[ { "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, "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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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", "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", "publications": [ "2013_Viola_Ivan_2013_MTS", 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"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 }, { "publ_id": "dietrich-2016-viseq2", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "gangl-2018-gpsart", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Gehrer_Daniel_CUI", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Gehrer-2017", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "glinzner-2016-tex", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "haidacher-2004-FVV", 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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" } ], "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", "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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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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In mixed labeling, the given objects are labeled with both internal labels placed (at least partially) over the objects and external labels placed in the space around the objects and connected with the labeled objects with straight-line leaders. The proposed algorithm determines the position and type of each label based on the user-specified ambiguity threshold and eliminates overlaps between the labels, as well as between the internal labels and the straight-line leaders of external labels. The algorithm is a screen-space technique; it operates in an image where the 2D objects or projected 3D objects are encoded. In other words, we can use the algorithm whenever we can render the objects to an image, which makes the algorithm fit for use in many domains. The algorithm operates in real-time, giving the results immediately. Finally, we present results from an expert evaluation, in which a professional illustrator has evaluated the label layouts produced with the proposed algorithm.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "cmolik-2020-tvcg-image.png", "type": "image/png", "size": 47074, "path": "Publication:cmolik-2020-tvcg", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/cmolik-2020-tvcg/cmolik-2020-tvcg-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/cmolik-2020-tvcg/cmolik-2020-tvcg-image:thumb{{size}}.png" }, "sync_repositum_override": null, "authors": [ { "id": 1246, "drupal_id": 1184, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/LadislavČmolík-0", "firstname": "Ladislav", "lastname": "Čmolík", "searchname": 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"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", "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" } ], "doi": "10.1109/TVCG.2020.3027368", "journal": "IEEE Transactions on Visualization and Computer Graphics (TVCG)", "pages_from": "1", "pages_to": "14", "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", "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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"waldner-2017-vph", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "waser_2011_VSD", "webGPU_aggregateVis-2023", "wolf-2023-cc", "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", "d9282", "d9522", "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": true, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "cmolik-2020-tvcg-image.png", "type": "image/png", "size": 47074, "path": "Publication:cmolik-2020-tvcg", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/cmolik-2020-tvcg/cmolik-2020-tvcg-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/cmolik-2020-tvcg/cmolik-2020-tvcg-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "cmolik-2020-tvcg-paper.pdf", "type": "application/pdf", "size": 12960199, "path": "Publication:cmolik-2020-tvcg", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/cmolik-2020-tvcg/cmolik-2020-tvcg-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/cmolik-2020-tvcg/cmolik-2020-tvcg-paper:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "BioNetIllustration", "workgroup_id": "vis", "drupal_id": 4196, "name": "BioNetIllustration: User Centric Illustrations of Biological Networks", "name_de": null, "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/cmolik-2020-tvcg/", "__class": "Publication" }, { "id": "Purchase-2020-gd", "type_id": "inproceedings", "tu_id": null, "repositum_id": "20.500.12708/58252", "title": "The Turing Test for Graph Drawing Algorithms", "date": "2020-09", "abstract": "DoalgorithmsfordrawinggraphspasstheTuringTest?That is, are their outputs indistinguishable from graphs drawn by humans? We address this question through a human-centred experiment, focusing on ‘small’ graphs, of a size for which it would be reasonable for someone to choose to draw the graph manually. Overall, we find that hand-drawn layouts can be distinguished from those generated by graph drawing al- gorithms, although this is not always the case for graphs drawn by force- directed or multi-dimensional scaling algorithms, making these good can- didates for Turing Test success. We show that, in general, hand-drawn graphs are judged to be of higher quality than automatically generated ones, although this result varies with graph size and algorithm.