_planet_poster", "kerbl_2021_hdg", "kerbl-2020-improvencoding", "kerbl-2022-trienc", "kerbl-2024-ah3", "kimmersdorfer-2024-vcpr", "kimmersdorfer-fancyMaps-2023", "KLAUS-2020-PCC", "klein_2019_PHD", "klein_2019_PMP", "klein-2020-rtgi", "knecht_2013_RSM", "knecht_martin_2010_DIR", "knecht_martin_2012_BRDFEstimation", "knecht_martin_2012_RSMR", "knecht_martin_2013_ReflRefrObjsMR", "knecht_martin-2011-FPSPAR", "knecht-2007-ao", "knecht-2011-CBCM", "koch-2019-PR", "KOCH-2021-GVS", "KOCH-2021-GVSDA", "KOEPPEL-2025-Nearfield", "Koeppl-2023-DLO", "Komon2022", "Konev-FCV2018", "Kovacs_2017", "kovacs-2025-pf", "KREUZER-2015-DPA", "KREUZER-2017-PBF", "kristmann-2022-occ", "kristmann-2023-vkl", "KRISTMANN-24-JPG", "kroesl-2017-LiteMaker", "kroesl-2018-DC", "kroesl-2018-TVS", "kroesl-2019-ICthroughVR", "kroesl-2019-ThesisFF", "KROESL-2020-SVI", "kroesl-2020-XREye", "KUE11", "Kugler-2021", "Lan25", "leopold-2019-vox", "Liang-2023-TVR", "lipp-2019-rtxq3", "LIPP-2020-PHD", "lipp-2024-val", "Luidolt-2020-DA", "luidolt-2020-lightperceptionVR", "luksch_2020", "LUKSCH-2013-FLM", "LUKSCH-2014-RTR", "LUKSCH-2019-IGI", "Mantler-06-landscape", "MANTLER-2007-DMBBC", "matt2011", "MATTAUSCH-2006-AVC", "mattausch-2007-iav", "MATTAUSCH-2007-OSP", "mattausch-2008-CHC", "mattausch-2010-tao", "mattausch-2010-var", "Mattausch-2010-vcr", "MATTAUSCH-2012-EOV", "MATTAUSCH-2012-TIS", "MATTAUSCH-2013-FSBE", "MATTAUSCH-2015-CHCRT", "Mazza_2021_05", "Meier_2024_WIALT", "MEINDL-2015-OSR", "metzger-2024-smv", "mindek-2017-marion", "mindek-xmas-card-2016", "murturi_PGG", "muth-2026-clouds", "neumann-2006-gamma", "OPPITZ-2017-3DM", "oppitz-2023-ais", "OPPTIZ-2018-IVRL", "OTEPKA-2020-PPC", "ott-rgi", "ott-va", "panfili-2019-VAVR", "panfili-2021-myop", "PB-VRVis-2018-005", "pegrisch_2018_uvs", "PERNDORFER-2015-ECS", "pernsteiner-2022-msh", "pernsteinre_jakob_2020_eechc", "PETER-2023-PSW", "pichler_2022_fro", "pirraku-f", "pistellato-2023-elp", "pogrzebacz-2023-vkl", "pointner_michael-2017-baa", "preiner_2010_GIPC", "preiner_2017_phd", "preiner11IR", "preissegger-2025-vrh", "Preymann-2022-pytamashii", "probst-2023-para", "prost-2016-molecule", "PROST-2017-RTL", "PROST-2019-RTPAL", "Przemyslaw_Gora_2016_UVU", "purgathofer-2004-real", "purgathofer-2004-some", "Purgathofer-2005-Ros", "Purgathofer-2005-Tub", "Purgathofer-2006-VRVis", "radax-2008-ir", "Rainer_2017", "Rait2022", "Reisner_Irene_2013_R3D", "reznicek-2020-fpgaray", "ROEGNER-2014-TUI", "ROEGNER-2015-IBR", "roth_2021_vdst", "roth_vdi", "roth-2023-vlk", "rumpelnik_martin_2020_PRM", "Rumpelnik_Martin-2020-NPR", "rumpler_2019_PPC", "Rumpler-2019-PPC", "RUMPLER-2021-VOGL", "SAKAI-2015-EAPI", "sakai-2021-eif", "sakai-2024-asa", "sakai-2025-stater", "sakai-thesis", "schedl-2012-dof", "schedl-2013-gP4", "SCHEIBLAUER-2015-WFC", "scherzer_2010a", "Scherzer-2007-PCS", "SCHERZER-2008-FSR", "scherzer-2009-isvc", "SCHERZER-2012-TCM", "scherzer-eg2010", "scherzer-thesis", "scherzer2010b", "scherzer2010d", "scherzer2010e", "scherzer2011c", "scherzer2011d", "SCHOBER-2006-IVSA", "SCHUETZ-2015-HQP", "SCHUETZ-2016-POT", "schuetz-2018-PPC", "schuetz-2019-CLOD", "schuetz-2019-LCO", "SCHUETZ-2019-PCC", "SCHUETZ-2020-MPC", "schuetz-2020-PPC", "SCHUETZ-2021-DISS", "SCHUETZ-2021-PCC", "SCHUETZ-2022-PCC", "SCHUETZ-2023-LOD", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "schuetz-mb", "schwaerzler_2018_phd", "SCHWAERZLER-2012-FAS", "SCHWAERZLER-2013-FPCSS", "Schwengerer_Mathias-2022-BGL", "seczer-2025-vrs", "Semmelrath-2022-IRS", "seyr-2025-lbt", "silvana_2014", "sippl_tobias_2017_WPC", "SIPPL-2017-POS", "sorger-2015-litevis", "SSMW09", "stappen_SteFAS", "stappen-2019-vrs", "steinkellner-2024-dll", "STEINLECHNER-2019-APS", "STEINLECHNER-2019-ICT", "STREICHER-2022-DSLS", "STU-SR-25", "Sturn-2013-ST", "Szabo-2018-DA", "tatzgern-2020-sst", "Thann_2019_01", "themmer-2018-fbx", "tobler97_hsdasr", "TR 193-02-2019-4", "TR 193-2-2019-4", "TR-186-2-02-04", "TR-186-2-07-01", "TR-186-2-07-09", "TR-186-2-08-09", "TR-186-2-12-01", "traxler-1997-TRA", "Tucek_2018", "Tucek_Tom-2016-aai", "ulschmid-2025-apc", "ulschmid-phdthesis", "unterguggenberger-2020-fmvr", "unterguggenberger-2021-msh", "unterguggenberger-2022-vulkan", "unterguggenberger-2024-fropo", "VASCO-2019-EVR", "wagner-2024-par", "wallner-2015-ModelingRoutinization", "Wang-2016-BAC", "WEBER-2015-PRA", "WEBER-2015-PRA1", "weidlich_2009_REL", "weidlich-2009-dispersion", "weidlich-2009-thesis", "weinzierl_heigl-2017-wh14", 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"zsolnai-ist-invited-2014", "zsolnaifeher-2019-pme", "zsolnaifeher-2020-pme" ], "projects": [ "3DSpatialization", "d9259", "d9275", "d9555", "Desiree", "EVOCATION", "GameTools", "GPV", "Harvest4D", "Mofa", "OpenData", "PathSpace", "REPLICATE", "RESHADE", "Scanopy", "TERAPOINTS", "Treelumination" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Rendering", "__class": "ResearchArea" } ], "keywords": [ "Biological visualization", "remote rendering", "public dissemination" ], "weblinks": [ { "href": "https://vimeo.com/238851516", "caption": "VIS presentation", "description": null, "main_file": 0 } ], "files": { "1": { "description": null, "filetitle": "Paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "mindek-2017-marion-Paper.pdf", "type": "application/pdf", "size": 12037780, "path": "Publication:mindek-2017-marion", "url": 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The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/

