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Inhaltliche\nRedundanzen sollen dabei vermieden werden.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "screenshot", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 814, "image_height": 377, "name": "gundacker-2020-wlm-screenshot.png", "type": "image/png", "size": 132524, "path": "Publication:gundacker-2020-wlm", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/gundacker-2020-wlm/gundacker-2020-wlm-screenshot.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/gundacker-2020-wlm/gundacker-2020-wlm-screenshot:thumb{{size}}.png" }, "sync_repositum_override": null, "authors": [ { "id": 1649, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Wolfgang", "lastname": "Gundacker", "searchname": "Wolfgang Gundacker", "is_teacher": false, "name": "Wolfgang Gundacker", "publications": [ "gundacker-2020-wlm" ], 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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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"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", 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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": { "1": { "description": null, "filetitle": "screenshot", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 814, "image_height": 377, "name": "gundacker-2020-wlm-screenshot.png", "type": "image/png", "size": 132524, "path": "Publication:gundacker-2020-wlm", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/gundacker-2020-wlm/gundacker-2020-wlm-screenshot.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/gundacker-2020-wlm/gundacker-2020-wlm-screenshot:thumb{{size}}.png" }, "2": { "description": null, "filetitle": "thesis", "main_file": false, "use_in_gallery": false, "access": "public", "name": "gundacker-2020-wlm-thesis.pdf", "type": "application/pdf", "size": 1436642, "path": "Publication:gundacker-2020-wlm", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/gundacker-2020-wlm/gundacker-2020-wlm-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/gundacker-2020-wlm/gundacker-2020-wlm-thesis:thumb{{size}}.png" } }, "projects_workgroups": [ { "id": "deskollage", "workgroup_id": "vis", "drupal_id": 4198, "name": "Visual Information Foraging on the Desktop", "name_de": null, "website": null, "status": "active", "short_abstract": "The goal of this project is to design and develop novel interactive visualization techniques to support knowledge workers in making sense of their unstructured, dynamic information collections. ", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. On the one hand, the studies show that, in some situations, interactive visualization can be less efficient than working with unprocessed text-based information. On the other hand, the studies also show that combining automatic data analysis with interactive visualization can lead to more unexpected findings, especially when exploring large data. The extent of manual information organization varies with the task: the less users know about the gathered information, the more automatic organization they expect. \n\nIn summary, this project contributed novel user interface concepts and design guidelines for user interfaces supporting information foraging and sensemaking. The techniques and study results were published at high-ranking peer-reviewed venues, and it can be expected that the findings of this project shape the way how users seek and organize their information in the future. \n\n", "start_date": "2015-12-01", "end_date": "2018-12-31", "leader_id": 1110, "logo": { "name": "logo.png", "path": "project:deskollage", "type": "image/png", "size": 331697, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/deskollage/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "T 752-N30", "comment": null } ], "research_areas": [ "InfoVis" ], "publications": [ "2019-ic", "byska-2019-mdfc", "casellato-2016-pkg", "cizmic-2018-evd", "donabauer-2015-asc", "dworschak-2016-szcm", "edlinger-2018-vwr", "georgiev-2019-cbg", "geymayer-2017-std", "gundacker-2020-wlm", "gusenbauer-2018", "hromniak-2019-vcn", "Koszticsak-2017-ewt", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "polatsek-2018-stv", "samoul-2019-cnp", "sietzen-2019-wnn", "sietzen-ifv-2019", "smiech-2018-tei", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "trautner-2018-imd", "unger-2019_vcp", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg" ], "url": "https://www.cg.tuwien.ac.at/research/projects/deskollage", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/gundacker-2020-wlm/", "__class": "Publication" }, { "id": "waldner-2020-tbg", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": "20.500.12708/141146", "title": "Interactive exploration of large time-dependent bipartite graphs", "date": "2020-04", "abstract": "Bipartite graphs are typically visualized using linked lists or matrices, but these visualizations neither scale well nor do they convey temporal development. We present a new interactive exploration interface for large, time-dependent bipartite graphs. We use two clustering techniques to build a hierarchical aggregation supporting different exploration strategies. Aggregated nodes and edges are visualized as linked lists with nested time series. We demonstrate two use cases: finding advertising expenses of public authorities following similar temporal patterns and comparing author-keyword co-occurrences across time. 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"https://doi.org/10.1016/j.cola.2020.100959", "journal": "Journal of Computer Languages", "volume": "57", "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.
\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" }, { "id": "NetVis", "drupal_id": 9472, "name": "Network Visualization", "short_abstract": "This research area aims to investigate how to best visualize graph-typed data, both abstractly as well as in domain-specific applications.", "abstract": "Graph-typed data is ubiquitous, from logistical or transportation networks, through social or correspondence networks, all the way to more abstract biochemical interaction networks. Each such application domain brings with it unique analytical goals, metadata, canonical representations, as well as types of vertices and edges. Routine, automated analyses of such data, while important, can often not fully support the kind of decision-making or data exploration necessary for more complex and/or larger networks. Here, it is through (interactive) visualization that we can support domain experts in their exploratory and (semi-) confirmatory research endeavors. On the one hand, we can build custom, tailor-made interactive, visual dashboards which directly address the needs and support the analysis of our domain expert collaborators. On the other, we can look at more foundational questions about how to best represent graph-typed data or better understand the factors which negatively/positively affect comprehension.
\r\n", "website": "https://www.cg.tuwien.ac.at/research/area/NetVis", "teaser": { "name": "teaser.png", "path": "research_area:NetVis", "type": "image/png", "size": 1948873, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/NetVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "ehlers-2023-iro", "mazurek-2018-veq", "sorger-2019-odn", "sorger-2021-egonet", "steinboeck-2018-lbg", "waldner-2014-ghi", "waldner-2020-tbg" ], "projects": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=NetVis", "__class": "ResearchArea" } ], "keywords": [ "Information visualization", "Bipartite graphs", "Clustering", "Time series data", "Insight-based evaluation" ], "weblinks": [ { "href": "https://www.sciencedirect.com/science/article/pii/S2590118420300198", "caption": "paper", "description": "Open Access article at ScienceDirect", "main_file": 1 } ], "files": [ { "description": "Dynamic BicFlows with nested time series visualization per cluster per set.", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1121, "image_height": 936, "name": "waldner-2020-tbg-teaser.png", "type": "image/png", "size": 250456, "path": "Publication:waldner-2020-tbg", "url": "https://www.cg.tuwien.ac.at/research/publications/2020/waldner-2020-tbg/waldner-2020-tbg-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2020/waldner-2020-tbg/waldner-2020-tbg-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "deskollage", "workgroup_id": "vis", "drupal_id": 4198, "name": "Visual Information Foraging on the Desktop", "name_de": null, "website": null, "status": "active", "short_abstract": "The goal of this project is to design and develop novel interactive visualization techniques to support knowledge workers in making sense of their unstructured, dynamic information collections. ", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. On the one hand, the studies show that, in some situations, interactive visualization can be less efficient than working with unprocessed text-based information. On the other hand, the studies also show that combining automatic data analysis with interactive visualization can lead to more unexpected findings, especially when exploring large data. The extent of manual information organization varies with the task: the less users know about the gathered information, the more automatic organization they expect. \n\nIn summary, this project contributed novel user interface concepts and design guidelines for user interfaces supporting information foraging and sensemaking. The techniques and study results were published at high-ranking peer-reviewed venues, and it can be expected that the findings of this project shape the way how users seek and organize their information in the future. \n\n", "start_date": "2015-12-01", "end_date": "2018-12-31", "leader_id": 1110, "logo": { "name": "logo.png", "path": "project:deskollage", "type": "image/png", "size": 331697, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/deskollage/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "T 752-N30", "comment": null } ], "research_areas": [ "InfoVis" ], "publications": [ "2019-ic", "byska-2019-mdfc", "casellato-2016-pkg", "cizmic-2018-evd", "donabauer-2015-asc", "dworschak-2016-szcm", "edlinger-2018-vwr", "georgiev-2019-cbg", "geymayer-2017-std", "gundacker-2020-wlm", "gusenbauer-2018", "hromniak-2019-vcn", "Koszticsak-2017-ewt", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "polatsek-2018-stv", "samoul-2019-cnp", "sietzen-2019-wnn", "sietzen-ifv-2019", "smiech-2018-tei", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "trautner-2018-imd", "unger-2019_vcp", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg" ], "url": "https://www.cg.tuwien.ac.at/research/projects/deskollage", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2020/waldner-2020-tbg/", "__class": "Publication" }, { "id": "mazurek-2018-vac", "type_id": "masterthesis", "tu_id": 282668, "repositum_id": null, "title": "Visual Active Learning for News Stream Classification", "date": "2019-10-10", "abstract": "In many domains, the sheer quantity of text documents that have to be parsed increases\ndaily. To keep up with this continuous text stream, a considerable amount of time has to be invested. We developed a classification interface for text streams that learns user-specific topics from the user’s labeling process and partitions the incoming data into these topics.\nCurrent approaches that try to derive content categorization from a vast number of unstructured text documents use pre-trained learning models to perform text classification.\nThese models assign predefined categories to the text according to its content. Depending on the use case, a user’s interests might not coincide with the given categories. The model cannot adapt to changing terminology that was not present during training. Besides these factors, users often do not trust pre-trained models as they are a black box for them.\nTo solve this problem, our application lets users define a classification problem and\ntrain a learning model through interaction with a Star Coordinates visualization. The\napproach that makes this interaction efficient is a variant of active learning. This active learning variant states that a learning model can achieve greater accuracy with fewer labeled training instances, if a user provides data purposefully from which it learns. We adapted this strategy for text stream classification by visualizing the topic affiliation probabilities of the learning model and providing novel interaction tools to enhance the model’s performance iteratively. By simulating different selection strategies common in active learning, we found that our visual selection strategies correspond closely to the classic active learning selection\nstrategies. Further, users performed on par with the best simulated selection strategies in the results from our preliminary user study. Our evaluation concludes that there are benefits from incorporating information visualization into the active learning process.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 668, "image_height": 638, "name": "mazurek-2018-vac-image.png", "type": "image/png", "size": 56667, "path": "Publication:mazurek-2018-vac", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/mazurek-2018-vac/mazurek-2018-vac-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/mazurek-2018-vac/mazurek-2018-vac-image:thumb{{size}}.png" }, "sync_repositum_override": null, "authors": [ { "id": 1364, "drupal_id": 1285, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/MichaelMazurek", "firstname": "Michael", "lastname": "Mazurek", "searchname": "Michael Mazurek", "is_teacher": 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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": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 668, "image_height": 638, "name": "mazurek-2018-vac-image.png", "type": "image/png", "size": 56667, "path": "Publication:mazurek-2018-vac", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/mazurek-2018-vac/mazurek-2018-vac-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/mazurek-2018-vac/mazurek-2018-vac-image:thumb{{size}}.png" }, { "description": null, "filetitle": "Master thesis", "main_file": true, "use_in_gallery": true, "access": "public", "name": "mazurek-2018-vac-Master thesis.pdf", "type": "application/pdf", "size": 5490435, "path": "Publication:mazurek-2018-vac", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/mazurek-2018-vac/mazurek-2018-vac-Master thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/mazurek-2018-vac/mazurek-2018-vac-Master thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "Poster", "main_file": true, "use_in_gallery": true, "access": "public", "name": "mazurek-2018-vac-Poster.pdf", "type": "application/pdf", "size": 1520895, "path": "Publication:mazurek-2018-vac", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/mazurek-2018-vac/mazurek-2018-vac-Poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/mazurek-2018-vac/mazurek-2018-vac-Poster:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "deskollage", "workgroup_id": "vis", "drupal_id": 4198, "name": "Visual Information Foraging on the Desktop", "name_de": null, "website": null, "status": "active", "short_abstract": "The goal of this project is to design and develop novel interactive visualization techniques to support knowledge workers in making sense of their unstructured, dynamic information collections. ", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. On the one hand, the studies show that, in some situations, interactive visualization can be less efficient than working with unprocessed text-based information. On the other hand, the studies also show that combining automatic data analysis with interactive visualization can lead to more unexpected findings, especially when exploring large data. The extent of manual information organization varies with the task: the less users know about the gathered information, the more automatic organization they expect. \n\nIn summary, this project contributed novel user interface concepts and design guidelines for user interfaces supporting information foraging and sensemaking. The techniques and study results were published at high-ranking peer-reviewed venues, and it can be expected that the findings of this project shape the way how users seek and organize their information in the future. \n\n", "start_date": "2015-12-01", "end_date": "2018-12-31", "leader_id": 1110, "logo": { "name": "logo.png", "path": "project:deskollage", "type": "image/png", "size": 331697, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/deskollage/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "T 752-N30", "comment": null } ], "research_areas": [ "InfoVis" ], "publications": [ "2019-ic", "byska-2019-mdfc", "casellato-2016-pkg", "cizmic-2018-evd", "donabauer-2015-asc", "dworschak-2016-szcm", "edlinger-2018-vwr", "georgiev-2019-cbg", "geymayer-2017-std", "gundacker-2020-wlm", "gusenbauer-2018", "hromniak-2019-vcn", "Koszticsak-2017-ewt", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "polatsek-2018-stv", "samoul-2019-cnp", "sietzen-2019-wnn", "sietzen-ifv-2019", "smiech-2018-tei", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "trautner-2018-imd", "unger-2019_vcp", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg" ], "url": "https://www.cg.tuwien.ac.at/research/projects/deskollage", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/mazurek-2018-vac/", "__class": "Publication" }, { "id": "waldner-2019-rld", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "A Comparison of Radial and Linear Charts for Visualizing Daily Patterns", "date": "2019-10", "abstract": "Radial charts are generally considered less effective than linear charts. Perhaps the only exception is in visualizing periodical time-dependent data, which is believed to be naturally supported by the radial layout. It has been demonstrated that the\ndrawbacks of radial charts outweigh the benefits of this natural mapping. Visualization of daily patterns, as a special case, has not been systematically evaluated using radial charts. In contrast to yearly or weekly recurrent trends, the analysis of daily patterns on a radial chart may benefit from our trained skill on reading radial clocks that are ubiquitous in our culture. In a crowd-sourced experiment with 92 non-expert users, we evaluated the accuracy, efficiency, and subjective ratings of radial and linear charts for visualizing daily traffic accident patterns. We systematically compared juxtaposed 12-hours variants and single 24-hours variants for both layouts in four low-level tasks and one high-level interpretation task. Our results show that over all tasks, the most elementary 24-hours linear bar chart is most accurate and efficient and is also preferred by the users. This provides strong evidence for the use of linear layouts – even for visualizing periodical daily patterns.", "authors_et_al": false, "substitute": null, "main_image": { "description": "Daily patterns visualized in a 24-hours radial chart. 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By understanding the limits of human perception, we can design and optimize rendering algorithms that perfectly fit users' needs, tailor visualizations to make data better understandable, and effectively draw the user's attention to important information.