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 256, "image_height": 192, "name": "Purchase-2020-gd-image.png", "type": "image/png", "size": 29720, "path": "Publication:Purchase-2020-gd", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Purchase-2020-gd/Purchase-2020-gd-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Purchase-2020-gd/Purchase-2020-gd-image:thumb{{size}}.png" }, "sync_repositum_override": null, "authors": [ { "id": 1623, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Helen C.", "lastname": "Purchase", "searchname": "Helen C. Purchase", "is_teacher": false, "name": "Helen C. Purchase", "publications": [ "Purchase-2020-gd", "YOGHOURDJIAN2019" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "Purchase-2020-gd", "field_id": "lecturer", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1623", "__class": "Author" }, { "id": 1619, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Daniel", "lastname": "Archambault", "searchname": "Daniel Archambault", "is_teacher": false, "name": "Daniel Archambault", "publications": [ "Purchase-2020-gd", "wu-2018-shonan", "YOGHOURDJIAN2019" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1619", "__class": "Author" }, { "id": 1783, "drupal_id": null, "orcid_id": null, "website": "https://www2.cs.arizona.edu/~kobourov/", "firstname": "Stephen", "lastname": "Kobourov", "searchname": "Stephen Kobourov", "is_teacher": false, "name": "Stephen Kobourov", "publications": [ "Purchase-2020-gd" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1783", "__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", "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": 1784, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Sergey", "lastname": "Pupyrev", "searchname": "Sergey Pupyrev", "is_teacher": false, "name": "Sergey Pupyrev", "publications": [ "Purchase-2020-gd" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1784", "__class": "Author" }, { "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": "Wu", "searchname": "Hsiang-Yun Wu", "is_teacher": false, "name": "Hsiang-Yun Wu", "publications": [ "8564188", "An-2018-CHI", "batik-2021-gd", "batik-2022-smm", "bhore-2021-issac", "bhore-2023-ucd", "cmolik-2020-tvcg", "ehlers-2023-iro", "Ganglberger-2022-cg", "Iijima-2020-iV", "koeppel-2021", "korpitsch-2020-cescg", "Korpitsch-2020-wscg", "kouril-2018-LoL", "Kuroko-2020-iV", "li-2019-gdc", "maruyama-2019-iv", "mizuno-2019-eurovis", "noellenburg-2023-pga", "pahr-2021-vologram", "Purchase-2020-gd", "raidou_slicedice", "sakr_sherif-2020-cacm", "Sbardellati-2019-vcbm", "schindler_2020vis", "Schindler-2022-eurovis", "takahashi-2019-acdt", "vasileva-2019-smw", "wu-2017-dagstuhl", "wu-2018-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-prague", "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": "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-thesis", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Pahr2020", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Pilizar_-2020-bachelor", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "pointner_simon-2020", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "rinortner_susanne-2019-vpicc", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Schindler-2022-eurovis", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Thomas-2018", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Vasileva-2018", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "wu-2019-smw", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "wu-2019-visworkshop", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "wu-2020-eurovis-star", "field_id": "lecturer", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1464", "__class": "Author" } ], "booktitle": "Proceedings of the 28th International Symposium on Graph Drawing and Network Visualization (GD2020)", "cfp": { "name": "gd20-cfp.pdf", "type": "application/pdf", "error": "0", "size": "182950", "orig_name": "gd20-cfp.pdf", "ext": "pdf" }, "event": "28th International Symposium on Graph Drawing and Network Visualization ", "lecturer": [ { "id": 1623, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Helen C.", "lastname": "Purchase", "searchname": "Helen C. Purchase", "is_teacher": false, "name": "Helen C. Purchase", "publications": [ "Purchase-2020-gd", "YOGHOURDJIAN2019" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "Purchase-2020-gd", "field_id": "lecturer", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1623", "__class": "Author" } ], "pages_from": "1", "pages_to": "16", "research_areas": [ { "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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"https://www.cg.tuwien.ac.at/research/publications/2020/Purchase-2020-gd/Purchase-2020-gd-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Purchase-2020-gd/Purchase-2020-gd-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Purchase-2020-gd-paper.pdf", "type": "application/pdf", "size": 3933269, "path": "Publication:Purchase-2020-gd", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/Purchase-2020-gd/Purchase-2020-gd-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/Purchase-2020-gd/Purchase-2020-gd-paper:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "BioNetIllustration", "workgroup_id": "vis", "drupal_id": 4196, "name": "BioNetIllustration: User Centric Illustrations of Biological Networks", "name_de": null, "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/Purchase-2020-gd/", "__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, "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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"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", "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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"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-gall-2020-dde", "Heinzl2021", "hromniak-2019-vcn", "Iijima-2020-iV", "indirectBiasLanguageModels-2023", "karnik-09-shapegrammar", "Kehrer-2010-mom", "kehrer-2012-mod", "kehrer-2013-SBC", "Kehrer-2013-STAR", "klaffenboeck-thesis", "Klein_Tobias_2015TIV", "klein-2016-WCL", "koeppel-2021", "Kolter_2021", "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", 