\r\n\r\n

Prototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/

\r\n\r\n

cellVIEW

\r\n\r\n

cellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.

\r\n\r\n

Invited Talks

\r\n\r\n

18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness

\r\n", "abstract": "

The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/

\r\n\r\n

Prototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/

\r\n\r\n

cellVIEW

\r\n\r\n

cellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.

\r\n\r\n

Invited Talks

\r\n\r\n

18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness

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The study of such interactions often requires to track the molecules that enter or exit specific regions of the proteins. This is investigated with molecular dynamics simulations, producing the trajectories of thousands of water molecules during hundreds of thousands of time steps. To ease the exploration of such rich spatio-temporal data, we propose a novel workflow for the analysis and visualization of large sets of water-molecule trajectories. Our solution consists of a set of visualization techniques, which help biochemists to classify, cluster, and filter the trajectories and to explore the properties and behavior of selected subsets in detail. Initially, we use an interactive histogram and a time-line visualization to give an overview of all water trajectories and select the interesting ones for further investigation. Further, we depict clusters of trajectories in a novel 2D representation illustrating the flows of water molecules. These views are interactively linked with a 3D representation where we show individual paths, including their simplification, as well as extracted statistical information displayed by isosurfaces. The proposed solution has been designed in tight collaboration with experts to support specific tasks in their scientific workflows. They also conducted several case studies to evaluate the usability and effectiveness of our new solution with respect to their research scenarios. 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"firstname": "Eduard", "lastname": "Gröller", "searchname": "Eduard Gröller", "is_teacher": true, "name": "Eduard Gröller", "publications": [ "a-2001-ah", "a-2001-ahr", "a-2001-Rec", "Acquisto-1995-DCR", "alacruzECR2004", "Alharbi_2021", "Alsallakh_2012_RCW", "amabili-2024-smg", "amabili-2025-lpb", "amirkhanov_2012", "amirkhanov_2012heur", "amirkhanov_2013_AMA", "amirkhanov-2011", "amirkhanov-2014-ama", "amirkhanov-2017-cffet", "amirkhanov-2018-withteeth", "amirkhanov-2019-manylands", "amirkhanov2010AMA", "amirkhanov2020visual", "Antonini2020", "Artner-2004-Hig", "Artner-2005-Hig", "Auzinger_Mistelbauer_2013_CSR", "balabanian-2007-ant", "balabanian-2008-hvv", "balabanian-2008-tst", "Balabanian-2010-IIV", "Balabanian-2010-PSDSV", "Bartroli-2002-Pro", "Bartroli-2003-Geo", "Bartroli-2003-Non", "beham-2014-cupid", "Berger_2011_UAE", "Berger-1998-Col", "Berger-2000-Col", "Bruckner_Stefan_2015_VAS", "Bruckner-2003-The", "bruckner-2005-ICV", "bruckner-2005-vid", "bruckner-2005-VIS", 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"Groeller_2014_CaQ", "Groeller_2014_CQV", "Groeller_2014_CV", "Groeller_2014_RWA", "Groeller_2014_STC", "Groeller_2014_UPS", "Groeller_2014_VND", "Groeller_2016_I1", "Groeller_2016_I2", "Groeller_2016_I3", "Groeller_2016_I4", "Groeller_2016_I5", "Groeller_2016_I6", "Groeller_2016_I7", "Groeller_2016_I8", "Groeller_2016_P1", "Groeller_2016_P2", "Groeller_2016_P3", "Groeller_2016_P4", "Groeller_2016_P6", "Groeller_2016_P7", "Groeller_2021_11", "Groeller_2021_BVM", "Groeller_2021-10", "Groeller_Edi_2013_TVC", "Groeller_Edi_2013_VCQ", "Groeller_Edi_2013TVCK", "Groeller_Edi_VKA", "Groeller_Eduard_2014_THS", "Groeller_Eduard_2014_TSP", "Groeller_Eduard_2014_UCT", "Groeller_Eduard_2015_SMV", "Groeller_Eduard_2015_TCU", "Groeller_V1_2020", "Groeller_V2_2020", "Groeller_V3_2020", "Groeller_V42020", "Groeller_V5_2020", "groeller-1987-opt", "groeller-1988-duale", "groeller-1988-using", "groeller-1991-frac", "groeller-1991-temp", "groeller-1992-frac", "groeller-1992-fractals", "groeller-1992-fraktale", "groeller-1992-vis", "groeller-1993-acc", "groeller-1993-cha", "groeller-1993-coh", "groeller-1993-coh1", "groeller-1993-daten", "groeller-1993-dist", "groeller-1993-disto", "groeller-1993-eff", "groeller-1993-exp", "groeller-1993-frak", "groeller-1993-grund", "groeller-1993-oct", "Groeller-1994