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", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 497, "image_height": 474, "name": "waldner-2019-rld-teaser.png", "type": "image/png", "size": 53565, "path": "Publication:waldner-2019-rld", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/waldner-2019-rld/waldner-2019-rld-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/waldner-2019-rld/waldner-2019-rld-teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "video preview", "main_file": false, "use_in_gallery": false, "access": "public", "name": "waldner-2019-rld-video preview.mp4", "type": "video/mp4", "size": 3082628, "path": "Publication:waldner-2019-rld", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/waldner-2019-rld/waldner-2019-rld-video preview.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/waldner-2019-rld/waldner-2019-rld-video preview:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2019/waldner-2019-rld/waldner-2019-rld-video preview:video.mp4" } ], "projects_workgroups": [ { "id": "deskollage", "workgroup_id": "vis", "drupal_id": 4198, "name": "Visual Information Foraging on the Desktop", "name_de": null, "website": null, "status": "active", "short_abstract": "The goal of this project is to design and develop novel interactive visualization techniques to support knowledge workers in making sense of their unstructured, dynamic information collections. ", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. On the one hand, the studies show that, in some situations, interactive visualization can be less efficient than working with unprocessed text-based information. On the other hand, the studies also show that combining automatic data analysis with interactive visualization can lead to more unexpected findings, especially when exploring large data. The extent of manual information organization varies with the task: the less users know about the gathered information, the more automatic organization they expect. \n\nIn summary, this project contributed novel user interface concepts and design guidelines for user interfaces supporting information foraging and sensemaking. The techniques and study results were published at high-ranking peer-reviewed venues, and it can be expected that the findings of this project shape the way how users seek and organize their information in the future. \n\n", "start_date": "2015-12-01", "end_date": "2018-12-31", "leader_id": 1110, "logo": { "name": "logo.png", "path": "project:deskollage", "type": "image/png", "size": 331697, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/deskollage/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "T 752-N30", "comment": null } ], "research_areas": [ "InfoVis" ], "publications": [ "2019-ic", "byska-2019-mdfc", "casellato-2016-pkg", "cizmic-2018-evd", "donabauer-2015-asc", "dworschak-2016-szcm", "edlinger-2018-vwr", "georgiev-2019-cbg", "geymayer-2017-std", "gundacker-2020-wlm", "gusenbauer-2018", "hromniak-2019-vcn", "Koszticsak-2017-ewt", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "polatsek-2018-stv", "samoul-2019-cnp", "sietzen-2019-wnn", "sietzen-ifv-2019", "smiech-2018-tei", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "trautner-2018-imd", "unger-2019_vcp", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg" ], "url": "https://www.cg.tuwien.ac.at/research/projects/deskollage", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/waldner-2019-rld/", "__class": "Publication" }, { "id": "sietzen-ifv-2019", "type_id": "otherreviewed", "tu_id": null, "repositum_id": null, "title": "Interactive Feature Visualization in the Browser", "date": "2019-10", "abstract": "Excellent explanations of feature visualization already exist in the form of interactive articles, e.g. DeepDream, Feature Visualization, The Building Blocks of Interpretability, Activation Atlas, Visualizing GoogLeNet Classes. They mostly rely on curated prerendered visualizations, additionally providing colab notebooks or public repositories allowing the reader to reproduce those results. While precalculated visualizations have many advantages (directability, more processing budget), they are always discretized samples of a continuous parameter space. In the spirit of Tensorflow Playground, this project aims at providing a fully interactive interface to some basic functionality of the originally Python-based Lucid library, roughly corresponding to the concepts presented in the “Feature Visualization\" article. The user is invited to explore the effect of parameter changes in a playful way and without requiring any knowledge of programming, enabled by an implementation on top of TensorFlow.js. Live updates of the generated input image as well as feature map activations should give the user a visual intuition to the otherwise abstract optimization process. 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", "main_file": 1 }, { "href": "https://visxai.io/", "caption": "VISxAI Workshop 2019", "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "screenshot", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 759, "image_height": 614, "name": "sietzen-ifv-2019-screenshot.png", "type": "image/png", "size": 293509, "path": "Publication:sietzen-ifv-2019", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/sietzen-ifv-2019/sietzen-ifv-2019-screenshot.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/sietzen-ifv-2019/sietzen-ifv-2019-screenshot:thumb{{size}}.png" }, { "description": null, "filetitle": "video", "main_file": true, "use_in_gallery": false, "access": "public", "name": "sietzen-ifv-2019-video.mp4", "type": "video/mp4", "size": 51123687, "path": "Publication:sietzen-ifv-2019", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/sietzen-ifv-2019/sietzen-ifv-2019-video.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/sietzen-ifv-2019/sietzen-ifv-2019-video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2019/sietzen-ifv-2019/sietzen-ifv-2019-video:video.mp4" } ], "projects_workgroups": [ { "id": "deskollage", "workgroup_id": "vis", "drupal_id": 4198, "name": "Visual Information Foraging on the Desktop", "name_de": null, "website": null, "status": "active", "short_abstract": "The goal of this project is to design and develop novel interactive visualization techniques to support knowledge workers in making sense of their unstructured, dynamic information collections. ", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. On the one hand, the studies show that, in some situations, interactive visualization can be less efficient than working with unprocessed text-based information. On the other hand, the studies also show that combining automatic data analysis with interactive visualization can lead to more unexpected findings, especially when exploring large data. The extent of manual information organization varies with the task: the less users know about the gathered information, the more automatic organization they expect. \n\nIn summary, this project contributed novel user interface concepts and design guidelines for user interfaces supporting information foraging and sensemaking. The techniques and study results were published at high-ranking peer-reviewed venues, and it can be expected that the findings of this project shape the way how users seek and organize their information in the future. \n\n", "start_date": "2015-12-01", "end_date": "2018-12-31", "leader_id": 1110, "logo": { "name": "logo.png", "path": "project:deskollage", "type": "image/png", "size": 331697, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/deskollage/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "T 752-N30", "comment": null } ], "research_areas": [ "InfoVis" ], "publications": [ "2019-ic", "byska-2019-mdfc", "casellato-2016-pkg", "cizmic-2018-evd", "donabauer-2015-asc", "dworschak-2016-szcm", "edlinger-2018-vwr", "georgiev-2019-cbg", "geymayer-2017-std", "gundacker-2020-wlm", "gusenbauer-2018", "hromniak-2019-vcn", "Koszticsak-2017-ewt", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "polatsek-2018-stv", "samoul-2019-cnp", "sietzen-2019-wnn", "sietzen-ifv-2019", "smiech-2018-tei", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "trautner-2018-imd", "unger-2019_vcp", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg" ], "url": "https://www.cg.tuwien.ac.at/research/projects/deskollage", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/sietzen-ifv-2019/", "__class": "Publication" }, { "id": "2019-ic", "type_id": "techreport", "tu_id": 282845, "repositum_id": null, "title": "Collecting and Structuring Information in the Information Collage", "date": "2019-08", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. These processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. In this paper, we present the concept of an information collage (IC) -- a web browser extension combining manual spatial organization of gathered information fragments and automatic text analysis for interactive content exploration and expressive visual summaries. We used IC for case studies with knowledge workers from different domains and longer-term field studies over a period of one month. We identified three different ways how users collect and structure information and provide design recommendations how to support these observed usage strategies. 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"status": "active", "short_abstract": "The goal of this project is to design and develop novel interactive visualization techniques to support knowledge workers in making sense of their unstructured, dynamic information collections. ", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. 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unstructured, dynamic information collections. ", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. On the one hand, the studies show that, in some situations, interactive visualization can be less efficient than working with unprocessed text-based information. On the other hand, the studies also show that combining automatic data analysis with interactive visualization can lead to more unexpected findings, especially when exploring large data. The extent of manual information organization varies with the task: the less users know about the gathered information, the more automatic organization they expect. \n\nIn summary, this project contributed novel user interface concepts and design guidelines for user interfaces supporting information foraging and sensemaking. The techniques and study results were published at high-ranking peer-reviewed venues, and it can be expected that the findings of this project shape the way how users seek and organize their information in the future. \n\n", "start_date": "2015-12-01", "end_date": "2018-12-31", "leader_id": 1110, "logo": { "name": "logo.png", "path": "project:deskollage", "type": "image/png", "size": 331697, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/deskollage/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "T 752-N30", "comment": null } ], "research_areas": [ "InfoVis" ], "publications": [ "2019-ic", "byska-2019-mdfc", "casellato-2016-pkg", "cizmic-2018-evd", "donabauer-2015-asc", "dworschak-2016-szcm", "edlinger-2018-vwr", "georgiev-2019-cbg", "geymayer-2017-std", "gundacker-2020-wlm", "gusenbauer-2018", "hromniak-2019-vcn", "Koszticsak-2017-ewt", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "polatsek-2018-stv", "samoul-2019-cnp", "sietzen-2019-wnn", "sietzen-ifv-2019", "smiech-2018-tei", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "trautner-2018-imd", "unger-2019_vcp", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg" ], "url": "https://www.cg.tuwien.ac.at/research/projects/deskollage", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/sietzen-2019-wnn/", "__class": "Publication" }, { "id": "byska-2019-mdfc", "type_id": "journalpaper", "tu_id": 283263, "repositum_id": null, "title": "Analysis of Long Molecular Dynamics Simulations Using Interactive Focus+Context Visualization", "date": "2019-06", "abstract": "Analyzing molecular dynamics (MD) simulations is a key aspect to understand protein dynamics and function. With increasing computational power, it is now possible to generate very long and complex simulations, which are cumbersome to explore using traditional 3D animations of protein movements. Guided by requirements derived from multiple focus groups with protein engineering experts, we designed and developed a novel interactive visual analysis approach for long and crowded MD simulations. In this approach, we link a dynamic 3D focus+context visualization with a 2D chart of time series data to guide the detection and navigation towards important spatio-temporal events. The 3D visualization renders elements of interest in more detail and increases the temporal resolution dependent on the time series data or the spatial region of interest. In case studies with different MD simulation data sets and research questions, we found that the proposed visual analysis approach facilitates exploratory analysis to generate, confirm, or reject hypotheses about causalities. Finally, we derived design guidelines for interactive visual analysis of complex MD simulation data.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 783, "image_height": 717, "name": "byska-2019-mdfc-teaser.jpg", "type": "image/jpeg", "size": 95308, "path": "Publication:byska-2019-mdfc", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/byska-2019-mdfc/byska-2019-mdfc-teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/byska-2019-mdfc/byska-2019-mdfc-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "authors": [ { "id": 1254, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Jan", "lastname": "Byska", "searchname": "Jan Byska", "is_teacher": false, "name": "Jan Byska", "publications": [ "byska-2019-mdfc", "Furmanova_2018", "Groeller-2017-PTPMD", "raidou_pingu2020", "sMolBoxes_2022", "vad_viktor-2017-WVE", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "byska-2019-mdfc", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Viola_Ivan_2015_AAM", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Viola_Ivan_2015_MCT", "field_id": "lecturer", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1254", "__class": "Author" }, { "id": 1196, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Thomas", "lastname": "Trautner", "searchname": "Thomas Trautner", "is_teacher": false, "name": "Thomas Trautner", "publications": [ "byska-2019-mdfc", "Trautner_Thomas_2014_VAE", "trautner-2018-imd" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1196", 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false, "use_in_gallery": true, "access": "public", "image_width": 783, "image_height": 717, "name": "byska-2019-mdfc-teaser.jpg", "type": "image/jpeg", "size": 95308, "path": "Publication:byska-2019-mdfc", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/byska-2019-mdfc/byska-2019-mdfc-teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/byska-2019-mdfc/byska-2019-mdfc-teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "video", "main_file": true, "use_in_gallery": false, "access": "public", "name": "byska-2019-mdfc-video.mp4", "type": "video/mp4", "size": 222623560, "path": "Publication:byska-2019-mdfc", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/byska-2019-mdfc/byska-2019-mdfc-video.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/byska-2019-mdfc/byska-2019-mdfc-video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2019/byska-2019-mdfc/byska-2019-mdfc-video:video.mp4" } ], "projects_workgroups": [ { "id": "deskollage", "workgroup_id": "vis", "drupal_id": 4198, "name": "Visual Information Foraging on the Desktop", "name_de": null, "website": null, "status": "active", "short_abstract": "The goal of this project is to design and develop novel interactive visualization techniques to support knowledge workers in making sense of their unstructured, dynamic information collections. ", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. On the one hand, the studies show that, in some situations, interactive visualization can be less efficient than working with unprocessed text-based information. On the other hand, the studies also show that combining automatic data analysis with interactive visualization can lead to more unexpected findings, especially when exploring large data. The extent of manual information organization varies with the task: the less users know about the gathered information, the more automatic organization they expect. \n\nIn summary, this project contributed novel user interface concepts and design guidelines for user interfaces supporting information foraging and sensemaking. The techniques and study results were published at high-ranking peer-reviewed venues, and it can be expected that the findings of this project shape the way how users seek and organize their information in the future. \n\n", "start_date": "2015-12-01", "end_date": "2018-12-31", "leader_id": 1110, "logo": { "name": "logo.png", "path": "project:deskollage", "type": "image/png", "size": 331697, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/deskollage/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "T 752-N30", "comment": null } ], "research_areas": [ "InfoVis" ], "publications": [ "2019-ic", "byska-2019-mdfc", "casellato-2016-pkg", "cizmic-2018-evd", "donabauer-2015-asc", "dworschak-2016-szcm", "edlinger-2018-vwr", "georgiev-2019-cbg", "geymayer-2017-std", "gundacker-2020-wlm", "gusenbauer-2018", "hromniak-2019-vcn", "Koszticsak-2017-ewt", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "polatsek-2018-stv", "samoul-2019-cnp", "sietzen-2019-wnn", "sietzen-ifv-2019", "smiech-2018-tei", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "trautner-2018-imd", "unger-2019_vcp", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg" ], "url": "https://www.cg.tuwien.ac.at/research/projects/deskollage", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/byska-2019-mdfc/", "__class": "Publication" }, { "id": "samoul-2019-cnp", "type_id": "studentproject", "tu_id": null, "repositum_id": null, "title": "Visual Comparison of NLP Pipelines", "date": "2019-04", "abstract": "Natural Language Processing (NLP) is a sub-field of artificial intelligence (AI). It enables computers to understand, process\nand analyze large amounts of unstructured natural language data (raw text). Nowadays with the new techniques of machine\nlearning, we got good performance and brings us closer to unfolding the semantic meaning of the text. However, it is far\nfrom perfect. Therefore, an alternative approach to helping humans understand a text corpus is to provide a visualization of the\ncontent. To generate such a visualization, several NLP steps are necessary to convert the raw text into features, such as weighted\nkeywords or phrases, that can be visualized. The words to be visualized and their weights strongly depend on which NLP steps\nare performed, in which order, and with which parameters. However, there is currently no standard how to set up such an\nNLP pipeline and NLP pipeline configurations vary significantly across visualizations and input texts. Our project consists of\nvisualizing high dimensional data with different pre-processing steps with a different order. To compare the results, we choose\na well-known and wide-spread overview visualization technique: word clouds. Word clouds are composed of words used in a\nparticular text or subject, in which the size of each word indicates its weight computed in the course of the NLP pipeline.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "screenshot", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1599, "image_height": 754, "name": "samoul-2019-cnp-screenshot.jpg", "type": "image/jpeg", "size": 415531, "path": "Publication:samoul-2019-cnp", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/samoul-2019-cnp/samoul-2019-cnp-screenshot.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/samoul-2019-cnp/samoul-2019-cnp-screenshot:thumb{{size}}.png" }, "sync_repositum_override": null, "authors": [ { "id": 1644, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Muhammad", "lastname": "Samoul", "searchname": "Muhammad Samoul", "is_teacher": false, "name": "Muhammad Samoul", "publications": [ "samoul-2019-cnp" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1644", "__class": "Author" } ], "date_end": "2019-04", "date_start": "2018-11", "matrikelnr": "11833154", "supervisor": [ { "id": 1110, "drupal_id": 625, "orcid_id": "0000-0003-1387-5132", "website": "https://www.cg.tuwien.ac.at/staff/ManuelaWaldner", "firstname": "Manuela", "lastname": "Waldner", "searchname": "Manuela Waldner", "is_teacher": true, "name": "Manuela Waldner", "publications": [ "2019-ic", "Alharbi_2021", "bernhard-2016-gft", "byska-2019-mdfc", "eschner-2023-evl", "eschner-2023-ims", "geymayer-2017-std", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", "indirectBiasLanguageModels-2023", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "mazurek-2018-veq", "polatsek-2018-stv", "reina-2020-mtv", "sietzen-2021-perturber", "sietzen-ifv-2019", "sMolBoxes_2022", "sorger-2019-odn", "sorger-2021-egonet", "steinboeck-2018-lbg", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2013-facetCloudsGI", "waldner-2013-ubiWM", "waldner-2014-af", "waldner-2014-ghi", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "webGPU_aggregateVis-2023", "wu-2021", "wu-2021-vi" ], "publications_first": [], "project_leader": [ "d9282", "d9522", "d9555", "deskollage" ], "publication_field": [ { "publ_id": "arbesser_ba_2023", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "bayat-2022-mva", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "boesch_2014_browserHistoryVis", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "breitenecker-2020-bct", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "bugnar-esk-2021", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": 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"publ_id": "gundacker-2020-wlm", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "gusenbauer-2018", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "heim-gall-2020-dde", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "hromniak-2019-vcn", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "indirectBiasLanguageModels-2023", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "kimmersdorfer-fancyMaps-2023", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "korpitsch-2021-lov", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Koszticsak-2017-ewt", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "lippeck-2022-mna", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "louis-alexandre_dit_petit-frere-2022-veo", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "mahler-2021-mdar", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "matt-2023-vae", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "mayr-2021-wec", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "mazurek-2017-sio", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "mazurek-2017-vows", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "mazurek-2018-vac", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Panayotov", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Presch_2020", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "samoul-2019-cnp", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "sbardellati-2021-eveos", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "sietzen-2019-wnn", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "sietzen-2022-vacnnr", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "smiech-2018-tei", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "spegel-gruenberger-2020", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "staats-2024-atr", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "steinboeck-2017-vbn", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "steinboeck-2017-vefp", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "steinboeck-2018-lbg", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "stoff-concepMap-2021", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "textures-3d-printing", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "trautner-2018-imd", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "unger-2019_vcp", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Unger2020", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "waldner-2013-ubiWM", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldner-2014-af", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldner-2014-ghi", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldner-2017-vph", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldner-2019-rld", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "webGPU_aggregateVis-2023", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "wolf-2023-cc", "field_id": "supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1110", "__class": "Author" } ], "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.
\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", 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"https://www.cg.tuwien.ac.at/research/publications/2019/samoul-2019-cnp/samoul-2019-cnp-Report.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/samoul-2019-cnp/samoul-2019-cnp-Report:thumb{{size}}.png" }, { "description": null, "filetitle": "screenshot", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1599, "image_height": 754, "name": "samoul-2019-cnp-screenshot.jpg", "type": "image/jpeg", "size": 415531, "path": "Publication:samoul-2019-cnp", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/samoul-2019-cnp/samoul-2019-cnp-screenshot.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/samoul-2019-cnp/samoul-2019-cnp-screenshot:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "deskollage", "workgroup_id": "vis", "drupal_id": 4198, "name": "Visual Information Foraging on the Desktop", "name_de": null, "website": null, "status": "active", "short_abstract": "The goal of this project is to design and develop novel interactive visualization techniques to support knowledge workers in making sense of their unstructured, dynamic information collections. ", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. On the one hand, the studies show that, in some situations, interactive visualization can be less efficient than working with unprocessed text-based information. On the other hand, the studies also show that combining automatic data analysis with interactive visualization can lead to more unexpected findings, especially when exploring large data. The extent of manual information organization varies with the task: the less users know about the gathered information, the more automatic organization they expect. \n\nIn summary, this project contributed novel user interface concepts and design guidelines for user interfaces supporting information foraging and sensemaking. The techniques and study results were published at high-ranking peer-reviewed venues, and it can be expected that the findings of this project shape the way how users seek and organize their information in the future. \n\n", "start_date": "2015-12-01", "end_date": "2018-12-31", "leader_id": 1110, "logo": { "name": "logo.png", "path": "project:deskollage", "type": "image/png", "size": 331697, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/deskollage/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "T 752-N30", "comment": null } ], "research_areas": [ "InfoVis" ], "publications": [ "2019-ic", "byska-2019-mdfc", "casellato-2016-pkg", "cizmic-2018-evd", "donabauer-2015-asc", "dworschak-2016-szcm", "edlinger-2018-vwr", "georgiev-2019-cbg", "geymayer-2017-std", "gundacker-2020-wlm", "gusenbauer-2018", "hromniak-2019-vcn", "Koszticsak-2017-ewt", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "polatsek-2018-stv", "samoul-2019-cnp", "sietzen-2019-wnn", "sietzen-ifv-2019", "smiech-2018-tei", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "trautner-2018-imd", "unger-2019_vcp", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg" ], "url": "https://www.cg.tuwien.ac.at/research/projects/deskollage", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/samoul-2019-cnp/", "__class": "Publication" }, { "id": "waldin-2019-ccm", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": null, "title": "Cuttlefish: Color Mapping for Dynamic Multi‐Scale Visualizations", "date": "2019-03", "abstract": "Visualizations of hierarchical data can often be explored interactively. For example, in geographic visualization, there are continents, which can be subdivided into countries, states, counties and cities. Similarly, in models of viruses or bacteria at the highest level are the compartments, and below that are macromolecules, secondary structures (such as α‐helices), amino‐acids, and on the finest level atoms. Distinguishing between items can be assisted through the use of color at all levels. However, currently, there are no hierarchical and adaptive color mapping techniques for very large multi‐scale visualizations that can be explored interactively. We present a novel, multi‐scale, color‐mapping technique for adaptively adjusting the color scheme to the current view and scale. Color is treated as a resource and is smoothly redistributed. The distribution adjusts to the scale of the currently observed detail and maximizes the color range utilization given current viewing requirements. Thus, we ensure that the user is able to distinguish items on any level, even if the color is not constant for a particular feature. The coloring technique is demonstrated for a political map and a mesoscale structural model of HIV. The technique has been tested by users with expertise in structural biology and was overall well received.", "authors_et_al": false, "substitute": null, "main_image": { "description": "Multiple color zoom levels. 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"publ_id": "Viola_Ivan_2013_HQ3", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Viola-05-Smart", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "viola-2007-ort", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Viola-Pondering-2017", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "vis-foa", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldin-2017-thesis", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Wihann_2017", "field_id": "supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=171", "__class": "Author" } ], "doi": "10.1111/cgf.13611", "journal": "Computer Graphics Forum", "number": "6", "pages_from": "150", "pages_to": "164", "volume": "38", "research_areas": [ { "id": "BioVis", "drupal_id": 4127, "name": "Biological Data Visualization", "short_abstract": "In this research area, we develop new visualization techniques to support biologists in data analysis and create visualizations to disseminate scientific discoveries in biology.", "abstract": "In modern biological research domain experts have to deal with complex and large data collections and simulations. Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n", "website": "https://www.cg.tuwien.ac.at/research/area/BioVis", "teaser": { "name": "teaser.png", "path": "research_area:BioVis", "type": "image/png", "size": 16330957, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/BioVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "amirkhanov-2019-manylands", "byska-2019-mdfc", "cellVIEW_2015", "cmolik-2020-tvcg", "Dietrich_1", "dietrich-2016-viseq2", "Ehlers_PhD", "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.