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"waldner-2017-vph", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "waser_2011_VSD", "webGPU_aggregateVis-2023", "wolf-2023-cc", "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", "d9282", "d9522", "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": "wu-2019-visworkshop-paper.pdf", "type": "application/pdf", "size": 252096, "path": "Publication:wu-2019-visworkshop", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-visworkshop/wu-2019-visworkshop-paper.pdf", "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-paper:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "BioNetIllustration", "workgroup_id": "vis", "drupal_id": 4196, "name": "BioNetIllustration: User Centric Illustrations of Biological Networks", "name_de": null, "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/2019/wu-2019-visworkshop/", "__class": "Publication" }, { "id": "rinortner_susanne-2019-vpicc", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Visualizing Protein Interactions in Corresponding Compartments", "date": "2019-10-16", "abstract": "The visualization of networks for protein interactions is an important step to understand them. There are already many approaches for this task, but most of them do not show any information about the compartment of the cell the proteins belong to. Since the placement of proteins inside a cell is important information, because it helps to understand their interactions, this thesis proposes a method to visualize protein inside cell compartments. The objective of this project is a clear and understandable visualization of interactions between proteins and where these interactions or reactions happen inside the cell. This project uses a three-dimensional model of a cell as a base and intersects it using cutting planes. Then the intersection surface is sampled and reconstructed using Delaunay triangulation. To the mesh created by the triangulation, a force-directed algorithm is applied. This algorithm is used to scale single-cell parts in order to fit all proteins inside. This ensures that none of the cell parts get overfilled. The result is a new method that makes it possible to visualize not only protein-protein interactions but also in which compartment of the cell the proteins are located.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1650, "image_height": 832, "name": "rinortner_susanne-2019-vpicc-image.png", "type": "image/png", "size": 864375, "path": "Publication:rinortner_susanne-2019-vpicc", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/rinortner_susanne-2019-vpicc/rinortner_susanne-2019-vpicc-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/rinortner_susanne-2019-vpicc/rinortner_susanne-2019-vpicc-image:thumb{{size}}.png" }, "sync_repositum_override": null, "authors": [ { "id": 1704, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Susanne", "lastname": "Rinortner", "searchname": "Susanne Rinortner", "is_teacher": false, "name": "Susanne Rinortner", "publications": [ "rinortner_susanne-2019-vpicc" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1704", "__class": "Author" } ], "date_end": "2019-10-15", "date_start": "2019-03-05", "matrikelnr": "01526772", "supervisor": [ { "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": "Wu", "searchname": "Hsiang-Yun Wu", "is_teacher": false, "name": "Hsiang-Yun Wu", "publications": [ "8564188", "An-2018-CHI", "batik-2021-gd", "batik-2022-smm", "bhore-2021-issac", "bhore-2023-ucd", "cmolik-2020-tvcg", "ehlers-2023-iro", "Ganglberger-2022-cg", "Iijima-2020-iV", "koeppel-2021", "korpitsch-2020-cescg", "Korpitsch-2020-wscg", "kouril-2018-LoL", "Kuroko-2020-iV", "li-2019-gdc", "maruyama-2019-iv", "mizuno-2019-eurovis", "noellenburg-2023-pga", "pahr-2021-vologram", "Purchase-2020-gd", "raidou_slicedice", "sakr_sherif-2020-cacm", "Sbardellati-2019-vcbm", "schindler_2020vis", "Schindler-2022-eurovis", "takahashi-2019-acdt", "vasileva-2019-smw", "wu-2017-dagstuhl", "wu-2018-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-prague", "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": "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-thesis", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Pahr2020", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Pilizar_-2020-bachelor", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "pointner_simon-2020", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "rinortner_susanne-2019-vpicc", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Schindler-2022-eurovis", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Thomas-2018", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Vasileva-2018", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "wu-2019-smw", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "wu-2019-visworkshop", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "wu-2020-eurovis-star", "field_id": "lecturer", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1464", "__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", "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", 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"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": "BioNetIllustration", "workgroup_id": "vis", "drupal_id": 4196, "name": "BioNetIllustration: User Centric Illustrations of Biological Networks", "name_de": null, "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/2019/rinortner_susanne-2019-vpicc/", "__class": "Publication" }, { "id": "wu-2019-vcbm", "type_id": "unknown", "tu_id": null, "repositum_id": null, "title": "Map of Metabolic Harmony", "date": "2019-09-03", "abstract": "As the human body is healthy when the\nmetabolic harmony is maintained, the human metabolic pathways are\ninterpretable when its visual representation is harmonized. 