-AIV", "groeller-1994-appl", "Groeller-1994-AVT", "groeller-1994-coh", "Groeller-1994-CSA", "groeller-1994-ext", "Groeller-1994-HIS", "groeller-1994-hyper", "Groeller-1994-IDN", "groeller-1994-int", "Groeller-1994-ITV", "groeller-1994-mod", "Groeller-1994-MRN", "groeller-1994-tech", "groeller-1994-vis", "groeller-1995-appl", "groeller-1995-attract", "Groeller-1995-CCG", "groeller-1995-dyn", "Groeller-1995-GOW", "Groeller-1995-IED", "groeller-1995-inter", "groeller-1995-lok", "groeller-1995-mod", "groeller-1995-non", "Groeller-1995-SDC", "groeller-1995-vis", "groeller-1996-ACE", "groeller-1996-avn", "Groeller-1998-TunVis", "Groeller-1998-VAD", "Groeller-1998-VDS", "Groeller-1999-Dat", "Groeller-1999-Vis", "Groeller-2000-Vis", "Groeller-2001-IDV", "groeller-2002-anw", "Groeller-2002-Ins", "groeller-2002-med", "groeller-2002-wiss", "groeller-2003-fea", "groeller-2003-med", "groeller-2003-scie", "groeller-2003-vol", "groeller-2004-efficient", "groeller-2004-imp", "groeller-2004-sci", "groeller-2005-abs", "groeller-2005-dia", "groeller-2005-foc", "groeller-2005-imp", "groeller-2005-impo", "groeller-2005-proc", "groeller-2005-sma", "groeller-2005-smar", "groeller-2005-volg", "groeller-2006-cgf", "groeller-2006-civ", "groeller-2006-ivt", "groeller-2006-tvcg", "groeller-2007-csu", "groeller-2007-fci", "groeller-2007-mva", "groeller-2007-vis", "groeller-2007-visII", "groeller-2007-vws", "groeller-2008-att2", "groeller-2008-How", "groeller-2008-hsp", "groeller-2008-irs", "groeller-2008-kav2", "groeller-2008-kav3", "groeller-2008-kav4", "groeller-2008-lsy", "Groeller-2010-CVC", "groeller-2010-How", "Groeller-2010-IFI", "Groeller-2010-IVVI", "groeller-2010-PTT", "Groeller-2011-HSH", "Groeller-2017-AMOS", "Groeller-2017-ARTORW", "Groeller-2017-AVC", "Groeller-2017-IVAMCS", "Groeller-2017-PTPMD", "groeller-2022-iva", "groeller-2022-iva-1", "groeller-2022-ivd", "groeller-2023-ivd", "groeller-2023-siv", "groeller-2023-siv-1", "groeller-2023-siv-2", "groeller-2023-tfo", "groeller-2024-cui", "groeller-cvc-2009", "groeller-scv-2009", "groeller-svo-2009", "Groeller-thesis", "groeller-vks-2009", "Groller_2021-12-03", "Grorller-2010-IVV", "grossmann_2019_pelvisrunner_poster", "grossmann-2022-conceptSplatters", "Hadwiger-2003-MIP", "haidacher_2010_statTF", "haidacher-2008-vcbm", "haidacher-2011-MSM", "haidacher-2011-VAM", "Halladjian_2020", "Hauser-1999-SSI", "Hauser-2000-Tho", "Hauser-2000-Two", "Hauser-2000-TwoX", "Hauser-2002-SSI", "Hauser-2003-Acc", "Heim_2021", "heim-2024-accustripes", "heinzl_2006_RSDVCDM", "heinzl-2006-rep", "heinzl-2007-sem", "heinzl-2008-sam", "Herghelegiu-2012-BPV", "herzberger-2024-roh", 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"kohlmann-2008-lse", "kohlmann-2009-cp", "Korpitsch-2020-wscg", "kouril-2018-LoL", "kouril-2020-hyperlabels", "kouril-2021-molecumentary", "Labschuetz_Matthias_2015_JIT", "Labschuetz_Matthias_2016_JIT", "Labschuetz_Matthias_2016_JITT", "LaCruz-2004-NMF", "LaCruz2004", "lanzarotti-2025-viseps", "lee-2022-p", "Loeffelmann-1994-PSQ", "loeffelmann-1995-para", "Loeffelmann-1995-RTE", "loeffelmann-1996-CVA", "Loeffelmann-1996-DS3", "loeffelmann-1996-SVM", "Loeffelmann-1997-FV2", "Loeffelmann-1997-HSV", "Loeffelmann-1997-VPM", "Loeffelmann-1998-Enh", "Loeffelmann-1998-EVC", "Loeffelmann-1998-SMURF", "Loeffelmann-1998-VDS", "Loeffelmann-1998-Vis", "Loeffelmann-1998-Visu", "Loeffelmann-1999-SMU", "malik-2007-FP", "malik-2009-CVFA", "malik-2010-cvp", "manylands_award", "Matkovic-2002-Pro", "Mattausch-2003-SIE", "Mattausch-2003-Str", "Meinhart-1998-Tun", "Miao_2015_VCBM", "miao_2016_cgf", "Miao_2019", "miao_tvcg_2017", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "Milik-1997-GMMO", "Milik-1998-Geo", "mindek-2013-csl", "mindek-2013-pel", "mindek-2014-mcs", "mindek-2015-mc", "mindek-2017-dsn", "mindek-2017-marion", "Mistelbauer_2021", "Mistelbauer_Gabriel_2015_NHR", "mistelbauer-2012-cr", "mistelbauer-2012-ssv", "mistelbauer-2013-cfa", "Mlejnek_2004_PF", "Mlejnek_2005_AOEPF", "Mlejnek-2004-Int", "Mlejnek-2004-ITVAC", "Morar_2012_ISB", "Mroz-1998-Bri", "Mroz-1998-Sel", "Mroz-1998-SelX", "Mroz-1999-Adv", "Mroz-1999-IHQ", "Mroz-1999-MIP", "Mroz-1999-Real", "Mroz-1999-ReaX", "Mroz-2000-Int", "Mroz-2000-Mas", "Mroz-2000-MasX", "Mroz-2000-Rea", "Muigg_2011_VC", "muigg-2011-gpg", "musleh-2023-ugi", "Neumann-2000-Gra", "Neumann-2002-Fea", "oda-2025-artevoviewer", "ortner-2016-tunnel", "ortner-2016-visaware", "Ortner2020", "patel_2009_MC", "patel_daniel_2007_IRSD", "patel-2008-tsa", "patel-2009-kav", "patel-2010-SVV", "patel-2011-PEA", "Peter_2012_AIV", "piringer-2009-hds", "PMI_AR_2012", "preim-2009-sve", "purgathofer-1988-using", "Purgathofer-1994-CPI", "Purgathofer-1999-Gra", "raidou_2018_bladderrunner", "raidou_2019_pelvisrunner", "raidou_2019_preha", "raidou_slicedice", "raidou_visgap2020", "raidou2018visualflatter", "raidou2019_prsps", "rauer-zechmeister-2024-h3p", "Rautek_Peter_2014_TUC", "Rautek_Peter_2014_VSA", "Rautek-2007-O3D", "Rautek-2007-SLI", "Rautek-2008-IDS", "Rautek-2008-VF", "RAUTEK06", "Rautek06Vis", "Red_Andreas_2015_FFT", "reh-2013", "reh-2015-areh", "reina-2020-mtv", "Reiter_2009_IXIA", "Ribicic_2012_SUS", "Ribicic_2012_VAS", "roos-2007-mcp", "Ropinski-2012-UBT", "rsabin-2013", "Sarkis_2021", "Sbardellati-2019-vcbm", "Schernthaner-2017-MCP", "sikachev_peter-2011-dfc", "sikachev_peter-2011-incshad", "sikachev-2010-DFC", "solteszova-avp-2009", "sorger_2017_metamorphers", "sorger-2015-litevis", "sorger-2015-taxintec", "Soros_AVN_2011", "steinboeck-2018-lbg", "STEINLECHNER-2019-ICT", "Straka-2003-3DW", "Straka-2003-Apr", "Straka-2003-Bon", "Straka-2003-CTA", "Straka-2004-BSA", "Straka-2004-TVG", "StrakaVis2004", "suntinger-2008-etet", "suntinger-2008-tet", "szabo-2023-fig", "tanaka-2024-vor", "termeer-2007-covicad", "termeer-2008-scmr", "termeer-2008-vis", "termeer-2009-scmr", "Theussl-1999-MDH", "Theussl-2000-MWI", "Theussl-2001-ORS", "Theussl-2001-RIV", "Theussl-2002-RSH", "Theussl-2003-Rec", "toth-2007-ndd", "TR-186-2-05-01", "TR-186-2-05-02", "TR-186-2-05-03", "TR-186-2-05-04", "TR-186-2-05-06", "TR-186-2-05-07", "TR-186-2-05-08", "TR-186-2-06-01", "TR-186-2-06-02", "TR-186-2-06-03", "TR-186-2-06-04", "TR-186-2-07-02", "TR-186-2-07-03", "TR-186-2-07-04", "TR-186-2-07-05", "TR-186-2-07-06", "TR-186-2-07-07", "TR-186-2-07-08", "TR-186-2-07-10", "TR-186-2-07-11", "TR-186-2-07-12", "TR-186-2-08-01", "TR-186-2-08-02", "TR-186-2-08-03", "TR-186-2-08-04", "TR-186-2-08-05", "TR-186-2-08-06", "TR-186-2-08-07", "TR-186-2-08-08", "TR-186-2-08-10", "TR-186-2-08-11", "TR-186-2-08-12", "TR-186-2-08-13", "TR-186-2-08-14", "TR-186-2-09-01", "TR-186-2-15-03", "TR1862162", "tretyak-2025-tacmedvr", 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Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n", "website": "https://www.cg.tuwien.ac.at/research/area/BioVis", "teaser": { "name": "teaser.png", "path": "research_area:BioVis", "type": "image/png", "size": 16330957, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/BioVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "amirkhanov-2019-manylands", "byska-2019-mdfc", "cellVIEW_2015", "cmolik-2020-tvcg", "Dietrich_1", "dietrich-2016-viseq2", "Ehlers_PhD", "ehlers-2025-ait", "eschner-2023-ims", "eschner-blur-2022", "Escribano_2017", "Furmanova_2018", "Gehrer-2017", "Gehrer-2017-molmach", "glinzner-2016-tex", "Halladjian_2020", "kapferer-2017-godot", "klein_2017_IM", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koch-2018-sso", "Kolesar-Fractional-2016", "kolesar-ivan-2014-polymers", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kozlikova-Visualization-2016b", "Krone2016VABC", "Kugler_2019", "lemuzic_2015_timelapse", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lipp-2017-mgpu", "lipp-2017-vulkan", "Manczarski-2016", "manylands_award", "Miao_2019", "miao_inria_2017", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-xmas-card-2016", "Mitterhofer_2017", "nguyen_2020-covid", "Nowak_2020", "raidou_2019_springer", "raidou_shonan167", "raidou2018visualflatter", "rasch-2016-imgses", "Reisacher2016", "rinortner_susanne-2019-vpicc", "Sarkis_2021", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2013-neuromap", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "stappen_2017_animatedcomic", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "trautner-2018-imd", "unger-2019_vcp", "vad_2015_phd", "vad_viktor-2017-WVE", "vad-2016-bre", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "waldin-2019-ccm", "waldner-2014-af", "Weissenboeck_2019", "wu-2017-dagstuhl", "wu-2018-metabo", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg" ], "projects": [ "BioNetIllustration", "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=BioVis", "__class": "ResearchArea" }, { "id": "InfoVis", "drupal_id": 4128, "name": "Information Visualization and Visual Analytics", "short_abstract": "In this research area, our focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning. ", "abstract": "