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"viola-2006-FoA", "viola-evr", "Viola-Pondering-2017", "viola-popular-article-2006", "Viola-vistutillustrativevis", "vis-foa", "VisWeek-Tutorial-2012-Uncertainty", "vitruvian_2019", "voglreiter-2023-tro", "Vucenovic_2022", "vucini_2006", "vucini_2008_rnp", "vucini_2009", "vucini_erald-2007-FRI", "vucini-2009-phd", "vucini-2011", "Wagner_032017", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "Waldin_Nicholas_2017_FlickerObserver", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2017-thesis", "waldin-2019-ccm", "waldin-2019-ccm", "Waldner_2017_11", "Waldner_2017_11", "waldner-2013-facetCloudsGI", "waldner-2013-ubiWM", "waldner-2014-af", "waldner-2014-ghi", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "waser_2011_VSD", "Waser-2010-WL", "webGPU_aggregateVis-2023", "weiner_2011", "Weissenboeck_2019", "Weissenboeck_2019_PhD", "weissenboeck-2014", "Wihann_2017", "wolf-2023-cc", "Woschizka_2021", "wu-2017-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-shonan", "wu-2018-story", "wu-2019-bmc", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-smwp", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg", "wu-2021", "wu-2021-vi", "xmastree2002", "xmastree2005", "ymca", "YOGHOURDJIAN2019", "Zambal-2003-SWA", "zambal-2005-3dact", "Zaufel_2021", "zauner-2013-svkinect", "zechmeister2020", "Zeng_2021", "Zhu-2014-flowvis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Workgroup&id=vis", "__class": "Workgroup" }, { "id": "deskollage", "workgroup_id": "vis", "drupal_id": 4198, "name": "Visual Information Foraging on the Desktop", "name_de": null, "website": null, "status": "active", "short_abstract": "The goal of this project is to design and develop novel interactive visualization techniques to support knowledge workers in making sense of their unstructured, dynamic information collections. ", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. On the one hand, the studies show that, in some situations, interactive visualization can be less efficient than working with unprocessed text-based information. On the other hand, the studies also show that combining automatic data analysis with interactive visualization can lead to more unexpected findings, especially when exploring large data. The extent of manual information organization varies with the task: the less users know about the gathered information, the more automatic organization they expect. \n\nIn summary, this project contributed novel user interface concepts and design guidelines for user interfaces supporting information foraging and sensemaking. The techniques and study results were published at high-ranking peer-reviewed venues, and it can be expected that the findings of this project shape the way how users seek and organize their information in the future. \n\n", "start_date": "2015-12-01", "end_date": "2018-12-31", "leader_id": 1110, "logo": { "name": "logo.png", "path": "project:deskollage", "type": "image/png", "size": 331697, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/deskollage/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "T 752-N30", "comment": null } ], "research_areas": [ "InfoVis" ], "publications": [ "2019-ic", "byska-2019-mdfc", "casellato-2016-pkg", "cizmic-2018-evd", "donabauer-2015-asc", "dworschak-2016-szcm", "edlinger-2018-vwr", "georgiev-2019-cbg", "geymayer-2017-std", "gundacker-2020-wlm", "gusenbauer-2018", "hromniak-2019-vcn", "Koszticsak-2017-ewt", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "polatsek-2018-stv", "samoul-2019-cnp", "sietzen-2019-wnn", "sietzen-ifv-2019", "smiech-2018-tei", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "trautner-2018-imd", "unger-2019_vcp", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg" ], "url": "https://www.cg.tuwien.ac.at/research/projects/deskollage", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/waldin-2019-ccm/", "__class": "Publication" }, { "id": "unger-2019_vcp", "type_id": "studentproject", "tu_id": null, "repositum_id": null, "title": "Visual Comparison of Organism-Specific Metabolic Pathways", "date": "2019-02", "abstract": "The Kyoto Encyclopaedia of Genes and Genomes\n(KEGG) resource is a combination of multiple databases,\ncontaining information about biochemical compounds, reactions,\npathways, genes and much more. This database\nis one of the main resources for bioinformaticians and biologists\nto gain an understanding of molecular functionality\ninside organisms. The Orthology (KO) database from\nKEGG assigns pathways and genes with identical functionality\nto the same ortholog groups (KO entries). Therefore\nit is possible to map genes onto the pathway maps\nand obtain organism-specific visualizations. KEGG offers\na web-based graph visualization to explore these pathways,\nhowever, the interaction possibilities are restricted\nand the rendering is inefficient. It is possible to visualize\norganism-specific pathways but a visual analysis tool to\ncompare ortholog groups of multiple organisms is missing.\nIn this work, we present an efficient interactive web application\nto compare ortholog groups of multiple organisms\nin the metabolic reference pathway. We introduce a graph\noverlay technique to mark the differences and similarities\nbetween multiple organisms and demonstrate it with two\nuse cases. Additionally, we compare it against an existing\npoint set membership visualization.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "screenshot", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1117, "image_height": 742, "name": "unger-2019_vcp-screenshot.png", "type": "image/png", "size": 563486, "path": "Publication:unger-2019_vcp", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/unger-2019_vcp/unger-2019_vcp-screenshot.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/unger-2019_vcp/unger-2019_vcp-screenshot:thumb{{size}}.png" }, "sync_repositum_override": null, "authors": [ { "id": 1530, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Katharina", "lastname": "Unger", "searchname": "Katharina Unger", "is_teacher": false, "name": "Katharina Unger", "publications": [ "unger_2017", "unger-2019_vcp", "Unger2020" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1530", "__class": "Author" } ], "date_end": "2019-02", "date_start": "2018-10", "matrikelnr": "01325652", "supervisor": [ { "id": 1110, "drupal_id": 625, "orcid_id": "0000-0003-1387-5132", "website": "https://www.cg.tuwien.ac.at/staff/ManuelaWaldner", "firstname": "Manuela", "lastname": "Waldner", "searchname": "Manuela Waldner", "is_teacher": true, "name": "Manuela Waldner", "publications": [ "2019-ic", "Alharbi_2021", "bernhard-2016-gft", "byska-2019-mdfc", "eschner-2023-evl", "eschner-2023-ims", "geymayer-2017-std", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", "indirectBiasLanguageModels-2023", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "mazurek-2018-veq", "polatsek-2018-stv", "reina-2020-mtv", "sietzen-2021-perturber", "sietzen-ifv-2019", "sMolBoxes_2022", "sorger-2019-odn", "sorger-2021-egonet", "steinboeck-2018-lbg", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2013-facetCloudsGI", "waldner-2013-ubiWM", "waldner-2014-af", "waldner-2014-ghi", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "webGPU_aggregateVis-2023", "wu-2021", "wu-2021-vi" ], "publications_first": [], "project_leader": [ "d9282", "d9522", "d9555", "deskollage" ], "publication_field": [ { "publ_id": "arbesser_ba_2023", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "bayat-2022-mva", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "boesch_2014_browserHistoryVis", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "breitenecker-2020-bct", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "bugnar-esk-2021", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "casellato-2016-pkg", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": 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"steinboeck-2017-vefp", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "steinboeck-2018-lbg", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "stoff-concepMap-2021", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "textures-3d-printing", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "trautner-2018-imd", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "unger-2019_vcp", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Unger2020", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "waldner-2013-ubiWM", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldner-2014-af", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldner-2014-ghi", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldner-2017-vph", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldner-2019-rld", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "webGPU_aggregateVis-2023", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": 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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.
\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": [ "pathways", "web-based visualization" ], "weblinks": [ { "href": "https://users.cg.tuwien.ac.at/kunger/pr-pathway-exploration/", "caption": "Online tool", "description": "Best to be used with Chrome. Enter the organisms to be compared by entering them as a string like this: \"eco+hsa+mmu\" (compares E-Coli, Homo Sapiens, and Mus Musculus). ", "main_file": 0 }, { "href": "https://www.genome.jp/kegg/catalog/org_list.html", "caption": "List of KEGG organisms", "description": "List of organisms available in KEGG. ", "main_file": 0 }, { "href": "https://cescg.org/cescg_submission/visual-comparison-of-organism-specific-metabolic-pathways/", "caption": "CESCG paper", "description": "Paper presented at the Central European Seminar on Computer Graphics 2019. ", "main_file": 0 } ], "files": [ { "description": null, "filetitle": "CESCG paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "unger-2019_vcp-CESCG paper.pdf", "type": "application/pdf", "size": 4980072, "path": "Publication:unger-2019_vcp", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/unger-2019_vcp/unger-2019_vcp-CESCG paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/unger-2019_vcp/unger-2019_vcp-CESCG paper:thumb{{size}}.png" }, { "description": null, "filetitle": "developer documentation", "main_file": false, "use_in_gallery": false, "access": "public", "name": "unger-2019_vcp-developer documentation.pdf", "type": "application/pdf", "size": 524187, "path": "Publication:unger-2019_vcp", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/unger-2019_vcp/unger-2019_vcp-developer documentation.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/unger-2019_vcp/unger-2019_vcp-developer documentation:thumb{{size}}.png" }, { "description": null, "filetitle": "screenshot", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1117, "image_height": 742, "name": "unger-2019_vcp-screenshot.png", "type": "image/png", "size": 563486, "path": "Publication:unger-2019_vcp", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/unger-2019_vcp/unger-2019_vcp-screenshot.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/unger-2019_vcp/unger-2019_vcp-screenshot:thumb{{size}}.png" }, { "description": null, "filetitle": "user documentation", "main_file": false, "use_in_gallery": false, "access": "public", "name": "unger-2019_vcp-user documentation.pdf", "type": "application/pdf", "size": 58613, "path": "Publication:unger-2019_vcp", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/unger-2019_vcp/unger-2019_vcp-user documentation.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/unger-2019_vcp/unger-2019_vcp-user documentation:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "deskollage", "workgroup_id": "vis", "drupal_id": 4198, "name": "Visual Information Foraging on the Desktop", "name_de": null, "website": null, "status": "active", "short_abstract": "The goal of this project is to design and develop novel interactive visualization techniques to support knowledge workers in making sense of their unstructured, dynamic information collections. ", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. On the one hand, the studies show that, in some situations, interactive visualization can be less efficient than working with unprocessed text-based information. On the other hand, the studies also show that combining automatic data analysis with interactive visualization can lead to more unexpected findings, especially when exploring large data. The extent of manual information organization varies with the task: the less users know about the gathered information, the more automatic organization they expect. \n\nIn summary, this project contributed novel user interface concepts and design guidelines for user interfaces supporting information foraging and sensemaking. The techniques and study results were published at high-ranking peer-reviewed venues, and it can be expected that the findings of this project shape the way how users seek and organize their information in the future. \n\n", "start_date": "2015-12-01", "end_date": "2018-12-31", "leader_id": 1110, "logo": { "name": "logo.png", "path": "project:deskollage", "type": "image/png", "size": 331697, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/deskollage/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "T 752-N30", "comment": null } ], "research_areas": [ "InfoVis" ], "publications": [ "2019-ic", "byska-2019-mdfc", "casellato-2016-pkg", "cizmic-2018-evd", "donabauer-2015-asc", "dworschak-2016-szcm", "edlinger-2018-vwr", "georgiev-2019-cbg", "geymayer-2017-std", "gundacker-2020-wlm", "gusenbauer-2018", "hromniak-2019-vcn", "Koszticsak-2017-ewt", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "polatsek-2018-stv", "samoul-2019-cnp", "sietzen-2019-wnn", "sietzen-ifv-2019", "smiech-2018-tei", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "trautner-2018-imd", "unger-2019_vcp", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg" ], "url": "https://www.cg.tuwien.ac.at/research/projects/deskollage", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/unger-2019_vcp/", "__class": "Publication" }, { "id": "hromniak-2019-vcn", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Visual Comparison of Natural Language Processing Pipelines", "date": "2019-01", "abstract": "Natural Language Processing comprises a variety of operations that can be applied on\nraw text to extract features. The sequence of operations is called NLP pipeline. However,\nthe sequence and parameters of these individual operations differ between applications.\nIn each step of the ongoing sequence, a single process is performed with a specialized task.\nSuch a task can be the determination of the end of sentences or the removal of so-called\nstop words. There is no best-practice which combination is most effective and accurate\nto determine the descriptive features (key words) of a single document. The goal of this\nbachelor thesis is to compute the features of different variations of NLP pipelines and\nvisualize them as basic word clouds. It is also important to know how the resulting word\ncloud of each pipeline is affected by varying the order of certain steps, adding steps or\nremoving steps. The presented interface gives an overview of performance and similarity\nvalues of each computed pipeline.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "screenshot", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 512, "image_height": 486, "name": "hromniak-2019-vcn-screenshot.png", "type": "image/png", "size": 37562, "path": "Publication:hromniak-2019-vcn", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/hromniak-2019-vcn/hromniak-2019-vcn-screenshot.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/hromniak-2019-vcn/hromniak-2019-vcn-screenshot:thumb{{size}}.png" }, "sync_repositum_override": null, "authors": [ { "id": 1556, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Patrick", "lastname": "Hromniak", "searchname": "Patrick Hromniak", "is_teacher": false, "name": "Patrick Hromniak", 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"https://www.cg.tuwien.ac.at/research/publications/2019/hromniak-2019-vcn/hromniak-2019-vcn-screenshot.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/hromniak-2019-vcn/hromniak-2019-vcn-screenshot:thumb{{size}}.png" }, "2": { "description": null, "filetitle": "thesis", "main_file": false, "use_in_gallery": false, "access": "public", "name": "hromniak-2019-vcn-thesis.pdf", "type": "application/pdf", "size": 1302404, "path": "Publication:hromniak-2019-vcn", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/hromniak-2019-vcn/hromniak-2019-vcn-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/hromniak-2019-vcn/hromniak-2019-vcn-thesis:thumb{{size}}.png" } }, "projects_workgroups": [ { "id": "deskollage", "workgroup_id": "vis", "drupal_id": 4198, "name": "Visual Information Foraging on the Desktop", "name_de": null, "website": null, "status": "active", "short_abstract": "The goal of this project is to design and develop novel interactive visualization techniques to support knowledge workers in making sense of their unstructured, dynamic information collections. ", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. On the one hand, the studies show that, in some situations, interactive visualization can be less efficient than working with unprocessed text-based information. On the other hand, the studies also show that combining automatic data analysis with interactive visualization can lead to more unexpected findings, especially when exploring large data. The extent of manual information organization varies with the task: the less users know about the gathered information, the more automatic organization they expect. \n\nIn summary, this project contributed novel user interface concepts and design guidelines for user interfaces supporting information foraging and sensemaking. The techniques and study results were published at high-ranking peer-reviewed venues, and it can be expected that the findings of this project shape the way how users seek and organize their information in the future. \n\n", "start_date": "2015-12-01", "end_date": "2018-12-31", "leader_id": 1110, "logo": { "name": "logo.png", "path": "project:deskollage", "type": "image/png", "size": 331697, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/deskollage/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "T 752-N30", "comment": null } ], "research_areas": [ "InfoVis" ], "publications": [ "2019-ic", "byska-2019-mdfc", "casellato-2016-pkg", "cizmic-2018-evd", "donabauer-2015-asc", "dworschak-2016-szcm", "edlinger-2018-vwr", "georgiev-2019-cbg", "geymayer-2017-std", "gundacker-2020-wlm", "gusenbauer-2018", "hromniak-2019-vcn", "Koszticsak-2017-ewt", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "polatsek-2018-stv", "samoul-2019-cnp", "sietzen-2019-wnn", "sietzen-ifv-2019", "smiech-2018-tei", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "trautner-2018-imd", "unger-2019_vcp", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg" ], "url": "https://www.cg.tuwien.ac.at/research/projects/deskollage", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/hromniak-2019-vcn/", "__class": "Publication" }, { "id": "trautner-2018-imd", "type_id": "masterthesis", "tu_id": null, "repositum_id": "20.500.12708/7274", "title": "Importance-Driven Exploration of Molecular Dynamics Simulations", "date": "2018-10-03", "abstract": "The aim of this thesis is a novel real-time visualization approach for exploring molecular dynamics (MD-)simulations. Through the constantly improving hardware and everincreasing computing power, MD-simulations are more easily available. Additionally, they consist of hundreds, thousands or even millions of individual simulation frames and are getting more and more detailed. The calculation of such simulations is no longer limited by algorithms or hardware, nevertheless it is still not possible to efficiently explore this huge amount of simulation data, as animated 3D visualization, with ordinary and well established visualization tools. Using current software tools, the exploration of such long simulations takes too much time and due to the complexity of large molecular scenes, the visualizations highly suffer from visual clutter. It is therefore very likely that the user will miss important events.\nTherefore, we designed a focus & context approach for MD-simulations that guides the\nuser to the most relevant temporal and spatial events, and it is no longer necessary to explore the simulation in a linear fashion. Our contribution can be divided into the following four topics:\n1. Spatial importance through different levels of detail. Depending on the type of\nresearch task, different geometrical representations can be selected for both, focusand context elements.\n2. Importance driven visibility management through ghosting, to prevent context\nelements from occluding focus elements.\n3. Temporal importance through adaptive fast-forward. The playback speed of the\nsimulation is thereby dependent on a single or a combination of multiple importance\nfunctions.\n4. Visual declutter of accumulated frames through motion blur, which additionally\nillustrates the playback speed-up.\nSince the very beginning, this work was developed in close cooperation with biochemists from the Loschmidt Laboratories in Brno, Czech Republic. Together, we analyzed different use cases demonstrating the flexibility of our novel focus & context approach. 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Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. 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By understanding the limits of human perception, we can design and optimize rendering algorithms that perfectly fit users' needs, tailor visualizations to make data better understandable, and effectively draw the user's attention to important information.