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, "authors": [ { "id": 1464, "drupal_id": 1266, "orcid_id": "0000-0003-1028-0010", "website": "https://www.cg.tuwien.ac.at/staff/Hsiang-YunWu", "firstname": 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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" } ], "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", "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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"waldner-2017-vph", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "waser_2011_VSD", "webGPU_aggregateVis-2023", "wolf-2023-cc", "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", "d9282", "d9522", "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": 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" } ], "projects_workgroups": [ { "id": "BioNetIllustration", "workgroup_id": "vis", "drupal_id": 4196, "name": "BioNetIllustration: User Centric Illustrations of Biological Networks", "name_de": null, "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/2019/wu-2019-vcbm/", "__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, "authors": [ { "id": 1555, "drupal_id": 1363, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/MaximilianSbardellati", "firstname": "Maximilian", 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"is_teacher": false, "name": "Hsiang-Yun Wu", "publications": [ "8564188", "An-2018-CHI", "batik-2021-gd", "batik-2022-smm", "bhore-2021-issac", "bhore-2023-ucd", "cmolik-2020-tvcg", "ehlers-2023-iro", "Ganglberger-2022-cg", "Iijima-2020-iV", "koeppel-2021", "korpitsch-2020-cescg", "Korpitsch-2020-wscg", "kouril-2018-LoL", "Kuroko-2020-iV", "li-2019-gdc", "maruyama-2019-iv", "mizuno-2019-eurovis", "noellenburg-2023-pga", "pahr-2021-vologram", "Purchase-2020-gd", "raidou_slicedice", "sakr_sherif-2020-cacm", "Sbardellati-2019-vcbm", "schindler_2020vis", "Schindler-2022-eurovis", "takahashi-2019-acdt", "vasileva-2019-smw", "wu-2017-dagstuhl", "wu-2018-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-prague", "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": [ 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for Biology and Medicine", "cfp": { "name": "vcbm2019.pdf", "type": "application/pdf", "error": "0", "size": "270183", "orig_name": "vcbm2019.pdf", "ext": "pdf" }, "event": "VCBM 2019", "lecturer": [ { "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" } ], "pages_from": "103", "pages_to": "112", "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", "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", "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", "dietrich-2016-viseq2", "donabauer_2019_1", "eg-tut2005-iv", 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null, "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, "name": "Visual Computing: Illustrative Visualization", "name_de": null, "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\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
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\n18.11.2016: 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
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\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
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\n18.11.2016: 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
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", "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", "eiweck-hnv-2021", "eschner-2023-evl", "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-gall-2020-dde", "Heinzl2021", "hromniak-2019-vcn", "Iijima-2020-iV", "indirectBiasLanguageModels-2023", "karnik-09-shapegrammar", "Kehrer-2010-mom", "kehrer-2012-mod", "kehrer-2013-SBC", "Kehrer-2013-STAR", "klaffenboeck-thesis", "Klein_Tobias_2015TIV", "klein-2016-WCL", "koeppel-2021", "Kolter_2021", "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", "mayr-2021-wec", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "medeiros-2023-gwf", "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-2022-mam5", "Neubauer2020", "Nowak_2021", "ortner-2016-tunnel", "ortner-2016-visaware", "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", "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-2020-parameter", "stoff-concepMap-2021", "stritzel2022", "Strohmayer-2018-BT", "takahashi-2019-acdt", "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", "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", "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", "d9282", "d9522", "deskollage", "Scenario Pool" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=InfoVis", "__class": "ResearchArea" } ], "keywords": [], "weblinks": [ { "href": "https://youtu.be/dMphkr6nAHQ", "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": "mizuno-2019-eurovis-image.png", "type": "image/png", "size": 100164, "path": "Publication:mizuno-2019-eurovis", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/mizuno-2019-eurovis/mizuno-2019-eurovis-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/mizuno-2019-eurovis/mizuno-2019-eurovis-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "mizuno-2019-eurovis-paper.pdf", "type": "application/pdf", "size": 20180512, "path": "Publication:mizuno-2019-eurovis", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/mizuno-2019-eurovis/mizuno-2019-eurovis-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/mizuno-2019-eurovis/mizuno-2019-eurovis-paper:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "BioNetIllustration", "workgroup_id": "vis", "drupal_id": 4196, "name": "BioNetIllustration: User Centric Illustrations of Biological Networks", "name_de": null, "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/2019/mizuno-2019-eurovis/", "__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" }, "sync_repositum_override": 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": "Wu", "searchname": "Hsiang-Yun Wu", "is_teacher": false, "name": "Hsiang-Yun Wu", "publications": [ "8564188", "An-2018-CHI", "batik-2021-gd", "batik-2022-smm", "bhore-2021-issac", "bhore-2023-ucd", "cmolik-2020-tvcg", "ehlers-2023-iro", "Ganglberger-2022-cg", "Iijima-2020-iV", "koeppel-2021", "korpitsch-2020-cescg", "Korpitsch-2020-wscg", "kouril-2018-LoL", "Kuroko-2020-iV", "li-2019-gdc", "maruyama-2019-iv", "mizuno-2019-eurovis", "noellenburg-2023-pga", "pahr-2021-vologram", "Purchase-2020-gd", "raidou_slicedice", "sakr_sherif-2020-cacm", "Sbardellati-2019-vcbm", "schindler_2020vis", "Schindler-2022-eurovis", "takahashi-2019-acdt", "vasileva-2019-smw", "wu-2017-dagstuhl", "wu-2018-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-prague", "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": "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-thesis", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Pahr2020", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Pilizar_-2020-bachelor", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "pointner_simon-2020", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "rinortner_susanne-2019-vpicc", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Schindler-2022-eurovis", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Thomas-2018", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Vasileva-2018", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "wu-2019-smw", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "wu-2019-visworkshop", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "wu-2020-eurovis-star", "field_id": "lecturer", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1464", "__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", "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": 1673, "drupal_id": null, "orcid_id": null, "website": "https://archaea.univie.ac.at/research/filipa-sousa-lab/", "firstname": "Filipa", "lastname": "L. Sousa", "searchname": "Filipa L. Sousa", "is_teacher": false, "name": "Filipa L. Sousa", "publications": [ "wu-2019-bmc" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1673", "__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", "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", "Kehl-Direct-2016", "klein_2017_IM", "klein_2019_MSA_Poster", "klein_2019_PGG", "klein_2019_PMP", "koch_bernhard_2018-1", "Kolesar-Fractional-2016", "kolesar-ivan-2014-polymers", "Konev-FCV2018", "kouril-2017-sccgposter", "kouril-2018-LoL", "kouril-2020-hyperlabels", "kouril-2021-molecumentary", "Kozlikova-Visualization-2016b", "Krone2016VABC", "lawonn-2018-illvisstar", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lemuzic-mindek-sorger-cgfcc", "li-2019-gdc", "Masterthesis-Viola", "Mazza_2020", "Miao_2019", "miao_nantech_2019", "miao_nar_2020", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "mindek-2015-mc", "mindek-2017-marion", "mindek-2017-virtualcell", "Neumann-2002-Fea", "nguyen_2020-covid", "patel-2010-SVV", "phd-viola", "polatsek-2018-stv", "Rautek-2008-kav", "Rautek-2008-VF", "Rautek06Vis", "Reisacher2016", "ruiz-2008-OVR", "ruiz-2008-SEV", "Sarkis_2021", "Sbardellati-2019-vcbm", "sbert-2017-sa_course_0023", "seyfert-2017", "solteszova-2010-MOS", "Solteszova2016", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "toth-2007-ndd", "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", "tut-eg-2006", "tut-siggraph-2006", "tut-vis-2006", "tut-vis-2007", "vad_viktor-2017-WVE", "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-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-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 }, { "publ_id": "dietrich-2016-viseq2", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "gangl-2018-gpsart", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Gehrer_Daniel_CUI", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Gehrer-2017", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "glinzner-2016-tex", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "haidacher-2004-FVV", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "haidacher-2005-MND", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "haidacher-2007-idr", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "haushofer-2018-skinning", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "horvath-2018-ism", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "kapferer-2017-godot", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "klein_2019_PHD", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "klein-thesis", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "koch-2018-sso", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "koehle-2013-sgv", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "kohlmann-2009-lssl", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "kouril-2015-maya2cellview", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "kouril-2021-phdthesis", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Kugler_2019", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "Langer_Maximillian_DMV", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "LeMuzic_2016_PhD", "field_id": "reviewer_1", "ordernum": 0 }, { "publ_id": "LeMuzic_2016_PhD", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "lipp-2017-vulkan", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "malik-thesis", "field_id": "reviewer_2", "ordernum": 0 }, { "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 }, { "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": "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", "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", "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", "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", "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", "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", "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", "eiweck-hnv-2021", "eschner-2023-evl", "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-gall-2020-dde", "Heinzl2021", "hromniak-2019-vcn", "Iijima-2020-iV", "indirectBiasLanguageModels-2023", "karnik-09-shapegrammar", "Kehrer-2010-mom", "kehrer-2012-mod", "kehrer-2013-SBC", "Kehrer-2013-STAR", "klaffenboeck-thesis", "Klein_Tobias_2015TIV", "klein-2016-WCL", "koeppel-2021", "Kolter_2021", "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", "mayr-2021-wec", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "medeiros-2023-gwf", "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-2022-mam5", "Neubauer2020", "Nowak_2021", "ortner-2016-tunnel", "ortner-2016-visaware", "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", "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-2020-parameter", "stoff-concepMap-2021", "stritzel2022", "Strohmayer-2018-BT", "takahashi-2019-acdt", "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", "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", "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", "d9282", "d9522", "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, "name": "BioNetIllustration: User Centric Illustrations of Biological Networks", "name_de": null, "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, "name": "Visual Computing: Illustrative Visualization", "name_de": null, "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\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
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\n18.11.2016: 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
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\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
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\n18.11.2016: 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
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", "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", "eiweck-hnv-2021", "eschner-2023-evl", "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-gall-2020-dde", "Heinzl2021", "hromniak-2019-vcn", "Iijima-2020-iV", "indirectBiasLanguageModels-2023", "karnik-09-shapegrammar", "Kehrer-2010-mom", "kehrer-2012-mod", "kehrer-2013-SBC", "Kehrer-2013-STAR", "klaffenboeck-thesis", "Klein_Tobias_2015TIV", "klein-2016-WCL", "koeppel-2021", "Kolter_2021", "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", "mayr-2021-wec", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "medeiros-2023-gwf", "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-2022-mam5", "Neubauer2020", "Nowak_2021", "ortner-2016-tunnel", "ortner-2016-visaware", "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", "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-2020-parameter", "stoff-concepMap-2021", "stritzel2022", "Strohmayer-2018-BT", "takahashi-2019-acdt", "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", "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", "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", "d9282", "d9522", "deskollage", "Scenario Pool" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=InfoVis", "__class": "ResearchArea" } ], "keywords": [ "Metro Maps", "Graph Drawing", "Metaphors" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 256, "image_height": 192, "name": "wu-2019-smw-image.png", "type": "image/png", "size": 36787, "path": "Publication:wu-2019-smw", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-smw/wu-2019-smw-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-smw/wu-2019-smw-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "wu-2019-smw-paper.pdf", "type": "application/pdf", "size": 2849219, "path": "Publication:wu-2019-smw", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-smw/wu-2019-smw-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-smw/wu-2019-smw-paper:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "BioNetIllustration", "workgroup_id": "vis", "drupal_id": 4196, "name": "BioNetIllustration: User Centric Illustrations of Biological Networks", "name_de": null, "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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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", "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", "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", "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", "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", "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", "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", "eiweck-hnv-2021", "eschner-2023-evl", "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-gall-2020-dde", "Heinzl2021", "hromniak-2019-vcn", "Iijima-2020-iV", "indirectBiasLanguageModels-2023", "karnik-09-shapegrammar", "Kehrer-2010-mom", "kehrer-2012-mod", "kehrer-2013-SBC", "Kehrer-2013-STAR", "klaffenboeck-thesis", "Klein_Tobias_2015TIV", "klein-2016-WCL", "koeppel-2021", "Kolter_2021", "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", "mayr-2021-wec", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "medeiros-2023-gwf", "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-2022-mam5", "Neubauer2020", "Nowak_2021", "ortner-2016-tunnel", "ortner-2016-visaware", "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", "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-2020-parameter", "stoff-concepMap-2021", "stritzel2022", "Strohmayer-2018-BT", "takahashi-2019-acdt", "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", "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", "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", "d9282", "d9522", "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, "name": "BioNetIllustration: User Centric Illustrations of Biological Networks", "name_de": null, "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/2019/wu-2019-report/", "__class": "Publication" }, { "id": "YOGHOURDJIAN2019", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": null, "title": "Exploring the limits of complexity: A survey of empirical studies ongraph visualisation", "date": "2019-01-06", "abstract": "For