Data and information created by various processes (e.g., simulations) is getting larger, and more and more complex. We use interactive visualization and analysis techniques to facilitate exploration of complex parameter spaces (e.g., to analyze and compare parameters for automotive engineering, reconstruction algorithms, or geometry generators) or unstructured information collections (e.g., annotated digital documents or image collections). Our research focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning.

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Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n", "website": "https://www.cg.tuwien.ac.at/research/area/BioVis", "teaser": { "name": "teaser.png", "path": "research_area:BioVis", "type": "image/png", "size": 16330957, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/BioVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "amirkhanov-2019-manylands", "byska-2019-mdfc", "cellVIEW_2015", "cmolik-2020-tvcg", "Dietrich_1", "dietrich-2016-viseq2", "Ehlers_PhD", "ehlers-2025-ait", "eschner-2023-ims", "eschner-blur-2022", "Escribano_2017", "Furmanova_2018", "Gehrer-2017", "Gehrer-2017-molmach", "glinzner-2016-tex", "Halladjian_2020", "kapferer-2017-godot", "klein_2017_IM", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koch-2018-sso", "Kolesar-Fractional-2016", "kolesar-ivan-2014-polymers", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kozlikova-Visualization-2016b", "Krone2016VABC", "Kugler_2019", "lemuzic_2015_timelapse", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lipp-2017-mgpu", "lipp-2017-vulkan", "Manczarski-2016", "manylands_award", "Miao_2019", "miao_inria_2017", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-xmas-card-2016", "Mitterhofer_2017", "nguyen_2020-covid", "Nowak_2020", "raidou_2019_springer", "raidou_shonan167", "raidou2018visualflatter", "rasch-2016-imgses", "Reisacher2016", "rinortner_susanne-2019-vpicc", "Sarkis_2021", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2013-neuromap", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "stappen_2017_animatedcomic", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "trautner-2018-imd", "unger-2019_vcp", "vad_2015_phd", "vad_viktor-2017-WVE", "vad-2016-bre", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "waldin-2019-ccm", "waldner-2014-af", "Weissenboeck_2019", "wu-2017-dagstuhl", "wu-2018-metabo", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg" ], "projects": [ "BioNetIllustration", "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=BioVis", "__class": "ResearchArea" } ], "keywords": [], "weblinks": [], "files": [], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2016/Kozlikova-Visualization-2016b/", "__class": "Publication" }, { "id": "sorger-2016-fowardabstraction", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "Illustrative Transitions in Molecular Visualization via Forward and Inverse Abstraction Transform", "date": "2016-09", "abstract": "A challenging problem in biology is the incompleteness of acquired information when visualizing biological phenomena. Structural biology generates detailed models of viruses or bacteria at different development stages, while the processes that relate one stage to another are often not clear. Similarly, the entire life cycle of a biological entity might be available as a quantitative model, while only one structural model is available. If the relation between two models is specified at a lower level of detail than the actual models themselves, the two models cannot be interpolated correctly. We propose a method that deals with the visualization of incomplete data information in the developmental or evolutionary states of biological mesoscale models, such as viruses or microorganisms. The central tool in our approach is visual abstraction. Instead of directly interpolating between two models that show different states of an organism, we gradually forward transform the models into a level of visual abstraction that matches the level of detail of the modeled relation between them. At this level, the models can be interpolated without conveying false information. After the interpolation to the new state, we apply the inverse transformation to the model’'s original level of abstraction. To show the flexibility of our approach, we demonstrate our method on the basis of molecular data, in particular data of the HIV virion and the mycoplasma bacterium.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2084, "image_height": 1027, "name": "sorger-2016-fowardabstraction-teaser.png", "type": "image/png", "size": 2349725, "path": "Publication:sorger-2016-fowardabstraction", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/sorger-2016-fowardabstraction/sorger-2016-fowardabstraction-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/sorger-2016-fowardabstraction/sorger-2016-fowardabstraction-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1072, "drupal_id": 1056, "orcid_id": null, 