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"Groeller_2014_VND", "Groeller_2016_I2", "Groeller_2016_I7", "Groeller_2016_I8", "Groeller_2016_P2", "Groeller_2016_P4", "Groeller_2016_P6", "Groeller_2016_P7", "Groeller_2021_11", "Groeller_2021_BVM", "Groeller_2021-10", "Groeller_Edi_2013_TVC", "Groeller_Edi_2013_VCQ", "Groeller_Edi_2013TVCK", "Groeller_Edi_VKA", "Groeller_Eduard_2014_THS", "Groeller_Eduard_2014_TSP", "Groeller_Eduard_2014_UCT", "Groeller_Eduard_2015_SMV", "Groeller_Eduard_2015_TCU", "Groeller_V1_2020", "Groeller_V2_2020", "Groeller_V3_2020", "Groeller_V42020", "Groeller_V5_2020", "groeller-2004-efficient", "groeller-2004-imp", "groeller-2004-sci", "groeller-2005-dia", "Groeller-2010-CVC", "Groeller-2010-IFI", "Groeller-2010-IVVI", "Groeller-2011-HSH", "Groeller-2017-ARTORW", "Groeller-2017-AVC", "Groeller-2017-IVAMCS", "Groeller-2017-PTPMD", "Groller_2021-12-03", "Gronde_2008", "Grorller-2010-IVV", "grossmann_2019_pelvisrunner_poster", "Grossmann_MA", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", "grossmann-thesis", "Gruenauer-2011-CAT", "Gschwantner_2011_AMQ", "gundacker-2020-wlm", "Gurbat_2011_SBS", "gusenbauer-2018", "gusenbauer-2018", "gusenbauer-2018-P", "gutekunst_2019", "Hadwiger-2002-Fas", "haidacher_2010_statTF", "haidacher-2004-FVV", "haidacher-2005-MND", "haidacher-2007-idr", "haidacher-2008-vcbm", "haidacher-2011-MSM", "haidacher-2011-phd", "haidacher-2011-VAM", "Hainoun2019", "Halladjian_2020", "hanzl-2011", "hartl-2008-vcd", "hartmann-2005-adv", "haushofer-2018-skinning", "Heim_2020", "Heim_2021", "Heim-2017", "heim-gall-2020-dde", "heinzl_2006_RSDVCDM", "heinzl-2006-rep", "heinzl-2008-sam", "Heinzl2021", "Herghelegiu-2012-BPV", "herzberger-2023-swv", "herzberger-2024-roh", "Hirsch_Christian_2015_ABL", "Hladuvka-2002-Exp", "hladuvka-2002-exploiting", "Hochmayr_Manuel_2015_PSE", "hochmayr_manuel-2011-VoRMD", "Hochpoechler_2016_VR", "horvath-2018-ism", "hromniak-2019-vcn", "Iijima-2020-iV", "indirectBiasLanguageModels-2023", "irger-2023-ves", "Ismail-2018", "jank-2022-cbf", "Kanitsar-2002-CPR", "Kanitsar-2003-Adva", "Kanitsar-2003-Dem", "Kanitsar-2004-Dia", "Kanitsar-thesis", "kapferer-2017-godot", "Karall2017CVAB", "Karall2018_2", "karimov-2013-vivisection", "karimov-2015-HD", "karimov-2016-GIVE", "karimov-2016-SD", "keglevic_schulz-2011-MB", "Kehrer-2008-hyp", "Kehrer-2010-mom", "kehrer-2011-vai", "kehrer-2012-mod", "kehrer-2013-IVA", "kehrer-2013-SBC", "Kehrer-2013-STAR", "Kehrer-2014-CSD", "kimmersdorfer-fancyMaps-2023", "Kinkelin_2009", "Kinkelin-2011-VR", "Kleber-2004-TFE", "klein_2017_IM", "klein_2019_MSA_Poster", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "Klein_Tobias_2015TIV", "klein-thesis", "Knapp_2017_CVR", "knapp_michael_2004_MAS", "knapp-2004-semi", "koch_bernhard_2018-1", "koch-2018-sso", "koehle-2013-sgv", "koeppel-2021", "Koeppel2020", "Kohlmann-2007-EBV", "kohlmann-2007-livesync", "kohlmann-2008-lse", "kohlmann-2009-cp", "kohlmann-2009-lssl", "kolesar-ivan-2014-polymers", "Kolter_2021", "Konyha_2013_IVA", "korpitsch_thorsten-2019", "korpitsch-2020-cescg", "Korpitsch-2020-wscg", "korpitsch-2021-lov", "Koszticsak-2017-ewt", "Kouril_2017_11", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2018-LoL", "kouril-2018-LoL", "kouril-2020-hyperlabels", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kovacs_PhD", "krakhofer-2015", "Krone2016VABC", "kuehschelm-2005-adv", "Kugler_2019", "Kuroko-2020-iV", "Labschuetz_Matthias_2015_JIT", "Labschuetz_Matthias_2016_AHD", "Labschuetz_Matthias_2016_JIT", "Labschuetz_Matthias_2016_JITT", "Lackner_2022", "LaCruz2004", "Ladstaedter-2009-sim", "Langer_Edith_IR1", "Langer_Maximillian_DMV", "Laschober-2018", "lawonn-2018-illvisstar", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "LeMuzic_2016_PhD", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lemuzic-mindek-sorger-cgfcc", "Leutschacher_2022", "li-2019-gdc", "lie-2009-cri", "lipp-2017-mgpu", "lipp-2017-vulkan", "lippeck-2022-mna", "liu-2014-ac", "lkoell-2014", "ludwig-2012-MT", "Machegger2018DTI", "magg-2021-dva", "magg2021", "mahler-2021-mdar", "major-2010-mrf", "malan_fluoro", "malik-2007-FP", "malik-2009-CVFA", "malik-thesis", "Manczarski-2016", "Marek06", "Maricic_2013_VFE", "martorell2022", "maruyama-2019-iv", "Masopust_2018", "Masterthesis-Viola", "Matkovic_Kresimir_2015_", "matt-2023-vae", "matt-masterthesis", "Mattausch-2003-ISL", "Mattausch-2003-SIE", "Mattausch-2003-Str", "Matusich-2017-01", "Mautner 2020", "Mayr-2017-1", "mayr-2021-wec", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "Mazza_2020", "Mazza_2021_05", "Melo_2018_11", "Meusburger_2020", "Miao_2015_VCBM", "Miao_2019", "Miao_Haichao_2015_VQC", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_plitvice_2018", "miao_thesis_2019", "miao_tvcg_2017", "miao_tvcg_2018", "miao_tvcg_2018", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "Michl_2017_CSV", "mindek_peter-2012-visgroupproj", "mindek_peter-2014-cs_kaust", "mindek-2013-cs_cvut", "mindek-2013-csl", "mindek-2013-pel", "mindek-2014-mcs", "mindek-2014-vivi_cvut", "mindek-2015-mc", "mindek-2015-mctalk", "mindek-2016-utah-talk", "mindek-2017-dsn", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-2019-mci", "mindek-thesis", "mistelbauer_2013_SIV", "Mistelbauer_2021", "Mistelbauer_Gabriel_2015_NHR", "Mistelbauer_Gabriel_2016", "mistelbauer-2010-pvv", "mistelbauer-2012-cr", "mistelbauer-2012-ssv", "mistelbauer-2013-cfa", "mistelbauer-2015-abvv", "Mitterhofer_2017", "mizuno-2019-eurovis", "Mlejnek_2004_PF", "Mlejnek_2005_AOEPF", "Mlejnek_2006_MVOA", "Mlejnek-2004-Int", "Mlejnek-2004-ITVAC", "Mlinaric-2015-MT", "Moellinger_Christian_IDE2", "moerth_eric-2016-3DF", "moerth-2018-tpose", "monitzer_2008_FluSi", "Morar_2012_ISB", "Muehlbacher_diss_2018", "mueller-2009-ivs", "Muigg_2011_ISI", "Muigg_2011_VC", "Muigg-2008-four", "muigg-2012-svr", "Musleh_PhD", "Neumann-2002-Fea", "nguyen_2020-covid", "Niedermayer_2018", "Novotny_2013_ASVD", "Nowak_2020", "Nowak_2021", "Oancea_2018_1", "Oancea_Stefan_2016_VOT", "Oancea2018OAK", "oeltze-2013-tut", "opitz-2009-cvv", "Ortner_PhD", "Ortner2020", "Pahr_PhD", "pahr-2021-vologram", "pahr-thesis", "Pahr2020", "Pajer_2012_VoM", "Panayotov", "Parzer_2013_IIG", "patel_2009_MC", "patel_daniel_2007_IRSD", "patel-2008-tsa", "patel-2009-evr", "patel-2011-PEA", "Pauschenwein_2022", "Peter_2012_AIV", "Pezenka-2016-MT", "Pfahler_David_2015_IPI", "Pfahler-2016-MT", "PH-2011-LDS", "phd-viola", "Philipp_Hochhauser_2023", "Pilizar_-2020-bachelor", "piringer-2009-hds", "Plank_Pascal_2015_HVP", "plank-2017-sldg", "PMI_AR_2012", "pointner_simon-2020", "polatsek-2018-stv", "polatsek-2018-stv", "Pramerdorfer-2011-PAV", "preim-2009-sve", "Presch_2020", "Priselac2021", "puehringer-2009-sbm", "puenguentzky-2014-ht", "Purchase-2020-gd", "raidou_2018_bladderrunner", "raidou_2019_pelvisrunner", "raidou_2019_preha", "raidou_2019_springer", "raidou_2020Onc", "raidou_EuroVis15", "raidou_eurovis16", "raidou_miccai16", "raidou_pingu2020", "raidou_previs2021", "raidou_RO2019", "raidou_shonan167", "raidou_slicedice", "raidou_star2019", "raidou_vcbm14", "raidou_vis14", "raidou_vis15", "raidou_visgap2020", "raidou2018_rv3", "raidou2018visualflatter", "raidou2019_prsps", "rasch-2016-imgses", "Rau08", "Rautek_Peter_2014_TUC", "Rautek_Peter_2014_VSA", "rautek-2005-dvr", "Rautek-2007-O3D", "Rautek-2007-SLI", "Rautek-2008-IDS", "Rautek-2008-kav", "Rautek-2008-VF", "rautek-2009-vmv", "RAUTEK06", "Rautek06Vis", "Rautek06VMLS", "rautek2010", "Red_Andreas_2015_FFT", "Reh_Andreas_VoP", "reh-2013", "reina-2020-mtv", "Reisacher_Matthias_CPW", "Reisacher2016", "Reiter_2009_IXIA", "Reiter2017CVAP", "Rezk06Vis", "Ribicic_2012_SUS", "Ribicic_2012_VAS", "Ribicic-2010-CRS", "Riegelnegg_2019", "rinortner_susanne-2019-vpicc", "rinortner_susanne-2019-vpicc", "Rippberger_2019", "rippl-2023-atg", "ritzberger-2010-nar", "Ropinski-2012-UBT", "rraidou_clinical", "rraidou_EG17", "rraidou_phdbook", "rsabin-2013", "ruiz-2008-OVR", "ruiz-2008-SEV", "samoul-2019-cnp", "Sanjin_Rados_RV", "Sarkis_2021", "Sbardellati-2019-vcbm", "Sbardellati-2019-vcbm", "sbardellati-2021-eveos", "scharsach-2005-adv", "Schernthaner-2017-MCP", "schindler_2020vis", "Schindler-2022-eurovis", "schindler2020", "schleicher-2011-VLSC", "Schmidlehner_Sandra_SbC", "schmidlehner2021", "schmidt-2011-mt", "schmidt-phd", "schmidt-phd", "schoellhuber-2008-asc", "scholz_2021", "Schrempf_2018", "Schrempf_2020", "SCHUETZ-2023-SIMLOD", "schuh-2018-mesh-blending", "Schulze_Florian_2013_CMI", "schwankl-2013-smis", "seyfert-2017", "shakhova-2023-atp", "sietzen-2019-wnn", "sietzen-2019-wnn", "sietzen-2021-perturber", "sietzen-2022-vacnnr", "sietzen-ifv-2019", "sifuentes-2018-crowd", "SifuentesGangl2017FIS", "sikachev_peter_2010_STLCI", "sikachev_peter-2011-dfc", "sikachev_peter-2011-incshad", "sikachev_peter-2011-metavis", "sikachev_peter-2011-protovis", "sikachev-2010-DFC", "sikachev-2010-ill_vis_vol_ren", "Sippl_Sebastian_EFG", "smiech-2018-tei", "Smisek_Michal_A3D", "Sollboeck_2011_FSS", "sollboeck-2011", "Solteszova-2009-VQN", "solteszova-2010-MOS", "Solteszova2016", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "sorger-2019-odn", "sorger-2021-egonet", "Soros_AVN_2011", "Soros-AV-2010", "Spechtenhauser_Florian_2016", "spegel-gruenberger-2020", "Spelitz2020", "spoerk-2010-hpgpu", "Stabel_2012_UDM", "stappen_2017_animatedcomic", "Staudacher_2022", "staudacher_florian-2016-topo3d", "stehno-2011-RVD", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "STEINLECHNER-2019-ICT", "StickmanMax-shoetta-kampfer", "stoff-concepMap-2021", "StrakaVis2004", "stritzel2022", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "suntinger-2008-etet", "suntinger-2008-tet", "Swoboda_Nicolas_VIT", "Swoboda2020", "szabo_patrik-2022-tour", "takahashi-2019-acdt", "termeer-2006-000", "termeer-2007-covicad", "termeer-2008-scmr", "termeer-2008-vis", "termeer-2009-cvc", "termeer-2009-scmr", "textures-3d-printing", "thesis-tekaya", "Thomas-2018", "Thurner-2005-IVR", "toth-2007-ndd", "TR-186-2-05-01", "TR-186-2-05-02", "TR-186-2-05-03", "TR-186-2-05-04", "TR-186-2-05-06", "TR-186-2-05-07", "TR-186-2-05-08", "TR-186-2-06-01", "TR-186-2-06-02", "TR-186-2-06-03", "TR-186-2-06-04", "TR-186-2-07-02", "TR-186-2-07-03", "TR-186-2-07-04", "TR-186-2-07-05", "TR-186-2-07-06", "TR-186-2-07-07", "TR-186-2-07-08", "TR-186-2-07-10", "TR-186-2-07-11", "TR-186-2-07-12", "TR-186-2-08-01", "TR-186-2-08-02", "TR-186-2-08-03", "TR-186-2-08-04", "TR-186-2-08-05", "TR-186-2-08-06", "TR-186-2-08-07", "TR-186-2-08-08", "TR-186-2-08-10", "TR-186-2-08-11", "TR-186-2-08-12", "TR-186-2-08-14", "TR-186-2-09-01", "TR-186-2-15-03", "TR1862162", "Tramberger_2018", "Tramberger2017BCS", "Trautner_Thomas_2014_VAE", "trautner-2018-imd", "trautner-2018-imd", "travnicek-2017-thm", "Trenkwalder-2004-MAR", "Troidl_2019", "Troidl_2021", "Troidl_2022", "turner-aso", "tut-eg-2006", "tut-siggraph-2006", "tut-vis-2006", "tut-vis-2007", "tweebo-2014", "ulschmid-2024-reo", "unger_2017", "unger-2019_vcp", "Unger2020", "vad_2015_phd", "Vad_Viktor_2015_RVV", "vad-2016-bre", "vaico", "varchola_andrej-2012-fetoscopic", "Vasileva_2022", "Vasileva-2018", "vessel2003", "Viola_2013_IDV", "Viola_Ivan_2013_CAI", "Viola_Ivan_2013_D3D", "Viola_Ivan_2013_DC", "Viola_Ivan_2013_GS", "Viola_Ivan_2013_HQ3", "Viola_Ivan_2013_RMA", "Viola_Ivan_2013_RSb", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_DAC", "Viola_Ivan_IIP", "Viola_Ivan_UVP", "Viola_Ivan_VDP", "Viola-05-Smart", "Viola-2003-GPU", "Viola-2003-Har", "viola-2003-hbn", "Viola-2003-NON", "viola-2004-gbf", "Viola-2004-GPU", "viola-2004-har", "viola-2004-har2", "viola-2004-idv", "viola-2004-imp", "Viola-2004-ImpX", "Viola-2004-ImpX2", "viola-2005-imp", "viola-2006-FoA", "viola-evr", "Viola-Pondering-2017", "viola-popular-article-2006", "Viola-vistutillustrativevis", "vis-foa", "VisWeek-Tutorial-2012-Uncertainty", "vitruvian_2019", "voglreiter-2023-tro", "Vucenovic_2022", "vucini_2006", "vucini_2008_rnp", "vucini_2009", "vucini_erald-2007-FRI", "vucini-2009-phd", "vucini-2011", "Wagner_032017", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "Waldin_Nicholas_2017_FlickerObserver", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2017-thesis", "waldin-2019-ccm", "waldin-2019-ccm", "Waldner_2017_11", "Waldner_2017_11", "waldner-2013-facetCloudsGI", "waldner-2013-ubiWM", "waldner-2014-af", "waldner-2014-ghi", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "waser_2011_VSD", "Waser-2010-WL", "webGPU_aggregateVis-2023", "weiner_2011", "Weissenboeck_2019", "Weissenboeck_2019_PhD", "weissenboeck-2014", "Wihann_2017", "wolf-2023-cc", "Woschizka_2021", "wu-2017-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-shonan", "wu-2018-story", "wu-2019-bmc", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-smwp", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg", "wu-2021", "wu-2021-vi", "xmastree2002", "xmastree2005", "ymca", "YOGHOURDJIAN2019", "Zambal-2003-SWA", "zambal-2005-3dact", "Zaufel_2021", "zauner-2013-svkinect", "zechmeister2020", "Zeng_2021", "Zhu-2014-flowvis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Workgroup&id=vis", "__class": "Workgroup" }, { "id": "deskollage", "workgroup_id": "vis", "drupal_id": 4198, "name": "Visual Information Foraging on the Desktop", "name_de": null, "website": null, "status": "active", "short_abstract": "The goal of this project is to design and develop novel interactive visualization techniques to support knowledge workers in making sense of their unstructured, dynamic information collections. ", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. On the one hand, the studies show that, in some situations, interactive visualization can be less efficient than working with unprocessed text-based information. On the other hand, the studies also show that combining automatic data analysis with interactive visualization can lead to more unexpected findings, especially when exploring large data. The extent of manual information organization varies with the task: the less users know about the gathered information, the more automatic organization they expect. \n\nIn summary, this project contributed novel user interface concepts and design guidelines for user interfaces supporting information foraging and sensemaking. The techniques and study results were published at high-ranking peer-reviewed venues, and it can be expected that the findings of this project shape the way how users seek and organize their information in the future. \n\n", "start_date": "2015-12-01", "end_date": "2018-12-31", "leader_id": 1110, "logo": { "name": "logo.png", "path": "project:deskollage", "type": "image/png", "size": 331697, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/deskollage/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "T 752-N30", "comment": null } ], "research_areas": [ "InfoVis" ], "publications": [ "2019-ic", "byska-2019-mdfc", "casellato-2016-pkg", "cizmic-2018-evd", "donabauer-2015-asc", "dworschak-2016-szcm", "edlinger-2018-vwr", "georgiev-2019-cbg", "geymayer-2017-std", "gundacker-2020-wlm", "gusenbauer-2018", "hromniak-2019-vcn", "Koszticsak-2017-ewt", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "polatsek-2018-stv", "samoul-2019-cnp", "sietzen-2019-wnn", "sietzen-ifv-2019", "smiech-2018-tei", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "trautner-2018-imd", "unger-2019_vcp", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg" ], "url": "https://www.cg.tuwien.ac.at/research/projects/deskollage", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/trautner-2018-imd/", "__class": "Publication" }, { "id": "edlinger-2018-vwr", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Visually Linking web search results with bookmarked information", "date": "2018-10", "abstract": "This work presents a new approach of regaining access to stored information and for the visualization of similarities between new information and locally stored data. The fact that bookmarks are cumbersome to use and that there is no possibility to compare web search results with local information motivates the concept of this thesis. The\nimplementation was done as Google Chrome extension and based on the ’Information\nCollage’ environment. In order to improve the perceived ease of use, the visualization was integrated in the search engine results page to avoid a context switch for the user. The\nvisualization uses a word cloud to display similarities and differences between remote and\nlocal information. The word cloud layout focuses on the spatial arrangment and the text\ncolour of the words to encode their association to the remote or the local information.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 761, "image_height": 758, "name": "edlinger-2018-vwr-teaser.png", "type": "image/png", "size": 267653, "path": "Publication:edlinger-2018-vwr", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/edlinger-2018-vwr/edlinger-2018-vwr-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/edlinger-2018-vwr/edlinger-2018-vwr-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "authors": [ { "id": 1465, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Georg", "lastname": "Edlinger", "searchname": "Georg Edlinger", "is_teacher": false, "name": "Georg Edlinger", "publications": [ "edlinger-2018-vwr" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1465", "__class": "Author" } ], "date_end": "2018-10", "date_start": "2017-06", "matrikelnr": "1027088", "supervisor": [ { "id": 1110, "drupal_id": 625, "orcid_id": "0000-0003-1387-5132", "website": "https://www.cg.tuwien.ac.at/staff/ManuelaWaldner", "firstname": "Manuela", "lastname": "Waldner", "searchname": "Manuela Waldner", "is_teacher": true, "name": "Manuela Waldner", "publications": [ "2019-ic", "Alharbi_2021", "bernhard-2016-gft", "byska-2019-mdfc", "eschner-2023-evl", "eschner-2023-ims", "geymayer-2017-std", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", "indirectBiasLanguageModels-2023", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "mazurek-2018-veq", "polatsek-2018-stv", "reina-2020-mtv", "sietzen-2021-perturber", "sietzen-ifv-2019", 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", "abstract": "Data and information created by various processes (e.g., simulations) is getting larger, and more and more complex. We use interactive visualization and analysis techniques to facilitate exploration of complex parameter spaces (e.g., to analyze and compare parameters for automotive engineering, reconstruction algorithms, or geometry generators) or unstructured information collections (e.g., annotated digital documents or image collections). Our research focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning.