decades, researchers in information visualisation and graph drawing\nhave focused on developing techniques for the layout and display of very\nlarge and complex networks. Experiments involving human participants\nhave also explored the readability of different styles of layout and\nrepresentations for such networks. In both bodies of literature,\nnetworks are frequently referred to as being ‘large’ or ‘complex’, yet\nthese terms are relative. From a human-centred, experiment\npoint-of-view, what constitutes ‘large’ (for example) depends on several\nfactors, such as data complexity, visual complexity, and the technology\nused. In this paper, we survey the literature on human-centred\nexperiments to understand how, in practice, different features and\ncharacteristics of node–link diagrams affect visual complexity.", "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": "YOGHOURDJIAN2019-image.png", "type": "image/png", "size": 40040, "path": "Publication:YOGHOURDJIAN2019", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/YOGHOURDJIAN2019/YOGHOURDJIAN2019-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/YOGHOURDJIAN2019/YOGHOURDJIAN2019-image:thumb{{size}}.png" }, "sync_repositum_override": null, "authors": [ { "id": 1618, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Vahan", "lastname": "Yoghourdjian", "searchname": "Vahan Yoghourdjian", "is_teacher": false, "name": "Vahan Yoghourdjian", "publications": [ "YOGHOURDJIAN2019" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1618", "__class": "Author" }, { "id": 1619, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Daniel", "lastname": "Archambault", "searchname": "Daniel Archambault", "is_teacher": false, "name": "Daniel Archambault", "publications": [ "Purchase-2020-gd", "wu-2018-shonan", "YOGHOURDJIAN2019" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1619", "__class": "Author" }, { "id": 1620, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Stephan", "lastname": "Diehl", "searchname": "Stephan Diehl", "is_teacher": false, "name": "Stephan Diehl", "publications": [ "YOGHOURDJIAN2019" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1620", "__class": "Author" }, { "id": 1621, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Tim ", "lastname": "Dwyer", "searchname": "Tim Dwyer", "is_teacher": false, "name": "Tim Dwyer", "publications": [ "YOGHOURDJIAN2019" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1621", "__class": "Author" }, { "id": 1622, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Karsten", "lastname": "Klein", "searchname": "Karsten Klein", "is_teacher": false, "name": "Karsten Klein", "publications": [ "YOGHOURDJIAN2019" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1622", "__class": "Author" }, { "id": 1623, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Helen C.", "lastname": "Purchase", "searchname": "Helen C. Purchase", "is_teacher": false, "name": "Helen C. 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"BioNetIllustration: User Centric Illustrations of Biological Networks", "name_de": null, "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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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. 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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": "BioNetIllustration", "workgroup_id": "vis", "drupal_id": 4196, "name": "BioNetIllustration: User Centric Illustrations of Biological Networks", "name_de": null, "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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", "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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"waldner-2017-vph", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "waser_2011_VSD", "webGPU_aggregateVis-2023", "wolf-2023-cc", "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", "d9282", "d9522", "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": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "wu-2018-shonan-paper.pdf", "type": "application/pdf", "size": 1672636, "path": "Publication:wu-2018-shonan", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-shonan/wu-2018-shonan-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-shonan/wu-2018-shonan-paper:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "BioNetIllustration", "workgroup_id": "vis", "drupal_id": 4196, "name": "BioNetIllustration: User Centric Illustrations of Biological Networks", "name_de": null, "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-shonan/", "__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, "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": "Wu", "searchname": "Hsiang-Yun Wu", "is_teacher": false, "name": "Hsiang-Yun Wu", "publications": [ "8564188", "An-2018-CHI", "batik-2021-gd", "batik-2022-smm", "bhore-2021-issac", "bhore-2023-ucd", "cmolik-2020-tvcg", "ehlers-2023-iro", "Ganglberger-2022-cg", "Iijima-2020-iV", "koeppel-2021", "korpitsch-2020-cescg", "Korpitsch-2020-wscg", "kouril-2018-LoL", "Kuroko-2020-iV", "li-2019-gdc", "maruyama-2019-iv", "mizuno-2019-eurovis", "noellenburg-2023-pga", "pahr-2021-vologram", "Purchase-2020-gd", "raidou_slicedice", "sakr_sherif-2020-cacm", "Sbardellati-2019-vcbm", "schindler_2020vis", "Schindler-2022-eurovis", "takahashi-2019-acdt", "vasileva-2019-smw", "wu-2017-dagstuhl", "wu-2018-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-prague", "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": "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-thesis", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Pahr2020", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Pilizar_-2020-bachelor", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "pointner_simon-2020", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "rinortner_susanne-2019-vpicc", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