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"lemuzic-mindek-sorger-cgfcc", "Miao_2019", "mindek_peter-2012-visgroupproj", "mindek_peter-2014-cs_kaust", "mindek-2013-cs_cvut", "mindek-2013-csl", "mindek-2013-pel", "mindek-2014-mcs", "mindek-2014-vivi_cvut", "mindek-2015-mc", "mindek-2015-mctalk", "mindek-2016-utah-talk", "mindek-2017-dsn", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-2019-mci", "mindek-tedx", "mindek-thesis", "mindek-xmas-card-2014", "mindek-xmas-card-2016", "nguyen_2020-covid", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "TR-186-2-15-03", "wu-2021", "wu-2021-vi", "xmas-2012" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "bayer-2015-gapaot", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "bydlinski-2015-gapaot", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "eschner-blur-2022", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "Escribano_2017", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "gostler-2015-3dp", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "lemuzic-mindek-2016-viseq", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "liu-2014-ac", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "Manczarski-2016", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "mindek-2013-csl", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "mindek-2013-pel", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "mindek-2015-mc", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "mindek-2016-utah-talk", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "mindek-2017-marion", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "mindek-2018-fyi", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "schwankl-2013-smis", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "travnicek-2017-thm", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "travnicek-2017-thm", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "zauner-2013-svkinect", "field_id": "supervisor", "ordernum": 1 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=935", "__class": "Author" }, { "id": 1285, "drupal_id": 1146, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/TobiasKlein", "firstname": "Tobias", "lastname": "Klein", "searchname": "Tobias Klein", "is_teacher": false, "name": "Tobias Klein", "publications": [ "Alharbi_2021", "klein_2017_IM", "klein_2019_MSA_Poster", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "Klein_Tobias_2015TIV", "klein-2016-WCL", "klein-thesis", "koch_bernhard_2018-1", "Miao_2019", "mindek-2017-virtualcell", "mindek-2019-mci", "nguyen_2020-covid", "sorger-2016-fowardabstraction", "wu-2021", "wu-2021-vi" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "Escribano_2017", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Hochpoechler_2016_VR", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": 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"https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1379", "__class": "Author" }, { "id": 171, "drupal_id": 168, "orcid_id": "0000-0003-4248-6574", "website": "https://www.cg.tuwien.ac.at/staff/IvanViola", "firstname": "Ivan", "lastname": "Viola", "searchname": "Ivan Viola", "is_teacher": true, "name": "Ivan Viola", "publications": [ "2013_Viola_Ivan_2013_MTS", "Alharbi_2021", "Artner-2004-Hig", "Artner-2005-Hig", "balabanian-2007-ant", "balabanian-2008-hvv", "balabanian-2008-tst", "Balabanian-2010-IIV", "bernhard-2016-gft", "birkeland_aasmund_2014_pums", "Birkeland-2012-IMC", "boffi-2024-bagginghook", "bruckner-2005-vid", "bruckner-2010-HVC", "burns-2007-fea", "cellVIEW_2015", "Chen-Information-2016", "Cornel2016CFM", "Csebfalvi-2002-FPVF", "diss-thesis-bratislava", "diss-thesis-magdeburg", "diss-thesis-siegen", "eg-tut2005-iv", "Ford-2012-HRV", "Furmanova_2018", "Gehrer-2017-molmach", "Groeller-2017-PTPMD", "Hadwiger-2002-Fas", "Halladjian_2020", 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"viola-2006-FoA", "viola-2007-ort", "viola-evr", "Viola-Pondering-2017", "viola-popular-article-2006", "Viola-vistutillustrativevis", "vis-foa", "vitruvian_2019", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2016_Colormaps", "Waldin_Nicholas_2016_Individualization", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "waldner-2014-af", "waldner-2014-ghi", "wu-2018-metabo", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg", "wu-2021", "wu-2021-vi", "xmastree2005", "Zeng_2021" ], "publications_first": [], "project_leader": [ "Animated Cell Tab development", "exvisation", "Illustrare", "illvisation" ], "publication_field": [ { "publ_id": "2017-kouril-illcell", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Artner-2005-Thesis", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "balabanian-2009-mav", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "Balduz_01", "field_id": "supervisor", "ordernum": 0 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{ "publ_id": "miao_thesis_2019", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Mitterhofer_2017", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "moerth-2018-tpose", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Plank_Pascal_2015_HVP", "field_id": "supervisor", "ordernum": 2 }, { "publ_id": "plank-2017-sldg", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "puenguentzky-2014-ht", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "raidou_vcbm14", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "rasch-2016-imgses", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "rautek-2009-vmv", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Reisacher_Matthias_CPW", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "sbardellati_ba_2018", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "sifuentes-2018-crowd", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "sorger-2017-thesis", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "textures-3d-printing", "field_id": "supervisor", "ordernum": 2 }, { "publ_id": "Thurner-2005-IVR", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "vad_2015_phd", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Viola_Ivan_2013_HQ3", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Viola-05-Smart", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "viola-2007-ort", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Viola-Pondering-2017", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "vis-foa", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldin-2017-thesis", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Wihann_2017", "field_id": "supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=171", "__class": "Author" } ], "booktitle": "Eurographics Workshop on Visual Computing for Biology and Medicine (VCBM)", "editor": "S. Bruckner, B. Preim, and A. Vilanova", "location": "Bergen", "organization": "Eurographics", "pages_from": "21", "pages_to": "30", "research_areas": [ { "id": "BioVis", "drupal_id": 4127, "name": "Biological Data Visualization", "short_abstract": "In this research area, we develop new visualization techniques to support biologists in data analysis and create visualizations to disseminate scientific discoveries in biology.", "abstract": "In modern biological research domain experts have to deal with complex and large data collections and simulations. Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n", "website": "https://www.cg.tuwien.ac.at/research/area/BioVis", "teaser": { "name": "teaser.png", "path": "research_area:BioVis", "type": "image/png", "size": 16330957, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/BioVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "amirkhanov-2019-manylands", "byska-2019-mdfc", "cellVIEW_2015", "cmolik-2020-tvcg", "Dietrich_1", "dietrich-2016-viseq2", "Ehlers_PhD", "ehlers-2025-ait", "eschner-2023-ims", "eschner-blur-2022", "Escribano_2017", "Furmanova_2018", "Gehrer-2017", "Gehrer-2017-molmach", "glinzner-2016-tex", "Halladjian_2020", "kapferer-2017-godot", "klein_2017_IM", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koch-2018-sso", "Kolesar-Fractional-2016", "kolesar-ivan-2014-polymers", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kozlikova-Visualization-2016b", "Krone2016VABC", "Kugler_2019", "lemuzic_2015_timelapse", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lipp-2017-mgpu", "lipp-2017-vulkan", "Manczarski-2016", "manylands_award", "Miao_2019", "miao_inria_2017", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-xmas-card-2016", "Mitterhofer_2017", "nguyen_2020-covid", "Nowak_2020", "raidou_2019_springer", "raidou_shonan167", "raidou2018visualflatter", "rasch-2016-imgses", "Reisacher2016", "rinortner_susanne-2019-vpicc", "Sarkis_2021", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2013-neuromap", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "stappen_2017_animatedcomic", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "trautner-2018-imd", "unger-2019_vcp", "vad_2015_phd", "vad_viktor-2017-WVE", "vad-2016-bre", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "waldin-2019-ccm", "waldner-2014-af", "Weissenboeck_2019", "wu-2017-dagstuhl", "wu-2018-metabo", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg" ], "projects": [ "BioNetIllustration", "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=BioVis", "__class": "ResearchArea" }, { "id": "IllVis", "drupal_id": 4131, "name": "Illustrative Visualization", "short_abstract": "In this research area, we develop rendering methods that are inspired by scientific illustrations, in order to make complex biological information more intuitive to understand and more pleasant to read.", "abstract": "Scientific illustration is concerned with researching ways in which complex biological and medical data can be abstracted in order to convey a desired information that would otherwise be impossible or hard to retrieve from the original data. Illustrators apply such techniques, for instance, to present non-important parts of an organ in a simplified way, while using detailed representations to put the focus of attention on a region where a tumor might be situated.\n\nTo identify such meaningful visual abstractions for visualization, their effectiveness for human perception and cognition has to be assessed, and they have to be formalized in order to make them applicable in rendering algorithms. In this project, we try to advance the understanding of procedural visual abstraction of complex physiological processes that describe the complex machinery of biological life.", "website": "https://www.cg.tuwien.ac.at/research/area/IllVis", "teaser": { "name": "teaser.jpg", "path": "research_area:IllVis", "type": "image/jpeg", "size": 34861, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/IllVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "antes-2026-maa", "Antonini2020", "Balabanian-2010-IIV", "Balduz_01", "Bayat_2019", "Bechtold2020", "Birkeland-2012-IMC", "brandstaetter_01", "bruckner-2005-ICV", "bruckner-2006-ICE", "bruckner-2007-STF", "bruckner-2008-IIV", "bruckner-2010-HVC", "bruckner-2010-IFC", "cellVIEW_2015", "Chen-Information-2016", "Deutsch-2018", "Dhanoa_2021", "Dhanoa2024", "dietrich-2016-viseq2", 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"seyfert-2017", "sikachev-2010-ill_vis_vol_ren", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "Spechtenhauser_Florian_2016", "stappen_2017_animatedcomic", "Stoll2020", "sturl_2016_dynlabels", "Swoboda2020", "szabo_patrik-2022-tour", "takahashi-2019-acdt", "Thomas-2018", "TR-186-2-07-08", "Troidl_2021", "Troidl_2022", "tut-eg-2006", "tut-siggraph-2006", "tut-vis-2006", "tut-vis-2007", "Unger2020", "Vasileva_2022", "Viola_Ivan_2013_SVA", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "viola-evr", "Viola-Pondering-2017", "Viola-vistutillustrativevis", "Waldin_Nicholas_2016_Colormaps", "waldin-2019-ccm", "Waldner_2017_11", "Wihann_2017", "Woschizka_2021", "wu-2019-bmc", "wu-2019-report", "Zaufel_2021", "zechmeister2020", "Zeng_2021", "Zusag-2017-Bach" ], "projects": [ "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=IllVis", "__class": "ResearchArea" } ], "keywords": [ "I.3.3 [Computer 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The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/