\r\n", "website": "https://www.cg.tuwien.ac.at/research/area/InfoVis", "teaser": { "name": "teaser.png", "path": "research_area:InfoVis", "type": "image/png", "size": 60875, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/InfoVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "8564188", "arbesser_ba_2023", "Arleo-2019-vis", "Batik-2021", "batik-2021-gd", "bayat-2022-mva", "beham-2014-cupid", "bhore-2021-issac", "birsak-2014-agtb", "birsak-2017-dpe", "borgo-2013-gly", "borondy2022", "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", 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"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": [], "files": [ { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 761, "image_height": 758, "name": "edlinger-2018-vwr-teaser.png", "type": "image/png", "size": 267653, "path": "Publication:edlinger-2018-vwr", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/edlinger-2018-vwr/edlinger-2018-vwr-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/edlinger-2018-vwr/edlinger-2018-vwr-teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": false, "use_in_gallery": false, "access": "public", "name": "edlinger-2018-vwr-thesis.pdf", "type": "application/pdf", "size": 9699891, "path": "Publication:edlinger-2018-vwr", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/edlinger-2018-vwr/edlinger-2018-vwr-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/edlinger-2018-vwr/edlinger-2018-vwr-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "deskollage", "workgroup_id": "vis", "drupal_id": 4198, "name": "Visual Information Foraging on the Desktop", "name_de": null, "website": null, "status": "active", "short_abstract": "The goal of this project is to design and develop novel interactive visualization techniques to support knowledge workers in making sense of their unstructured, dynamic information collections. ", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. On the one hand, the studies show that, in some situations, interactive visualization can be less efficient than working with unprocessed text-based information. On the other hand, the studies also show that combining automatic data analysis with interactive visualization can lead to more unexpected findings, especially when exploring large data. The extent of manual information organization varies with the task: the less users know about the gathered information, the more automatic organization they expect. \n\nIn summary, this project contributed novel user interface concepts and design guidelines for user interfaces supporting information foraging and sensemaking. The techniques and study results were published at high-ranking peer-reviewed venues, and it can be expected that the findings of this project shape the way how users seek and organize their information in the future. \n\n", "start_date": "2015-12-01", "end_date": "2018-12-31", "leader_id": 1110, "logo": { "name": "logo.png", "path": "project:deskollage", "type": "image/png", "size": 331697, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/deskollage/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "T 752-N30", "comment": null } ], "research_areas": [ "InfoVis" ], "publications": [ "2019-ic", "byska-2019-mdfc", "casellato-2016-pkg", "cizmic-2018-evd", "donabauer-2015-asc", "dworschak-2016-szcm", "edlinger-2018-vwr", "georgiev-2019-cbg", "geymayer-2017-std", "gundacker-2020-wlm", "gusenbauer-2018", "hromniak-2019-vcn", "Koszticsak-2017-ewt", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "polatsek-2018-stv", "samoul-2019-cnp", "sietzen-2019-wnn", "sietzen-ifv-2019", "smiech-2018-tei", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "trautner-2018-imd", "unger-2019_vcp", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg" ], "url": "https://www.cg.tuwien.ac.at/research/projects/deskollage", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/edlinger-2018-vwr/", "__class": "Publication" }, { "id": "steinboeck-2018-lbg", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "Casual Visual Exploration of Large Bipartite Graphs Using Hierarchical Aggregation and Filtering", "date": "2018-10", "abstract": "Bipartite graphs are typically visualized using linked\nlists or matrices. However, these classic visualization techniques\ndo not scale well with the number of nodes. Biclustering has\nbeen used to aggregate edges, but not to create linked lists\nwith thousands of nodes. In this paper, we present a new\ncasual exploration interface for large, weighted bipartite graphs,\nwhich allows for multi-scale exploration through hierarchical\naggregation of nodes and edges using biclustering in linked\nlists. We demonstrate the usefulness of the technique using two\ndata sets: a database of media advertising expenses of public\nauthorities and author-keyword co-occurrences from the IEEE\nVisualization Publication collection. Through an insight-based\nstudy with lay users, we show that the biclustering interface leads\nto longer exploration times, more insights, and more unexpected\nfindings than a baseline interface using only filtering. However,\nusers also perceive the biclustering interface as more complex.", "authors_et_al": false, "substitute": null, "main_image": { "description": "BiCFlows showing visualization authors and their key words", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 708, "image_height": 702, "name": "steinboeck-2018-lbg-teaser.png", "type": "image/png", "size": 137906, "path": "Publication:steinboeck-2018-lbg", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/steinboeck-2018-lbg/steinboeck-2018-lbg-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/steinboeck-2018-lbg/steinboeck-2018-lbg-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "authors": [ { "id": 1378, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Daniel", "lastname": "Steinböck", "searchname": "Daniel Steinböck", "is_teacher": false, "name": "Daniel Steinböck", "publications": [ "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "waldner-2020-tbg" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1378", "__class": "Author" }, { "id": 166, "drupal_id": 111, "orcid_id": "0000-0002-8569-4149", "website": "https://www.cg.tuwien.ac.at/staff/EduardGröller", "firstname": "Eduard", "lastname": "Gröller", "searchname": "Eduard Gröller", "is_teacher": true, "name": "Eduard Gröller", "publications": [ "a-2001-ah", "a-2001-ahr", "a-2001-Rec", "Acquisto-1995-DCR", "alacruzECR2004", "Alharbi_2021", "Alsallakh_2012_RCW", "amirkhanov_2012", "amirkhanov_2012heur", "amirkhanov_2013_AMA", "amirkhanov-2011", "amirkhanov-2014-ama", "amirkhanov-2017-cffet", "amirkhanov-2018-withteeth", "amirkhanov-2019-manylands", "amirkhanov2010AMA", "amirkhanov2020visual", "Antonini2020", "Artner-2004-Hig", "Artner-2005-Hig", "Auzinger_Mistelbauer_2013_CSR", "balabanian-2007-ant", "balabanian-2008-hvv", "balabanian-2008-tst", "Balabanian-2010-IIV", "Balabanian-2010-PSDSV", "Bartroli-2002-Pro", "Bartroli-2003-Geo", "Bartroli-2003-Non", "beham-2014-cupid", "Berger_2011_UAE", "Berger-1998-Col", "Berger-2000-Col", "Bruckner_Stefan_2015_VAS", "Bruckner-2003-The", "bruckner-2005-ICV", "bruckner-2005-vid", "bruckner-2005-VIS", "bruckner-2006-EVV", "bruckner-2006-ICE", "bruckner-2007-EDF", "bruckner-2007-STF", "bruckner-2008-IVV", "bruckner-2009-BVQ", "bruckner-2009-IVV", "bruckner-2010-HVC", "bruckner-2010-IFC", "burns-2007-fea", "Carata_2011_IVE", "Castro-1998-TFS", "Cornel_Daniel_2015_VOC", "cornel-2022-wih", "coto-2005-MAC", "Csebfalvi-1999-Fast", "Csebfalvi-1999-MIP", "Csebfalvi-2000-Fas", "Csebfalvi-2000-GELR", "Csebfalvi-2000-Gra", "Csebfalvi-2000-IVRBM", "Csebfalvi-2001-Fas", "Csebfalvi-2001-Int", "Csebfalvi-2001-NPVR", "Csebfalvi-2002-FPVF", "Csebfalvi-2002-SBICG", "Csebfalvi-2002-Smo", "Csebfalvi-2012-IOM", "dataset-stagbeetle", "Dhanoa_2021", "dhanoa-2022-apm", "Diehl_2015", "Diehl_2021", "diehl-2013-VTA", "Diehl-2017-Albero", "Edi_2019_10_01", "eg-tut2005-iv", "EuroVis2018-ShortPapers-Karall", "EuroVis2018-ShortPapers-Reiter", "fernandez-2022-ergoexplorer", "fischel-1995-vis", "Fischel-1995-VLS", "Fischel-1997-CSVVP", "Fischel-1998-Cas", "fmistelbauer-2014-adict", "fritz-2009-ava", "Froehler_Berhnard_2015_ESM", "fuchs_vhml", "fuchs-2008-del", "Fuhr-1999-Multi", "Fuhrmann-1998-Rea", "fuhrmann-1998-reaX", "Furmanova_2018", "furmanova_2020", "Gall2021", "Ganuza", "Ganuza_2015", "Ganuza_MJ_2015_AVe", "Ganuza_ML_2015_ISA", "Ganuza-2017-IVCSGM", "Gavrilescu-2010-CIE", "Gillmann2021", "Glaeser-1997-EVG", "Glaeser-1998-AFa", "Glaeser-1998-Eff", "Glaeser-1999-Fas", "glanznig-2009-LAMC", "Grimm-2003-CPU", "Grimm-2003-HYP", "grimm-2004-arefined", "GRIMM-2004-FDM", "GRIMM-2004-FDMX", "GRIMM-2004-FDMX-P", "grimm-2004-memory", "GRIMM-2004-PPC", "grimm-2004-volume", "Groeller_2011_CVC", "Groeller_2011_CW", "Groeller_2011_GBC", "Groeller_2011_HP", "Groeller_2011_HSU", "Groeller_2011_IPV", "Groeller_2011_IVP", "Groeller_2011_NR", "Groeller_2011_NSM", "Groeller_2011_VCD", "Groeller_2011_VSD", "Groeller_2011_VSS", "Groeller_2012_KAV", "Groeller_2012_VBP", "Groeller_2012_ViV", "Groeller_2012_VV", "Groeller_2014_CaQ", "Groeller_2014_CQV", "Groeller_2014_CV", "Groeller_2014_RWA", "Groeller_2014_STC", "Groeller_2014_UPS", "Groeller_2014_VND", "Groeller_2016_I1", "Groeller_2016_I2", "Groeller_2016_I3", "Groeller_2016_I4", "Groeller_2016_I5", "Groeller_2016_I6", "Groeller_2016_I7", "Groeller_2016_I8", "Groeller_2016_P1", "Groeller_2016_P2", "Groeller_2016_P3", "Groeller_2016_P4", "Groeller_2016_P6", "Groeller_2016_P7", "Groeller_2021_11", "Groeller_2021_BVM", "Groeller_2021-10", "Groeller_Edi_2013_TVC", "Groeller_Edi_2013_VCQ", "Groeller_Edi_2013TVCK", "Groeller_Edi_VKA", "Groeller_Eduard_2014_THS", "Groeller_Eduard_2014_TSP", "Groeller_Eduard_2014_UCT", "Groeller_Eduard_2015_SMV", "Groeller_Eduard_2015_TCU", "Groeller_V1_2020", "Groeller_V2_2020", "Groeller_V3_2020", "Groeller_V42020", "Groeller_V5_2020", "groeller-1987-opt", "groeller-1988-duale", "groeller-1988-using", "groeller-1991-frac", "groeller-1991-temp", "groeller-1992-frac", "groeller-1992-fractals", "groeller-1992-fraktale", "groeller-1992-vis", "groeller-1993-acc", "groeller-1993-cha", "groeller-1993-coh", "groeller-1993-coh1", "groeller-1993-daten", "groeller-1993-dist", "groeller-1993-disto", "groeller-1993-eff", "groeller-1993-exp", "groeller-1993-frak", "groeller-1993-grund", "groeller-1993-oct", "Groeller-1994-AIV", "groeller-1994-appl", "Groeller-1994-AVT", "groeller-1994-coh", "Groeller-1994-CSA", "groeller-1994-ext", "Groeller-1994-HIS", "groeller-1994-hyper", "Groeller-1994-IDN", "groeller-1994-int", "Groeller-1994-ITV", "groeller-1994-mod", "Groeller-1994-MRN", "groeller-1994-tech", "groeller-1994-vis", "groeller-1995-appl", "groeller-1995-attract", "Groeller-1995-CCG", "groeller-1995-dyn", "Groeller-1995-GOW", "Groeller-1995-IED", "groeller-1995-inter", "groeller-1995-lok", "groeller-1995-mod", "groeller-1995-non", "Groeller-1995-SDC", "groeller-1995-vis", "groeller-1996-ACE", "groeller-1996-avn", "Groeller-1998-TunVis", "Groeller-1998-VAD", "Groeller-1998-VDS", "Groeller-1999-Dat", "Groeller-1999-Vis", "Groeller-2000-Vis", "Groeller-2001-IDV", "groeller-2002-anw", "Groeller-2002-Ins", "groeller-2002-med", "groeller-2002-wiss", "groeller-2003-fea", "groeller-2003-med", "groeller-2003-scie", "groeller-2003-vol", "groeller-2004-efficient", "groeller-2004-imp", "groeller-2004-sci", "groeller-2005-abs", "groeller-2005-dia", "groeller-2005-foc", "groeller-2005-imp", "groeller-2005-impo", "groeller-2005-proc", "groeller-2005-sma", "groeller-2005-smar", "groeller-2005-volg", "groeller-2006-cgf", "groeller-2006-civ", "groeller-2006-ivt", "groeller-2006-tvcg", "groeller-2007-csu", "groeller-2007-fci", "groeller-2007-mva", "groeller-2007-vis", "groeller-2007-visII", "groeller-2007-vws", "groeller-2008-att2", "groeller-2008-How", "groeller-2008-hsp", "groeller-2008-irs", "groeller-2008-kav2", "groeller-2008-kav3", "groeller-2008-kav4", "groeller-2008-lsy", "Groeller-2010-CVC", "groeller-2010-How", "Groeller-2010-IFI", "Groeller-2010-IVVI", "groeller-2010-PTT", "Groeller-2011-HSH", "Groeller-2017-AMOS", "Groeller-2017-ARTORW", "Groeller-2017-AVC", "Groeller-2017-IVAMCS", "Groeller-2017-PTPMD", "groeller-2022-iva", "groeller-2022-iva-1", "groeller-2022-ivd", "groeller-2023-ivd", "groeller-2023-siv", "groeller-2023-siv-1", "groeller-2023-siv-2", "groeller-2023-tfo", "groeller-cvc-2009", "groeller-scv-2009", "groeller-svo-2009", "Groeller-thesis", "groeller-vks-2009", "Groller_2021-12-03", "Grorller-2010-IVV", "grossmann_2019_pelvisrunner_poster", "grossmann-2022-conceptSplatters", "Hadwiger-2003-MIP", "haidacher_2010_statTF", "haidacher-2008-vcbm", "haidacher-2011-MSM", "haidacher-2011-VAM", "Halladjian_2020", "Hauser-1999-SSI", "Hauser-2000-Tho", "Hauser-2000-Two", "Hauser-2000-TwoX", "Hauser-2002-SSI", "Hauser-2003-Acc", "Heim_2021", "heinzl_2006_RSDVCDM", "heinzl-2006-rep", "heinzl-2007-sem", "heinzl-2008-sam", "Herghelegiu-2012-BPV", "herzberger-2024-roh", "Hladuvka-2000-Cur", "Hladuvka-2000-Exp", "Hladuvka-2000-ExpX", "Hladuvka-2001-DDI", "Hladuvka-2001-Dir", "Hladuvka-2001-Exp", "Hladuvka-2001-Sal", "Hladuvka-2002-Exp", "hladuvka-2002-exploiting", "Hladuvka-2002-Sma", "Jankovic-1994-PBM", "jankovic-1994-phy", "jankovic-1995-heter", "Kanitsar-2001-Aut", "Kanitsar-2001-Per", "Kanitsar-2001-Pos", "Kanitsar-2001-PVI", "kanitsar-2002-Chr", "Kanitsar-2002-CPR", "kanitsar-2002-CPRX", "Kanitsar-2003-ADV", "Kanitsar-2003-Adva", "Kanitsar-2003-CTa", "Kanitsar-2003-Dem", "Kanitsar-2004-Dia", "karimov-2013-vivisection", "karimov-2016-SD", "kehrer-2013-SBC", "klein_2017_IM", "klein_2019_PGG", "klein_2019_PMP", "klein-2016-WCL", "Knapp-2003-SAT", "knapp-2004-semi", "Knoll-2000-AJi", "Koechl-2003-Com", "Koenig-1998-NC", "Koenig-1998-Rea", "koenig-1999-AlV", "Koenig-1999-Mul", "Koenig-1999-MVA", "Koenig-2000-AlV", "Koenig-2000-AlVi", "Koenig-2000-ATFS", "Koenig-2001-Mas", "koeppel-2021", "Kohlmann-2007-EBV", "kohlmann-2007-livesync", "kohlmann-2008-lse", "kohlmann-2009-cp", "Korpitsch-2020-wscg", "kouril-2018-LoL", "kouril-2020-hyperlabels", "kouril-2021-molecumentary", "Labschuetz_Matthias_2015_JIT", "Labschuetz_Matthias_2016_JIT", "Labschuetz_Matthias_2016_JITT", "LaCruz-2004-NMF", "LaCruz2004", "lee-2022-p", "Loeffelmann-1994-PSQ", "loeffelmann-1995-para", "Loeffelmann-1995-RTE", "loeffelmann-1996-CVA", "Loeffelmann-1996-DS3", "loeffelmann-1996-SVM", "Loeffelmann-1997-FV2", "Loeffelmann-1997-HSV", "Loeffelmann-1997-VPM", "Loeffelmann-1998-Enh", "Loeffelmann-1998-EVC", "Loeffelmann-1998-SMURF", "Loeffelmann-1998-VDS", "Loeffelmann-1998-Vis", "Loeffelmann-1998-Visu", "Loeffelmann-1999-SMU", "malik-2007-FP", "malik-2009-CVFA", "malik-2010-cvp", 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"TR-186-2-08-08", "TR-186-2-08-10", "TR-186-2-08-11", "TR-186-2-08-12", "TR-186-2-08-13", "TR-186-2-08-14", "TR-186-2-09-01", "TR-186-2-15-03", "TR1862162", "Troidl_2022", "Tsoi-2000-Ada", "Vad_Viktor_2015_RVV", "vad_viktor-2017-WVE", "vaico", "Vilanova-1999-Vir", "Vilanova-1999-VirX", "Vilanova-2000-CAT", "Vilanova-2000-Cyl", "Vilanova-2000-VCF", "Vilanova-2001-Non", "Vilanova-2001-Per", "Vilanova-2001-VCU", "Vilanova-2001-Vir", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola-05-Smart", "Viola-2003-GPU", "Viola-2003-Har", "Viola-2003-NON", "Viola-2004-GPU", "viola-2004-har", "viola-2004-har2", "viola-2004-imp", "Viola-2004-ImpX", "Viola-2004-ImpX2", "viola-2005-imp", "viola-2006-FoA", "viola-2007-ort", "Viola-vistutillustrativevis", "vis-foa", "VisWeek-Tutorial-2012-Uncertainty", "vucini_2008_rnp", "vucini_2009", "vucini_erald-2007-FRI", "vucini-2011", "Wagner-2002-End", "Waldin_Nicholas_2016_Chameleon", "waldin-2019-ccm", "waldner-2017-vph", "waldner-2020-tbg", 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"organization": "IEEE", "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.
\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" }, { "id": "NetVis", "drupal_id": 9472, "name": "Network Visualization", "short_abstract": "This research area aims to investigate how to best visualize graph-typed data, both abstractly as well as in domain-specific applications.", "abstract": "Graph-typed data is ubiquitous, from logistical or transportation networks, through social or correspondence networks, all the way to more abstract biochemical interaction networks. Each such application domain brings with it unique analytical goals, metadata, canonical representations, as well as types of vertices and edges. Routine, automated analyses of such data, while important, can often not fully support the kind of decision-making or data exploration necessary for more complex and/or larger networks. Here, it is through (interactive) visualization that we can support domain experts in their exploratory and (semi-) confirmatory research endeavors. On the one hand, we can build custom, tailor-made interactive, visual dashboards which directly address the needs and support the analysis of our domain expert collaborators. On the other, we can look at more foundational questions about how to best represent graph-typed data or better understand the factors which negatively/positively affect comprehension.