Schindler-2022-eurovis", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Thomas-2018", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Vasileva-2018", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "wu-2019-smw", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "wu-2019-visworkshop", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "wu-2020-eurovis-star", "field_id": "lecturer", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1464", "__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", "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", "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", "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", "Kehl-Direct-2016", "klein_2017_IM", "klein_2019_MSA_Poster", "klein_2019_PGG", "klein_2019_PMP", "koch_bernhard_2018-1", "Kolesar-Fractional-2016", "kolesar-ivan-2014-polymers", "Konev-FCV2018", "kouril-2017-sccgposter", "kouril-2018-LoL", "kouril-2020-hyperlabels", "kouril-2021-molecumentary", "Kozlikova-Visualization-2016b", "Krone2016VABC", "lawonn-2018-illvisstar", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "lemuzic-2014-ivm", 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"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-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 }, { "publ_id": "dietrich-2016-viseq2", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "gangl-2018-gpsart", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Gehrer_Daniel_CUI", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Gehrer-2017", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "glinzner-2016-tex", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "haidacher-2004-FVV", "field_id": 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"field_id": "supervisor", "ordernum": 1 }, { "publ_id": "Langer_Maximillian_DMV", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "LeMuzic_2016_PhD", "field_id": "reviewer_1", "ordernum": 0 }, { "publ_id": "LeMuzic_2016_PhD", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "lipp-2017-vulkan", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "malik-thesis", "field_id": "reviewer_2", "ordernum": 0 }, { "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 }, { "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" } ], "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", "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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"waldner-2017-vph", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "waser_2011_VSD", "webGPU_aggregateVis-2023", "wolf-2023-cc", "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", "d9282", "d9522", "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, "name": "BioNetIllustration: User Centric Illustrations of Biological Networks", "name_de": null, "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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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. Finally, we demonstrate ATP is also utilized to synthesize urea to eliminate the toxic ammonia in our body.", "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-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" }, "sync_repositum_override": 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": "Wu", "searchname": "Hsiang-Yun Wu", "is_teacher": false, "name": "Hsiang-Yun 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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", "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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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 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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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", "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", "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", "eiweck-hnv-2021", "eschner-2023-evl", "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-gall-2020-dde", "Heinzl2021", "hromniak-2019-vcn", "Iijima-2020-iV", "indirectBiasLanguageModels-2023", "karnik-09-shapegrammar", "Kehrer-2010-mom", "kehrer-2012-mod", "kehrer-2013-SBC", "Kehrer-2013-STAR", "klaffenboeck-thesis", "Klein_Tobias_2015TIV", "klein-2016-WCL", "koeppel-2021", "Kolter_2021", "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", "mayr-2021-wec", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "medeiros-2023-gwf", "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-2022-mam5", "Neubauer2020", "Nowak_2021", "ortner-2016-tunnel", "ortner-2016-visaware", "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", "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-2020-parameter", "stoff-concepMap-2021", "stritzel2022", "Strohmayer-2018-BT", "takahashi-2019-acdt", "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", "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", "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", "d9282", "d9522", "deskollage", "Scenario Pool" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=InfoVis", "__class": "ResearchArea" } ], "keywords": [], "weblinks": [ { "href": "https://doi.org/10.4230/DagRep.7.8.1", "caption": "Dagstuhl Seminar 17332", "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "wu-2017-dagstuhl-paper.pdf", "type": "application/pdf", "size": 3647552, "path": "Publication:wu-2017-dagstuhl", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2017-dagstuhl/wu-2017-dagstuhl-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2017-dagstuhl/wu-2017-dagstuhl-paper:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "BioNetIllustration", "workgroup_id": "vis", "drupal_id": 4196, "name": "BioNetIllustration: User Centric Illustrations of Biological Networks", "name_de": null, "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-2017-dagstuhl/", "__class": "Publication" } ]