\r\n\r\n

Prototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/

\r\n\r\n

cellVIEW

\r\n\r\n

cellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.

\r\n\r\n

Invited Talks

\r\n\r\n

18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness

\r\n", "abstract": "

The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/

\r\n\r\n

Prototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/

\r\n\r\n

cellVIEW

\r\n\r\n

cellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.

\r\n\r\n

Invited Talks

\r\n\r\n

18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness

\r\n", "start_date": "2013-01-01", "end_date": "2020-12-31", "leader_id": 171, "logo": { "name": "logo.png", "path": "project:illvisation", "type": "image/png", "size": 58061, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/illvisation/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "eu7", "contract_number": "PCIG13-GA-2013-618680", "comment": null }, { "id": "WWTF", "contract_number": "VRG11-010", "comment": null } ], "research_areas": [ "BioVis", "IllVis" ], "publications": [ "2013_Viola_Ivan_2013_MTS", "2017-kouril-illcell", "bernhard-2014-GTOM", "bernhard-2016-gft", "birkeland_aasmund_2014_pums", "boesch_2014_browserHistoryVis", "cellVIEW_2015", "Cornel2016CFM", "Diehl_2015", "dietrich-2016-viseq2", "dworschak-2016-szcm", "Gadllah_Hani_2016", "gangl-2018-gpsart", "Gehrer_Daniel_CUI", "Gehrer-2017-molmach", "glinzner-2016-tex", "Groeller_2016_I7", "horvath-2018-ism", "kapferer-2017-godot", "koch-2018-sso", "koehle-2013-sgv", "kolesar-ivan-2014-polymers", "kouril-2015-maya2cellview", "Krone2016VABC", "Langer_Maximillian_DMV", "lemuzic_2015_timelapse", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lemuzic-mindek-sorger-cgfcc", "lipp-2017-mgpu", "lipp-2017-vulkan", "miao_tvcg_2017", "miao_tvcg_2018", "mindek-2015-mc", "mindek-2016-utah-talk", "mindek-2017-dsn", "mindek-2017-marion", "mindek-2018-fyi", "mindek-2019-mci", "moerth-2018-tpose", "Plank_Pascal_2015_HVP", "plank-2017-sldg", "puenguentzky-2014-ht", "rasch-2016-imgses", "Reisacher_Matthias_CPW", "Reisacher2016", "Sbardellati-2019-vcbm", "seyfert-2017", "sifuentes-2018-crowd", "Solteszova2016", "sorger-2016-fowardabstraction", "textures-3d-printing", "vad-2016-bre", "Viola_2013_IDV", "Viola_Ivan_2013_CAI", "Viola_Ivan_2013_D3D", "Viola_Ivan_2013_DC", "Viola_Ivan_2013_GS", "Viola_Ivan_2013_HQ3", "Viola_Ivan_2013_RMA", "Viola_Ivan_2013_RSb", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_DAC", "Viola_Ivan_IIP", "Viola_Ivan_UVP", "Viola_Ivan_VDP", "viola-evr", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2017-thesis", "waldner-2013-facetCloudsGI", "waldner-2013-ubiWM", "waldner-2014-af", "waldner-2014-ghi", "wu-2019-bmc" ], "url": "https://www.cg.tuwien.ac.at/research/projects/illvisation", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2016/sorger-2016-fowardabstraction/", "__class": "Publication" }, { "id": "bernhard-2016-gft", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": null, "title": " The Accuracy of Gauge-Figure Tasks in Monoscopic and Stereo Displays", "date": "2016-07", "abstract": "The gauge-figure task (GFT) is a widespread method used to study surface perception for evaluating rendering and visualization techniques. The authors investigate how accurately slant angles probed on well-defined objects align with the ground truth (GT) in monoscopic and stereoscopic displays. Their results show that the GFT probes taken with well-defined objects align well with the GT in the all-monoscopic and all-stereoscopic conditions. However, they found that a GF rendered in stereo over a monoscopic stimulus results in a strong slant underestimation and that an overestimation occurred in the inverse case (monoscopic GF andstereoscopic stimulus). They discuss how their findings affect the interpretation of absolute GFT measures, compared to the GT normal.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 216, "image_height": 205, "name": "bernhard-2016-gft-.jpg", "type": "image/jpeg", "size": 38475, "path": "Publication:bernhard-2016-gft", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/bernhard-2016-gft/bernhard-2016-gft-.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/bernhard-2016-gft/bernhard-2016-gft-:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 660, "drupal_id": 102, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/MatthiasBernhard", "firstname": "Matthias", "lastname": "Bernhard", "searchname": "Matthias Bernhard", "is_teacher": false, "name": "Matthias Bernhard", "publications": [ "amirkhanov-2018-withteeth", "amirkhanov2020visual", "Bernhard_Matthias_2014_VAC", "bernhard-2006-dvrcta", "bernhard-2010-gph", "bernhard-2011-bmtf", "bernhard-2011-maicg", "bernhard-2014-EFD", "bernhard-2014-GTOM", "bernhard-2016-gft", "hecher-2014-MH", "sundstedt-2013-vag", "Waldin_Nicholas_2016_Colormaps", "Waldin_Nicholas_2016_Individualization", "waldner-2014-af" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "bernhard-2011-maicg", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "bernhard-2014-EFD", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "bernhard-2014-GTOM", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "dellmour-2012-mcr", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "dellmour-2013-grs", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "grosse-2009-avp", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "labschuetz-2010-bms", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "labschuetz-2011-rsr", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Plank_Pascal_2015_HVP", "field_id": "supervisor", "ordernum": 0