\r\n", "website": "https://www.cg.tuwien.ac.at/research/area/NetVis", "teaser": { "name": "teaser.png", "path": "research_area:NetVis", "type": "image/png", "size": 1948873, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/NetVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "ehlers-2023-iro", "mazurek-2018-veq", "sorger-2019-odn", "sorger-2021-egonet", "steinboeck-2018-lbg", "waldner-2014-ghi", "waldner-2020-tbg" ], "projects": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=NetVis", "__class": "ResearchArea" } ], "keywords": [ "information visualization", "bipartite graphs", "biclustering", "insight-based evaluation" ], "weblinks": [ { "href": "https://users.cg.tuwien.ac.at/~waldner/bicflows/", "caption": "BiCFlows online", "description": "BiCFlows online for exploring Austria's media transparency database and the IEEE Visualization paper authors and their key words. ", "main_file": 0 } ], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "steinboeck-2018-lbg-paper.pdf", "type": "application/pdf", "size": 1871535, "path": "Publication:steinboeck-2018-lbg", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/steinboeck-2018-lbg/steinboeck-2018-lbg-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/steinboeck-2018-lbg/steinboeck-2018-lbg-paper:thumb{{size}}.png" }, { "description": "BiCFlows showing visualization authors and their key words", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 708, "image_height": 702, "name": "steinboeck-2018-lbg-teaser.png", "type": "image/png", "size": 137906, "path": "Publication:steinboeck-2018-lbg", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/steinboeck-2018-lbg/steinboeck-2018-lbg-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/steinboeck-2018-lbg/steinboeck-2018-lbg-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "deskollage", "workgroup_id": "vis", "drupal_id": 4198, "name": "Visual Information Foraging on the Desktop", "name_de": null, "website": null, "status": "active", "short_abstract": "The goal of this project is to design and develop novel interactive visualization techniques to support knowledge workers in making sense of their unstructured, dynamic information collections. ", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. On the one hand, the studies show that, in some situations, interactive visualization can be less efficient than working with unprocessed text-based information. On the other hand, the studies also show that combining automatic data analysis with interactive visualization can lead to more unexpected findings, especially when exploring large data. The extent of manual information organization varies with the task: the less users know about the gathered information, the more automatic organization they expect. \n\nIn summary, this project contributed novel user interface concepts and design guidelines for user interfaces supporting information foraging and sensemaking. The techniques and study results were published at high-ranking peer-reviewed venues, and it can be expected that the findings of this project shape the way how users seek and organize their information in the future. \n\n", "start_date": "2015-12-01", "end_date": "2018-12-31", "leader_id": 1110, "logo": { "name": "logo.png", "path": "project:deskollage", "type": "image/png", "size": 331697, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/deskollage/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "T 752-N30", "comment": null } ], "research_areas": [ "InfoVis" ], "publications": [ "2019-ic", "byska-2019-mdfc", "casellato-2016-pkg", "cizmic-2018-evd", "donabauer-2015-asc", "dworschak-2016-szcm", "edlinger-2018-vwr", "georgiev-2019-cbg", "geymayer-2017-std", "gundacker-2020-wlm", "gusenbauer-2018", "hromniak-2019-vcn", "Koszticsak-2017-ewt", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "polatsek-2018-stv", "samoul-2019-cnp", "sietzen-2019-wnn", "sietzen-ifv-2019", "smiech-2018-tei", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "trautner-2018-imd", "unger-2019_vcp", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg" ], "url": "https://www.cg.tuwien.ac.at/research/projects/deskollage", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/steinboeck-2018-lbg/", "__class": "Publication" }, { "id": "mazurek-2018-veq", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "Visualizing Expanded Query Results", "date": "2018-06", "abstract": "When performing queries in web search engines, users often face difficulties choosing appropriate query terms. Search engines\ntherefore usually suggest a list of expanded versions of the user query to disambiguate it or to resolve potential term mismatches.\nHowever, it has been shown that users find it difficult to choose an expanded query from such a list. In this paper, we describe\nthe adoption of set-based text visualization techniques to visualize how query expansions enrich the result space of a given\nuser query and how the result sets relate to each other. Our system uses a linguistic approach to expand queries and topic\nmodeling to extract the most informative terms from the results of these queries. In a user study, we compare a common text list\nof query expansion suggestions to three set-based text visualization techniques adopted for visualizing expanded query results\n– namely, Compact Euler Diagrams, Parallel Tag Clouds, and a List View – to resolve ambiguous queries using interactive\nquery expansion. Our results show that text visualization techniques do not increase retrieval efficiency, precision, or recall.\nOverall, users rate Parallel Tag Clouds visualizing key terms of the expanded query space lowest. Based on the results, we derive\nrecommendations for visualizations of query expansion results, text visualization techniques in general, and discuss alternative\nuse cases of set-based text visualization techniques in the context of web search.", "authors_et_al": false, "substitute": null, "main_image": { "description": "Density-based compact Euler Diagram", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 919, "image_height": 656, "name": "mazurek-2018-veq-teaser.png", "type": "image/png", "size": 34882, "path": "Publication:mazurek-2018-veq", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/mazurek-2018-veq/mazurek-2018-veq-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/mazurek-2018-veq/mazurek-2018-veq-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "authors": [ { "id": 1364, "drupal_id": 1285, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/MichaelMazurek", "firstname": "Michael", "lastname": "Mazurek", "searchname": "Michael Mazurek", "is_teacher": false, "name": "Michael Mazurek", "publications": [ "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "mazurek-2018-veq", "field_id": "lecturer", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1364", "__class": "Author" }, { "id": 1110, "drupal_id": 625, "orcid_id": "0000-0003-1387-5132", "website": "https://www.cg.tuwien.ac.at/staff/ManuelaWaldner", "firstname": "Manuela", "lastname": "Waldner", "searchname": "Manuela Waldner", "is_teacher": true, "name": "Manuela Waldner", "publications": [ "2019-ic", "Alharbi_2021", "bernhard-2016-gft", "byska-2019-mdfc", "eschner-2023-evl", "eschner-2023-ims", "geymayer-2017-std", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", "indirectBiasLanguageModels-2023", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "mazurek-2018-veq", "polatsek-2018-stv", "reina-2020-mtv", "sietzen-2021-perturber", "sietzen-ifv-2019", "sMolBoxes_2022", "sorger-2019-odn", "sorger-2021-egonet", "steinboeck-2018-lbg", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2013-facetCloudsGI", "waldner-2013-ubiWM", "waldner-2014-af", "waldner-2014-ghi", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "webGPU_aggregateVis-2023", "wu-2021", "wu-2021-vi" ], "publications_first": [], "project_leader": [ "d9282", "d9522", "d9555", "deskollage" ], "publication_field": [ { "publ_id": "arbesser_ba_2023", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "bayat-2022-mva", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "boesch_2014_browserHistoryVis", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "breitenecker-2020-bct", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "bugnar-esk-2021", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "casellato-2016-pkg", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "cizmic-2018-evd", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "da_cunha_melo-2023-c3m", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "donabauer-2015-asc", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "dworschak-2016-szcm", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "edlinger-2018-vwr", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "eiweck-hnv-2021", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "eschner-2023-rar", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "eschner-blur-2022", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "georgiev-2019-cbg", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Gogel2020", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "grammatikaki-thesis", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "grossmann-2021-layout", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "gundacker-2020-wlm", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "gusenbauer-2018", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "heim-gall-2020-dde", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "hromniak-2019-vcn", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "indirectBiasLanguageModels-2023", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "kimmersdorfer-fancyMaps-2023", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "korpitsch-2021-lov", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Koszticsak-2017-ewt", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "lippeck-2022-mna", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "louis-alexandre_dit_petit-frere-2022-veo", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "mahler-2021-mdar", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "matt-2023-vae", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "mayr-2021-wec", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "mazurek-2017-sio", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "mazurek-2017-vows", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "mazurek-2018-vac", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Panayotov", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Presch_2020", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "samoul-2019-cnp", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "sbardellati-2021-eveos", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "sietzen-2019-wnn", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "sietzen-2022-vacnnr", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "smiech-2018-tei", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "spegel-gruenberger-2020", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "staats-2024-atr", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "steinboeck-2017-vbn", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "steinboeck-2017-vefp", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "steinboeck-2018-lbg", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "stoff-concepMap-2021", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "textures-3d-printing", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "trautner-2018-imd", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "unger-2019_vcp", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Unger2020", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "waldner-2013-ubiWM", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldner-2014-af", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldner-2014-ghi", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldner-2017-vph", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldner-2019-rld", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "webGPU_aggregateVis-2023", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "wolf-2023-cc", "field_id": "supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1110", "__class": "Author" } ], "cfp": { "name": "EuroVis 2018 CfP.pdf", "type": "application/pdf", "error": "0", "size": "55844", "orig_name": "EuroVis 2018 CfP.pdf", "ext": "pdf" }, "date_from": "2018-06-04", "date_to": "2018-06-08", "event": "EG / VGTC Conference on Visualization (EuroVis)", "journal": "Computer Graphics Forum", "lecturer": [ { "id": 1364, "drupal_id": 1285, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/MichaelMazurek", "firstname": "Michael", "lastname": "Mazurek", "searchname": "Michael Mazurek", "is_teacher": false, "name": "Michael Mazurek", "publications": [ "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "mazurek-2018-veq", "field_id": "lecturer", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1364", "__class": "Author" } ], "location": "Brno, Czech Republic", "pages_from": "87", "pages_to": "98", "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.
\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" }, { "id": "NetVis", "drupal_id": 9472, "name": "Network Visualization", "short_abstract": "This research area aims to investigate how to best visualize graph-typed data, both abstractly as well as in domain-specific applications.", "abstract": "Graph-typed data is ubiquitous, from logistical or transportation networks, through social or correspondence networks, all the way to more abstract biochemical interaction networks. Each such application domain brings with it unique analytical goals, metadata, canonical representations, as well as types of vertices and edges. Routine, automated analyses of such data, while important, can often not fully support the kind of decision-making or data exploration necessary for more complex and/or larger networks. Here, it is through (interactive) visualization that we can support domain experts in their exploratory and (semi-) confirmatory research endeavors. On the one hand, we can build custom, tailor-made interactive, visual dashboards which directly address the needs and support the analysis of our domain expert collaborators. On the other, we can look at more foundational questions about how to best represent graph-typed data or better understand the factors which negatively/positively affect comprehension.
\r\n", "website": "https://www.cg.tuwien.ac.at/research/area/NetVis", "teaser": { "name": "teaser.png", "path": "research_area:NetVis", "type": "image/png", "size": 1948873, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/NetVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "ehlers-2023-iro", "mazurek-2018-veq", "sorger-2019-odn", "sorger-2021-egonet", "steinboeck-2018-lbg", "waldner-2014-ghi", "waldner-2020-tbg" ], "projects": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=NetVis", "__class": "ResearchArea" } ], "keywords": [ "Information visualization", "search interfaces", "empirical studies in visualization" ], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "mazurek-2018-veq-paper.pdf", "type": "application/pdf", "size": 1891501, "path": "Publication:mazurek-2018-veq", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/mazurek-2018-veq/mazurek-2018-veq-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/mazurek-2018-veq/mazurek-2018-veq-paper:thumb{{size}}.png" }, { "description": "Density-based compact Euler Diagram", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 919, "image_height": 656, "name": "mazurek-2018-veq-teaser.png", "type": "image/png", "size": 34882, "path": "Publication:mazurek-2018-veq", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/mazurek-2018-veq/mazurek-2018-veq-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/mazurek-2018-veq/mazurek-2018-veq-teaser:thumb{{size}}.png" }, { "description": null, "filetitle": "video", "main_file": true, "use_in_gallery": false, "access": "public", "name": "mazurek-2018-veq-video.mp4", "type": "video/mp4", "size": 30231176, "path": "Publication:mazurek-2018-veq", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/mazurek-2018-veq/mazurek-2018-veq-video.mp4", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/mazurek-2018-veq/mazurek-2018-veq-video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2018/mazurek-2018-veq/mazurek-2018-veq-video:video.mp4" } ], "projects_workgroups": [ { "id": "deskollage", "workgroup_id": "vis", "drupal_id": 4198, "name": "Visual Information Foraging on the Desktop", "name_de": null, "website": null, "status": "active", "short_abstract": "The goal of this project is to design and develop novel interactive visualization techniques to support knowledge workers in making sense of their unstructured, dynamic information collections. ", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. On the one hand, the studies show that, in some situations, interactive visualization can be less efficient than working with unprocessed text-based information. On the other hand, the studies also show that combining automatic data analysis with interactive visualization can lead to more unexpected findings, especially when exploring large data. The extent of manual information organization varies with the task: the less users know about the gathered information, the more automatic organization they expect. \n\nIn summary, this project contributed novel user interface concepts and design guidelines for user interfaces supporting information foraging and sensemaking. The techniques and study results were published at high-ranking peer-reviewed venues, and it can be expected that the findings of this project shape the way how users seek and organize their information in the future. \n\n", "start_date": "2015-12-01", "end_date": "2018-12-31", "leader_id": 1110, "logo": { "name": "logo.png", "path": "project:deskollage", "type": "image/png", "size": 331697, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/deskollage/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "T 752-N30", "comment": null } ], "research_areas": [ "InfoVis" ], "publications": [ "2019-ic", "byska-2019-mdfc", "casellato-2016-pkg", "cizmic-2018-evd", "donabauer-2015-asc", "dworschak-2016-szcm", "edlinger-2018-vwr", "georgiev-2019-cbg", "geymayer-2017-std", "gundacker-2020-wlm", "gusenbauer-2018", "hromniak-2019-vcn", "Koszticsak-2017-ewt", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "polatsek-2018-stv", "samoul-2019-cnp", "sietzen-2019-wnn", "sietzen-ifv-2019", "smiech-2018-tei", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "trautner-2018-imd", "unger-2019_vcp", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg" ], "url": "https://www.cg.tuwien.ac.at/research/projects/deskollage", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/mazurek-2018-veq/", "__class": "Publication" }, { "id": "steinboeck-2017-vbn", "type_id": "masterthesis", "tu_id": null, "repositum_id": null, "title": "Interactive Visual Exploration Interface for Large Bipartite Networks", "date": "2018-05-30", "abstract": "In this thesis we introduce BiCFlows, a novel interactive visualization approach to explore large bipartite graphs. We were motivated by the Media Transparency Database, a public database established by the Austrian government to provide information about governmental advertising and subsidies expenses, which holds the characteristics of a large, weighted bipartite graph.\nCurrent approaches that deal with the visualization of the Media Transparency Database are limited by the fact that they do not offer a sufficient overview of the whole dataset. Other existing approaches that are not particularly designed for the Media Transparency Database, but deal with the visualization of bipartite graphs are in addition limited by their lack of scalability for large datasets.\nAggregation is an often used concept in reducing the amount of data by grouping together similar data objects. This only works if the appropriate object properties are present in the data to use them for the aggregation. If this additional information is missing, like in the Media Transparency Database, other aggregation techniques have to be used. Since we are dealing with bipartite graphs in our approach, we use the concept of biclustering to establish a hierarchical structure within the data that can be interactively explored by the user.\nWe showed that BiCFlows cannot only be used for the Media Transparency Database, but also for other datasets that share the characteristics of a weighted bipartite graph. Furthermore, we conducted an insight-based user study to compare BiCFlows with existing concepts and discussed advantages and drawbacks. We showed that BiCFlows supported users in their exploration process and let them gain more insight than with existing approaches.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "sketch", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 649, "image_height": 462, "name": "steinboeck-2017-vbn-sketch.PNG", "type": "image/png", "size": 30764, "path": "Publication:steinboeck-2017-vbn", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/steinboeck-2017-vbn/steinboeck-2017-vbn-sketch.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/steinboeck-2017-vbn/steinboeck-2017-vbn-sketch:thumb{{size}}.png" }, "sync_repositum_override": null, "authors": [ { "id": 1378, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Daniel", "lastname": "Steinböck", "searchname": "Daniel Steinböck", "is_teacher": false, "name": "Daniel Steinböck", "publications": [ "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "waldner-2020-tbg" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1378", "__class": "Author" } ], "date_end": "2018-05-30", "date_start": "2017-07", "matrikelnr": "0826088", "open_access": "yes", "supervisor": [ { "id": 166, "drupal_id": 111, "orcid_id": "0000-0002-8569-4149", "website": "https://www.cg.tuwien.ac.at/staff/EduardGröller", "firstname": "Eduard", "lastname": "Gröller", "searchname": "Eduard Gröller", "is_teacher": true, "name": "Eduard Gröller", "publications": [ "a-2001-ah", "a-2001-ahr", "a-2001-Rec", "Acquisto-1995-DCR", "alacruzECR2004", "Alharbi_2021", "Alsallakh_2012_RCW", "amirkhanov_2012", "amirkhanov_2012heur", "amirkhanov_2013_AMA", "amirkhanov-2011", "amirkhanov-2014-ama", "amirkhanov-2017-cffet", "amirkhanov-2018-withteeth", "amirkhanov-2019-manylands", "amirkhanov2010AMA", "amirkhanov2020visual", "Antonini2020", "Artner-2004-Hig", "Artner-2005-Hig", "Auzinger_Mistelbauer_2013_CSR", "balabanian-2007-ant", "balabanian-2008-hvv", "balabanian-2008-tst", "Balabanian-2010-IIV", "Balabanian-2010-PSDSV", "Bartroli-2002-Pro", "Bartroli-2003-Geo", "Bartroli-2003-Non", "beham-2014-cupid", "Berger_2011_UAE", "Berger-1998-Col", "Berger-2000-Col", "Bruckner_Stefan_2015_VAS", "Bruckner-2003-The", "bruckner-2005-ICV", "bruckner-2005-vid", "bruckner-2005-VIS", "bruckner-2006-EVV", "bruckner-2006-ICE", "bruckner-2007-EDF", "bruckner-2007-STF", "bruckner-2008-IVV", "bruckner-2009-BVQ", "bruckner-2009-IVV", "bruckner-2010-HVC", "bruckner-2010-IFC", "burns-2007-fea", "Carata_2011_IVE", "Castro-1998-TFS", "Cornel_Daniel_2015_VOC", "cornel-2022-wih", "coto-2005-MAC", "Csebfalvi-1999-Fast", "Csebfalvi-1999-MIP", "Csebfalvi-2000-Fas", "Csebfalvi-2000-GELR", "Csebfalvi-2000-Gra", "Csebfalvi-2000-IVRBM", "Csebfalvi-2001-Fas", "Csebfalvi-2001-Int", "Csebfalvi-2001-NPVR", "Csebfalvi-2002-FPVF", "Csebfalvi-2002-SBICG", "Csebfalvi-2002-Smo", "Csebfalvi-2012-IOM", "dataset-stagbeetle", "Dhanoa_2021", "dhanoa-2022-apm", "Diehl_2015", "Diehl_2021", "diehl-2013-VTA", "Diehl-2017-Albero", "Edi_2019_10_01", "eg-tut2005-iv", "EuroVis2018-ShortPapers-Karall", "EuroVis2018-ShortPapers-Reiter", "fernandez-2022-ergoexplorer", "fischel-1995-vis", "Fischel-1995-VLS", "Fischel-1997-CSVVP", "Fischel-1998-Cas", "fmistelbauer-2014-adict", "fritz-2009-ava", "Froehler_Berhnard_2015_ESM", "fuchs_vhml", "fuchs-2008-del", "Fuhr-1999-Multi", "Fuhrmann-1998-Rea", "fuhrmann-1998-reaX", "Furmanova_2018", "furmanova_2020", "Gall2021", "Ganuza", "Ganuza_2015", "Ganuza_MJ_2015_AVe", "Ganuza_ML_2015_ISA", "Ganuza-2017-IVCSGM", "Gavrilescu-2010-CIE", "Gillmann2021", "Glaeser-1997-EVG", "Glaeser-1998-AFa", "Glaeser-1998-Eff", "Glaeser-1999-Fas", "glanznig-2009-LAMC", "Grimm-2003-CPU", "Grimm-2003-HYP", "grimm-2004-arefined", "GRIMM-2004-FDM", 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"__class": "Author" } ], "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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"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": [], "files": [ { "description": null, "filetitle": "Master Thesis", "main_file": true, "use_in_gallery": true, "access": "public", "name": "steinboeck-2017-vbn-Master Thesis.pdf", "type": "application/pdf", "size": 14008127, "path": "Publication:steinboeck-2017-vbn", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/steinboeck-2017-vbn/steinboeck-2017-vbn-Master Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/steinboeck-2017-vbn/steinboeck-2017-vbn-Master Thesis:thumb{{size}}.png" }, { "description": null, "filetitle": "Poster", "main_file": true, "use_in_gallery": true, "access": "public", "name": "steinboeck-2017-vbn-Poster.pdf", "type": "application/pdf", "size": 1309833, "path": "Publication:steinboeck-2017-vbn", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/steinboeck-2017-vbn/steinboeck-2017-vbn-Poster.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/steinboeck-2017-vbn/steinboeck-2017-vbn-Poster:thumb{{size}}.png" }, { "description": null, "filetitle": "sketch", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 649, "image_height": 462, "name": "steinboeck-2017-vbn-sketch.PNG", "type": "image/png", "size": 30764, "path": "Publication:steinboeck-2017-vbn", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/steinboeck-2017-vbn/steinboeck-2017-vbn-sketch.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/steinboeck-2017-vbn/steinboeck-2017-vbn-sketch:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "deskollage", "workgroup_id": "vis", "drupal_id": 4198, "name": "Visual Information Foraging on the Desktop", "name_de": null, "website": null, "status": "active", "short_abstract": "The goal of this project is to design and develop novel interactive visualization techniques to support knowledge workers in making sense of their unstructured, dynamic information collections. ", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. On the one hand, the studies show that, in some situations, interactive visualization can be less efficient than working with unprocessed text-based information. On the other hand, the studies also show that combining automatic data analysis with interactive visualization can lead to more unexpected findings, especially when exploring large data. The extent of manual information organization varies with the task: the less users know about the gathered information, the more automatic organization they expect. \n\nIn summary, this project contributed novel user interface concepts and design guidelines for user interfaces supporting information foraging and sensemaking. The techniques and study results were published at high-ranking peer-reviewed venues, and it can be expected that the findings of this project shape the way how users seek and organize their information in the future. \n\n", "start_date": "2015-12-01", "end_date": "2018-12-31", "leader_id": 1110, "logo": { "name": "logo.png", "path": "project:deskollage", "type": "image/png", "size": 331697, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/deskollage/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "T 752-N30", "comment": null } ], "research_areas": [ "InfoVis" ], "publications": [ "2019-ic", "byska-2019-mdfc", "casellato-2016-pkg", "cizmic-2018-evd", "donabauer-2015-asc", "dworschak-2016-szcm", "edlinger-2018-vwr", "georgiev-2019-cbg", "geymayer-2017-std", "gundacker-2020-wlm", "gusenbauer-2018", "hromniak-2019-vcn", "Koszticsak-2017-ewt", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "polatsek-2018-stv", "samoul-2019-cnp", "sietzen-2019-wnn", "sietzen-ifv-2019", "smiech-2018-tei", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "trautner-2018-imd", "unger-2019_vcp", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg" ], "url": "https://www.cg.tuwien.ac.at/research/projects/deskollage", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/steinboeck-2017-vbn/", "__class": "Publication" }, { "id": "gusenbauer-2018", "type_id": "masterthesis", "tu_id": null, "repositum_id": null, "title": "Bitstream - A bottom-up/top-down hybrid approach for web-based visual analysis of big data", "date": "2018-05-14", "abstract": "Analyzing large amounts of data is becoming an ever increasing problem. Bitcoin as an\nexample has produced more data than is possible to analyze. In order to compensate for these difficulties, creative ideas that employ data aggregation or minimization have been proposed. Other work also focuses on introducing novel visualization types that are geared towards the visualization of blockchain data. However, visualization of graphs through node-link diagrams remains a difficult challenge. Analysis of the Bitcoin transaction graph to follow bitcoin (BTC) transactions (TXs) poses a difficult problem due to the Bitcoin\nprotocol and the amount of data. This thesis combines two data processing strategies to visualize big network data on commodity hardware. The idea is to use visualization as a technique to analyze a data-set containing Bitcoin transaction information. Criminals use Bitcoin as a means of payment because of its guaranteed pseudonymity. Through visualization we aim to identify patterns that will allow us to deanonymize transactions. To do so we use a proxy server that does data preprocessing before they are visualized on a web client. The proxy leverages parallel computing to be able to do top-down and bottom-up data processing fast enough for interactive visualization. This is done through incremental loading (bottom-up), which enables to visualize data immediately\nwithout a (pre-)processing delay. The database containing the public Bitcoin ledger is over 163 gigabytes in size. The resulting graph has more than 800 million nodes. As this information is too much to be visualized, we also employ a top-down approach of data aggregation and graph minimization of the transactional graph. Through this methodology we intend to solve performance problems of long processing delays and the problem of fractured data where the data is shown only partially in the visualization.\nWe collaborate with security experts who share insights into their expertise through a continuously ongoing dialog. Exploratory analysis on a big data-set such as the Bitcoin ledger, enabled through the methodology presented in this thesis, will help security experts to analyze the money flow in a financial network that is used by criminals for its anonymity. We evaluate the result through the performance and feedback of these security experts as well as benchmark the performance against current best practice approaches.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": true, "use_in_gallery": true, "access": "public", "image_width": 237, "image_height": 113, "name": "gusenbauer-2018-image.JPG", "type": "image/jpeg", "size": 11712, "path": "Publication:gusenbauer-2018", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/gusenbauer-2018/gusenbauer-2018-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/gusenbauer-2018/gusenbauer-2018-image:thumb{{size}}.png" }, "sync_repositum_override": null, "authors": [ { "id": 1257, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Matthias", "lastname": "Gusenbauer", "searchname": "Matthias Gusenbauer", "is_teacher": false, "name": "Matthias Gusenbauer", "publications": [ "Gusenbauer_Matthias_2015_ANM", "gusenbauer-2018", "gusenbauer-2018-P" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1257", "__class": "Author" } ], "date_end": "2018-05-14", "date_start": "2016-11", "matrikelnr": "1125577", "supervisor": [ { "id": 1110, "drupal_id": 625, "orcid_id": "0000-0003-1387-5132", "website": "https://www.cg.tuwien.ac.at/staff/ManuelaWaldner", "firstname": "Manuela", "lastname": "Waldner", "searchname": "Manuela Waldner", "is_teacher": true, "name": "Manuela Waldner", "publications": [ "2019-ic", "Alharbi_2021", "bernhard-2016-gft", "byska-2019-mdfc", "eschner-2023-evl", "eschner-2023-ims", "geymayer-2017-std", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", "indirectBiasLanguageModels-2023", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "mazurek-2018-veq", "polatsek-2018-stv", 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} ], "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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"name_de": null, "website": null, "status": "active", "short_abstract": "The goal of this project is to design and develop novel interactive visualization techniques to support knowledge workers in making sense of their unstructured, dynamic information collections. ", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. On the one hand, the studies show that, in some situations, interactive visualization can be less efficient than working with unprocessed text-based information. On the other hand, the studies also show that combining automatic data analysis with interactive visualization can lead to more unexpected findings, especially when exploring large data. The extent of manual information organization varies with the task: the less users know about the gathered information, the more automatic organization they expect. \n\nIn summary, this project contributed novel user interface concepts and design guidelines for user interfaces supporting information foraging and sensemaking. The techniques and study results were published at high-ranking peer-reviewed venues, and it can be expected that the findings of this project shape the way how users seek and organize their information in the future. \n\n", "start_date": "2015-12-01", "end_date": "2018-12-31", "leader_id": 1110, "logo": { "name": "logo.png", "path": "project:deskollage", "type": "image/png", "size": 331697, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/deskollage/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "T 752-N30", "comment": null } ], "research_areas": [ "InfoVis" ], "publications": [ "2019-ic", "byska-2019-mdfc", "casellato-2016-pkg", "cizmic-2018-evd", "donabauer-2015-asc", "dworschak-2016-szcm", "edlinger-2018-vwr", "georgiev-2019-cbg", "geymayer-2017-std", "gundacker-2020-wlm", "gusenbauer-2018", "hromniak-2019-vcn", "Koszticsak-2017-ewt", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "polatsek-2018-stv", "samoul-2019-cnp", "sietzen-2019-wnn", "sietzen-ifv-2019", "smiech-2018-tei", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "trautner-2018-imd", "unger-2019_vcp", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg" ], "url": "https://www.cg.tuwien.ac.at/research/projects/deskollage", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/gusenbauer-2018/", "__class": "Publication" }, { "id": "waldner-2018-ved", "type_id": "talk", "tu_id": null, "repositum_id": null, "title": "Visual Data Exploration and Analysis in Emerging Display Environments ", "date": "2018-04-05", "abstract": "Increasingly powerful computing and display hardware open up entirely new ways for visual data exploration and analysis. Powerful machines and emerging display environments facilitate novel visual exploration techniques, collaborative data analysis, and even immersion into the scientific data. This talk will address the challenges we faced when bringing biomolecular visual analysis tools and complex molecular visualizations into such large, multi-user environments. A special focus lies on interfaces and attention guidance techniques we designed and evaluated to keep the user oriented and reduce visual clutter. ", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "authors": [ { "id": 1110, "drupal_id": 625, "orcid_id": "0000-0003-1387-5132", "website": "https://www.cg.tuwien.ac.at/staff/ManuelaWaldner", "firstname": "Manuela", "lastname": "Waldner", "searchname": "Manuela Waldner", "is_teacher": true, "name": "Manuela Waldner", "publications": [ "2019-ic", "Alharbi_2021", "bernhard-2016-gft", "byska-2019-mdfc", "eschner-2023-evl", "eschner-2023-ims", "geymayer-2017-std", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", "indirectBiasLanguageModels-2023", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "mazurek-2018-veq", "polatsek-2018-stv", "reina-2020-mtv", "sietzen-2021-perturber", "sietzen-ifv-2019", "sMolBoxes_2022", "sorger-2019-odn", "sorger-2021-egonet", "steinboeck-2018-lbg", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2013-facetCloudsGI", 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"ordernum": 0 }, { "publ_id": "textures-3d-printing", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "trautner-2018-imd", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "unger-2019_vcp", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Unger2020", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "waldner-2013-ubiWM", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldner-2014-af", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldner-2014-ghi", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldner-2017-vph", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldner-2019-rld", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "webGPU_aggregateVis-2023", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "wolf-2023-cc", "field_id": "supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1110", "__class": "Author" } ], "event": "Emerging Technologies in Scientific Data Visualisation - CECAM", "location": "Pisa, Italy", "research_areas": [], "keywords": [], "weblinks": [ { "href": "https://www.cecam.org/workshop-1586.html", "caption": "CECAM workshop", "description": null, "main_file": 0 } ], "files": [], "projects_workgroups": [ { "id": "deskollage", "workgroup_id": "vis", "drupal_id": 4198, "name": "Visual Information Foraging on the Desktop", "name_de": null, "website": null, "status": "active", "short_abstract": "The goal of this project is to design and develop novel interactive visualization techniques to support knowledge workers in making sense of their unstructured, dynamic information collections. ", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. On the one hand, the studies show that, in some situations, interactive visualization can be less efficient than working with unprocessed text-based information. On the other hand, the studies also show that combining automatic data analysis with interactive visualization can lead to more unexpected findings, especially when exploring large data. The extent of manual information organization varies with the task: the less users know about the gathered information, the more automatic organization they expect. \n\nIn summary, this project contributed novel user interface concepts and design guidelines for user interfaces supporting information foraging and sensemaking. The techniques and study results were published at high-ranking peer-reviewed venues, and it can be expected that the findings of this project shape the way how users seek and organize their information in the future. \n\n", "start_date": "2015-12-01", "end_date": "2018-12-31", "leader_id": 1110, "logo": { "name": "logo.png", "path": "project:deskollage", "type": "image/png", "size": 331697, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/deskollage/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "T 752-N30", "comment": null } ], "research_areas": [ "InfoVis" ], "publications": [ "2019-ic", "byska-2019-mdfc", "casellato-2016-pkg", "cizmic-2018-evd", "donabauer-2015-asc", "dworschak-2016-szcm", "edlinger-2018-vwr", "georgiev-2019-cbg", "geymayer-2017-std", "gundacker-2020-wlm", "gusenbauer-2018", "hromniak-2019-vcn", "Koszticsak-2017-ewt", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "polatsek-2018-stv", "samoul-2019-cnp", "sietzen-2019-wnn", "sietzen-ifv-2019", "smiech-2018-tei", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "trautner-2018-imd", "unger-2019_vcp", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg" ], "url": "https://www.cg.tuwien.ac.at/research/projects/deskollage", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/waldner-2018-ved/", "__class": "Publication" }, { "id": "smiech-2018-tei", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Configurable Text Exploration Interface with NLP for Decision Support", "date": "2018-04", "abstract": "Having to read and understand lots of text documents and reports on a daily basis can\nbe quite challenging. The intended audience for these reports has limited resources and\nwants to reduce time spent on reading such reports. Therefore a need for a tool emerges\nthat assists the process of gaining relevant information out of reports/documents more\nquickly. These text documents are often unstructured and of varying length. They are\nwritten in the English language and are available from different sources (such as RSS\nfeeds and text files). The aim of this project is to offer a tool that supports the process of\nanalysing and understanding given texts. This is made possible by using natural language\nprocessing (NLP) and text visualization (TextVis). TextVis is already a well known and\nfrequently used solution. The herein described project uses an NLP pipeline which serves\nas preprocessing for TextVis. To provide quick insight into the data, topic extraction\nmechanisms like Latent Dirichlet Allocation (LDA) or Non-negative Matrix Factorization\n(NMF) are available for the user to be chosen within the aforementioned pipeline. A major\nchallenge for TextVis is the configuration of the NLP pipeline, because there are many\ndifferent ways of doing so and a wide range of parameters to chose from. To overcome this\nissue, this project provides a solution that enables users to easily configure and customize\ntheir own NLP pipeline. It is designed to encourage these users to experiment with\ndifferent sequences of NLP operations and parameter configurations to find a solution\nthat suites them best. In order to keep it easy to use the software, it is implemented\nentirely using web technologies to be accessible in a common web browser. The resulting\nvisualization will emphasize particular parts of the text based on a set of different factors,\nif selected so. These factors can be topics, sentiments and part-of-speech-tagged words.\nThe focus of this work lies on a visual interface that enables and encourages users to\nadjust/optimize the underlying NLP pipeline (by selecting steps and setting parameters)\nand comparing their results. Evaluation with help of user feedback showed that certain\npipeline configurations work better for certain types of texts than others. Using the\nsolution created within this work, users can adapt the tool to their needs and also tweak\nit according to requirements. There is no universal configuration that works for all\ndocuments, however.", "authors_et_al": false, "substitute": null, "main_image": { "description": "detail text view", "filetitle": "screenshot", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 985, "image_height": 585, "name": "smiech-2018-tei-screenshot.PNG", "type": "image/png", "size": 125879, "path": "Publication:smiech-2018-tei", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/smiech-2018-tei/smiech-2018-tei-screenshot.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/smiech-2018-tei/smiech-2018-tei-screenshot:thumb{{size}}.png" }, "sync_repositum_override": null, "authors": [ { "id": 1463, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Martin", "lastname": "Smiech", "searchname": "Martin Smiech", "is_teacher": false, "name": "Martin Smiech", "publications": [ "smiech-2018-tei" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1463", "__class": "Author" } ], "date_end": "2018-04", "date_start": "2017-05", "matrikelnr": "01426853", "supervisor": [ { "id": 1110, "drupal_id": 625, "orcid_id": "0000-0003-1387-5132", "website": "https://www.cg.tuwien.ac.at/staff/ManuelaWaldner", "firstname": "Manuela", "lastname": "Waldner", "searchname": "Manuela Waldner", "is_teacher": true, "name": "Manuela Waldner", "publications": [ "2019-ic", "Alharbi_2021", "bernhard-2016-gft", "byska-2019-mdfc", "eschner-2023-evl", "eschner-2023-ims", "geymayer-2017-std", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", "indirectBiasLanguageModels-2023", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "mazurek-2018-veq", "polatsek-2018-stv", "reina-2020-mtv", "sietzen-2021-perturber", "sietzen-ifv-2019", "sMolBoxes_2022", "sorger-2019-odn", "sorger-2021-egonet", "steinboeck-2018-lbg", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2013-facetCloudsGI", "waldner-2013-ubiWM", "waldner-2014-af", "waldner-2014-ghi", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "webGPU_aggregateVis-2023", "wu-2021", "wu-2021-vi" ], "publications_first": [], "project_leader": [ "d9282", "d9522", "d9555", "deskollage" ], "publication_field": [ { "publ_id": "arbesser_ba_2023", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "bayat-2022-mva", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "boesch_2014_browserHistoryVis", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "breitenecker-2020-bct", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "bugnar-esk-2021", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "casellato-2016-pkg", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "cizmic-2018-evd", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "da_cunha_melo-2023-c3m", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "donabauer-2015-asc", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "dworschak-2016-szcm", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "edlinger-2018-vwr", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "eiweck-hnv-2021", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "eschner-2023-rar", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "eschner-blur-2022", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "georgiev-2019-cbg", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Gogel2020", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "grammatikaki-thesis", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "grossmann-2021-layout", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "gundacker-2020-wlm", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "gusenbauer-2018", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "heim-gall-2020-dde", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "hromniak-2019-vcn", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "indirectBiasLanguageModels-2023", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "kimmersdorfer-fancyMaps-2023", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "korpitsch-2021-lov", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Koszticsak-2017-ewt", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "lippeck-2022-mna", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "louis-alexandre_dit_petit-frere-2022-veo", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "mahler-2021-mdar", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "matt-2023-vae", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "mayr-2021-wec", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "mazurek-2017-sio", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "mazurek-2017-vows", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "mazurek-2018-vac", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Panayotov", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Presch_2020", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "samoul-2019-cnp", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "sbardellati-2021-eveos", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "sietzen-2019-wnn", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "sietzen-2022-vacnnr", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "smiech-2018-tei", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "spegel-gruenberger-2020", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "staats-2024-atr", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "steinboeck-2017-vbn", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "steinboeck-2017-vefp", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "steinboeck-2018-lbg", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "stoff-concepMap-2021", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "textures-3d-printing", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "trautner-2018-imd", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "unger-2019_vcp", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Unger2020", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "waldner-2013-ubiWM", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldner-2014-af", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldner-2014-ghi", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldner-2017-vph", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldner-2019-rld", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "webGPU_aggregateVis-2023", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "wolf-2023-cc", "field_id": "supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1110", "__class": "Author" } ], "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.
\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": [], "files": [ { "description": "detail text view", "filetitle": "screenshot", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 985, "image_height": 585, "name": "smiech-2018-tei-screenshot.PNG", "type": "image/png", "size": 125879, "path": "Publication:smiech-2018-tei", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/smiech-2018-tei/smiech-2018-tei-screenshot.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/smiech-2018-tei/smiech-2018-tei-screenshot:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": false, "use_in_gallery": false, "access": "public", "name": "smiech-2018-tei-thesis.pdf", "type": "application/pdf", "size": 1305969, "path": "Publication:smiech-2018-tei", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/smiech-2018-tei/smiech-2018-tei-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/smiech-2018-tei/smiech-2018-tei-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "deskollage", "workgroup_id": "vis", "drupal_id": 4198, "name": "Visual Information Foraging on the Desktop", "name_de": null, "website": null, "status": "active", "short_abstract": "The goal of this project is to design and develop novel interactive visualization techniques to support knowledge workers in making sense of their unstructured, dynamic information collections. ", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. On the one hand, the studies show that, in some situations, interactive visualization can be less efficient than working with unprocessed text-based information. On the other hand, the studies also show that combining automatic data analysis with interactive visualization can lead to more unexpected findings, especially when exploring large data. The extent of manual information organization varies with the task: the less users know about the gathered information, the more automatic organization they expect. \n\nIn summary, this project contributed novel user interface concepts and design guidelines for user interfaces supporting information foraging and sensemaking. The techniques and study results were published at high-ranking peer-reviewed venues, and it can be expected that the findings of this project shape the way how users seek and organize their information in the future. \n\n", "start_date": "2015-12-01", "end_date": "2018-12-31", "leader_id": 1110, "logo": { "name": "logo.png", "path": "project:deskollage", "type": "image/png", "size": 331697, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/deskollage/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "T 752-N30", "comment": null } ], "research_areas": [ "InfoVis" ], "publications": [ "2019-ic", "byska-2019-mdfc", "casellato-2016-pkg", "cizmic-2018-evd", "donabauer-2015-asc", "dworschak-2016-szcm", "edlinger-2018-vwr", "georgiev-2019-cbg", "geymayer-2017-std", "gundacker-2020-wlm", "gusenbauer-2018", "hromniak-2019-vcn", "Koszticsak-2017-ewt", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "polatsek-2018-stv", "samoul-2019-cnp", "sietzen-2019-wnn", "sietzen-ifv-2019", "smiech-2018-tei", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "trautner-2018-imd", "unger-2019_vcp", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg" ], "url": "https://www.cg.tuwien.ac.at/research/projects/deskollage", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/smiech-2018-tei/", "__class": "Publication" }, { "id": "cizmic-2018-evd", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Exploratory Data Visualization Dashboard for Technical Analysis of Commodity Market Indicators", "date": "2018-04", "abstract": "Companies and traders working in the commodity market encounter a variety of different\ndata sets, including numerous economic indicators. The analysis of those indicators and\ntheir connection to certain markets can lead to important insights. The understanding of\nthe market can be improved and predictions of the future market development can be\ncreated. However, dozens of economic indicators exist and one of the main challenges is\nto show a clear overview of the indicators and identify those, which show a correlation\nto a certain market. Software tools are often utilised in order to perform the analysis\nof financial markets. However, according to domain experts, they often hit the limit of\nhuman perception capabilities. This thesis focuses on the development of a prototypical\nweb application dashboard, which enables the user to analyse the relation between\na defined commodity market and different economic indicators. Besides the relation\nbetween one indicator and a given market, the possibility to interactively create one’s own\ncomposite indicator, for comparison with the given market, is implemented. The process\nof creating a composite indicator is another challenge as it requires numerous decisions to\nbe made. The dashboard therefore offers a platform for exploring the different composite\nindicator configurations. Moreover, the web-application provides also some visualization\nand interaction techniques, like highlighting, brushing and details-on-demand to enhance\nthe comparison process and amplify human cognition.", "authors_et_al": false, "substitute": null, "main_image": { "description": "composite indicator view", "filetitle": "screenshot", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 909, "image_height": 378, "name": "cizmic-2018-evd-screenshot.PNG", "type": "image/png", "size": 63662, "path": "Publication:cizmic-2018-evd", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/cizmic-2018-evd/cizmic-2018-evd-screenshot.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/cizmic-2018-evd/cizmic-2018-evd-screenshot:thumb{{size}}.png" }, "sync_repositum_override": null, "authors": [ { "id": 1462, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Dea", "lastname": "Cizmic", "searchname": "Dea Cizmic", "is_teacher": false, "name": "Dea Cizmic", "publications": [ "cizmic-2018-evd" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1462", "__class": "Author" } ], "date_end": "2018-04", "date_start": "2017-05", "matrikelnr": "1425788", "supervisor": [ { "id": 1110, "drupal_id": 625, "orcid_id": "0000-0003-1387-5132", "website": "https://www.cg.tuwien.ac.at/staff/ManuelaWaldner", "firstname": "Manuela", "lastname": "Waldner", "searchname": "Manuela Waldner", "is_teacher": true, "name": "Manuela Waldner", "publications": [ "2019-ic", "Alharbi_2021", "bernhard-2016-gft", "byska-2019-mdfc", "eschner-2023-evl", "eschner-2023-ims", "geymayer-2017-std", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", "indirectBiasLanguageModels-2023", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "mazurek-2018-veq", "polatsek-2018-stv", "reina-2020-mtv", "sietzen-2021-perturber", "sietzen-ifv-2019", "sMolBoxes_2022", "sorger-2019-odn", "sorger-2021-egonet", "steinboeck-2018-lbg", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2013-facetCloudsGI", "waldner-2013-ubiWM", "waldner-2014-af", "waldner-2014-ghi", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "webGPU_aggregateVis-2023", "wu-2021", "wu-2021-vi" ], "publications_first": [], "project_leader": [ "d9282", "d9522", "d9555", "deskollage" ], "publication_field": [ { "publ_id": "arbesser_ba_2023", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "bayat-2022-mva", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "boesch_2014_browserHistoryVis", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "breitenecker-2020-bct", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "bugnar-esk-2021", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "casellato-2016-pkg", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "cizmic-2018-evd", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "da_cunha_melo-2023-c3m", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "donabauer-2015-asc", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "dworschak-2016-szcm", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "edlinger-2018-vwr", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "eiweck-hnv-2021", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "eschner-2023-rar", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "eschner-blur-2022", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "georgiev-2019-cbg", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Gogel2020", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "grammatikaki-thesis", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "grossmann-2021-layout", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "gundacker-2020-wlm", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "gusenbauer-2018", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "heim-gall-2020-dde", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "hromniak-2019-vcn", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "indirectBiasLanguageModels-2023", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "kimmersdorfer-fancyMaps-2023", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "korpitsch-2021-lov", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Koszticsak-2017-ewt", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "lippeck-2022-mna", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "louis-alexandre_dit_petit-frere-2022-veo", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "mahler-2021-mdar", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "matt-2023-vae", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "mayr-2021-wec", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "mazurek-2017-sio", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "mazurek-2017-vows", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "mazurek-2018-vac", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Panayotov", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Presch_2020", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "samoul-2019-cnp", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "sbardellati-2021-eveos", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "sietzen-2019-wnn", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "sietzen-2022-vacnnr", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "smiech-2018-tei", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "spegel-gruenberger-2020", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "staats-2024-atr", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "steinboeck-2017-vbn", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "steinboeck-2017-vefp", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "steinboeck-2018-lbg", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "stoff-concepMap-2021", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "textures-3d-printing", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "trautner-2018-imd", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "unger-2019_vcp", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Unger2020", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "waldner-2013-ubiWM", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldner-2014-af", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldner-2014-ghi", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldner-2017-vph", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldner-2019-rld", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "webGPU_aggregateVis-2023", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "wolf-2023-cc", "field_id": "supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1110", "__class": "Author" } ], "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.
\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": [], "files": [ { "description": "composite indicator view", "filetitle": "screenshot", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 909, "image_height": 378, "name": "cizmic-2018-evd-screenshot.PNG", "type": "image/png", "size": 63662, "path": "Publication:cizmic-2018-evd", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/cizmic-2018-evd/cizmic-2018-evd-screenshot.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/cizmic-2018-evd/cizmic-2018-evd-screenshot:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": false, "use_in_gallery": false, "access": "public", "name": "cizmic-2018-evd-thesis.pdf", "type": "application/pdf", "size": 2131622, "path": "Publication:cizmic-2018-evd", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/cizmic-2018-evd/cizmic-2018-evd-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/cizmic-2018-evd/cizmic-2018-evd-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "deskollage", "workgroup_id": "vis", "drupal_id": 4198, "name": "Visual Information Foraging on the Desktop", "name_de": null, "website": null, "status": "active", "short_abstract": "The goal of this project is to design and develop novel interactive visualization techniques to support knowledge workers in making sense of their unstructured, dynamic information collections. ", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. On the one hand, the studies show that, in some situations, interactive visualization can be less efficient than working with unprocessed text-based information. On the other hand, the studies also show that combining automatic data analysis with interactive visualization can lead to more unexpected findings, especially when exploring large data. The extent of manual information organization varies with the task: the less users know about the gathered information, the more automatic organization they expect. \n\nIn summary, this project contributed novel user interface concepts and design guidelines for user interfaces supporting information foraging and sensemaking. The techniques and study results were published at high-ranking peer-reviewed venues, and it can be expected that the findings of this project shape the way how users seek and organize their information in the future. \n\n", "start_date": "2015-12-01", "end_date": "2018-12-31", "leader_id": 1110, "logo": { "name": "logo.png", "path": "project:deskollage", "type": "image/png", "size": 331697, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/deskollage/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "T 752-N30", "comment": null } ], "research_areas": [ "InfoVis" ], "publications": [ "2019-ic", "byska-2019-mdfc", "casellato-2016-pkg", "cizmic-2018-evd", "donabauer-2015-asc", "dworschak-2016-szcm", "edlinger-2018-vwr", "georgiev-2019-cbg", "geymayer-2017-std", "gundacker-2020-wlm", "gusenbauer-2018", "hromniak-2019-vcn", "Koszticsak-2017-ewt", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "polatsek-2018-stv", "samoul-2019-cnp", "sietzen-2019-wnn", "sietzen-ifv-2019", "smiech-2018-tei", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "trautner-2018-imd", "unger-2019_vcp", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg" ], "url": "https://www.cg.tuwien.ac.at/research/projects/deskollage", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/cizmic-2018-evd/", "__class": "Publication" }, { "id": "polatsek-2018-stv", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": null, "title": "Exploring visual attention and saliency modeling for task-based visual analysis", "date": "2018-02", "abstract": "Memory, visual attention and perception play a critical role in the design of visualizations. The way users observe a visualization is affected by salient stimuli in a scene as well as by domain knowledge, interest, and the task. While recent saliency models manage to predict the users’ visual attention in visualizations during exploratory analysis, there is little evidence how much influence bottom-up saliency has on task-based visual analysis. Therefore, we performed an eye-tracking study with 47 users to determine the users’ path of attention when solving three low-level analytical tasks using 30 different charts from the MASSVIS database [1]. We also compared our task-based eye tracking data to the data from the original memorability experiment by Borkin et al. [2]. We found that solving a task leads to more consistent viewing patterns compared to exploratory visual analysis. However, bottom-up saliency of a visualization has negligible influence on users’ fixations and task efficiency when performing a low-level analytical task. Also, the efficiency of visual search for an extreme target data point is barely influenced by the target’s bottom-up saliency. Therefore, we conclude that bottom-up saliency models tailored towards information visualization are not suitable for predicting visual attention when performing task-based visual analysis. We discuss potential reasons and suggest extensions to visual attention models to better account for task-based visual analysis.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "graphical abstract", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 591, "image_height": 584, "name": "polatsek-2018-stv-graphical abstract.png", "type": "image/png", "size": 193042, "path": "Publication:polatsek-2018-stv", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/polatsek-2018-stv/polatsek-2018-stv-graphical abstract.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/polatsek-2018-stv/polatsek-2018-stv-graphical abstract:thumb{{size}}.png" }, "sync_repositum_override": null, "authors": [ { "id": 1545, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Patrik", "lastname": "Polatsek", "searchname": "Patrik Polatsek", 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"Peter Kapec", "is_teacher": false, "name": "Peter Kapec", "publications": [ "polatsek-2018-stv" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1546", "__class": "Author" }, { "id": 1547, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Wanda", "lastname": "Benesova", "searchname": "Wanda Benesova", "is_teacher": false, "name": "Wanda Benesova", "publications": [ "polatsek-2018-stv" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1547", "__class": "Author" } ], "doi": "https://doi.org/10.1016/j.cag.2018.01.010", "journal": "Computers & Graphics", "number": "2", "open_access": "no", "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.
\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" }, { "id": "Perception", "drupal_id": 4136, "name": "Perception", "short_abstract": "In this area, our research focuses on understanding and using the capabilities of human perception for designing high-quality graphics algorithms and effective visualizations.", "abstract": "In computer graphics we produce images, videos, visualizations and other content that is perceived by humans. By understanding the limits of human perception, we can design and optimize rendering algorithms that perfectly fit users' needs, tailor visualizations to make data better understandable, and effectively draw the user's attention to important information.
\r\n", "website": "https://www.cg.tuwien.ac.at/research/area/Perception", "teaser": { "name": "teaser.PNG", "path": "research_area:Perception", "type": "image/png", "size": 259428, "orig_name": "teaser.PNG", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Perception/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend", "vis" ], "publications": [ "bernhard-2011-maicg", "bernhard-2014-EFD", "bernhard-2014-GTOM", "bernhard-2016-gft", "birkeland_aasmund_2014_pums", "cardoso-2022-rtpercept", "ERLER-2017-HVR", "eschner-2023-ims", "eschner-blur-2022", "georgiev-2019-cbg", "Groeller_2016_P7", "grossmann-2021-layout", "hecher-2012-MH", "hecher-2014-MH", "HECHER-2017-HDY", "huerbe-2019-BA", "Kathi-2018-VRB", "koch-2019-PR", "Koszticsak-2017-ewt", "KREUZER-2017-PBF", "kristmann-2022-occ", "kroesl-2018-DC", "kroesl-2018-TVS", "kroesl-2019-ICthroughVR", "kroesl-2019-ThesisFF", "kroesl-2020-XREye", "Laschober-2018", "Luidolt-2020-DA", "luidolt-2020-lightperceptionVR", "mayr-2021-wec", "mindek-2017-dsn", "panfili-2019-VAVR", "panfili-2021-myop", "plank-2017-sldg", "polatsek-2018-stv", "Reichinger-2016-spaghetti", "schindler_2020vis", "schuller_reichl-2019-avt", "Semmelrath-2022-IRS", "stappen_SteFAS", "steinkellner-2022-dll", "sundstedt-2013-vag", "trautner-2018-imd", "Vasylevska_Khrystyna-2019-TEFVR", "viola-evr", "Waldin_Nicholas_2016_Colormaps", "Waldin_Nicholas_2016_Individualization", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2017-thesis", "waldner-2013-facetCloudsGI", "waldner-2014-af", "waldner-2017-vph", "waldner-2019-rld" ], "projects": [ "CROSSMOD" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Perception", "__class": "ResearchArea" } ], "keywords": [ "Information visualization", "Eye-tracking experiment", "Saliency", "Visual attention", "Low-level analytical tasks" ], "weblinks": [ { "href": "https://www.sciencedirect.com/science/article/pii/S0097849318300104", "caption": null, "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "graphical abstract", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 591, "image_height": 584, "name": "polatsek-2018-stv-graphical abstract.png", "type": "image/png", "size": 193042, "path": "Publication:polatsek-2018-stv", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/polatsek-2018-stv/polatsek-2018-stv-graphical abstract.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/polatsek-2018-stv/polatsek-2018-stv-graphical abstract:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "polatsek-2018-stv-paper.pdf", "type": "application/pdf", "size": 3228380, "path": "Publication:polatsek-2018-stv", "url": 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"bernhard-2016-gft", "Bernold_2019", "bernold-2019-epr", "bhore-2021-issac", "birkeland_aasmund_2014_pums", "Birkeland-2012-IMC", "BirsakHanzl-2009", "boeroendy-2022-uio", "boesch_2014_browserHistoryVis", "borgo-2013-gly", "borondy2022", "bouzari-thesis", "Brandorff-08-OV", "brandorff-2009-erv", "brandstaetter_01", "brandstaetter-2007-vosd", "Brandstaetter2020", "breitenecker-2020-bct", "bront-2023-svo", "brucker-2010-RES", "Bruckner_Stefan_2015_VAS", "bruckner-2004-EVV", "bruckner-2005-AIV", "bruckner-2005-ATI", "bruckner-2005-ICV", "bruckner-2005-vid", "bruckner-2005-VIS", "bruckner-2006-EVV", "bruckner-2006-ICE", "bruckner-2007-EDF", "bruckner-2007-STF", "bruckner-2008-IIV", "bruckner-2008-IVV", "bruckner-2009-BVQ", "bruckner-2009-IVV", "bruckner-2010-HVC", "bruckner-2010-IFC", "bruckner-2010-ISM", "bruckner-2010-SES", "Bruckner-2012-VEA", "buerger_raphael_2006_3dpoly", "Buerger-2007-cmv", "Buerger-2007-eurovis", "buerger-2007-star", "bugnar-esk-2021", "burns-2007-fea", 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"eschner-2023-evl", "eschner-2023-ims", "eschner-blur-2022", "Escribano_2017", "Essler2022", "EuroVis2018-ShortPapers-Karall", "EuroVis2018-ShortPapers-Reiter", "facial2004", "Fechter_2011_DBS", "filipovic-2014-dect", "FISCHL-2012-CTASEG", "fmistelbauer-2014-ad", "fmistelbauer-2014-adict", "Ford-2012-HRV", "fourousan2021", "freiler-2008-ste", "fritz-2009-ieq", "Froehler_Berhnard_2015_ESM", "froschauer-2009-iod", "Fruehstueck_Anna_2015_DOM", "fuchs_raphael_2007_par", "fuchs_vhml", "fuchs-2008-del", "fuchs-vortex", "furmanova_2020", "gadllah_2016", "Gadllah_Hani_2016", "gall_2016", "Gall_2017", "gall_alexander_2016BA", "Gall2020", "Gall2021", "gangl-2018-gpsart", "Ganglberger-2022-cg", "ganglberger2019", "Ganuza", "Ganuza_2015", "Ganuza_MJ_2015_AVe", "Ganuza_ML_2015_ISA", "Ganuza-2017-IVCSGM", "Gavrilescu_2011_VGP", "gavrilescu-2008-vsc", "gavrilescu-2009-postrend", "Gavrilescu-2010-CIE", "Gehrer_Daniel_CUI", "Gehrer-2017", "Gehrer-2017-molmach", "georgiev-2019-cbg", "gerl-2006-vhi", "geymayer-2017-std", "Gietl_2020", "Gillmann2021", "glanznig-2009-LAMC", "glinzner-2016-tex", "Gogel2020", "gostler-2015-3dp", "grammatikaki-thesis", "grimm-2004-arefined", "GRIMM-2004-FDMX-P", "grimm-2004-memory", "GRIMM-2004-PPC", "grimm-2004-volume", "Groeller_2011_CVC", "Groeller_2011_CW", "Groeller_2011_GBC", "Groeller_2011_HP", "Groeller_2011_HSU", "Groeller_2011_IPV", "Groeller_2011_IVP", "Groeller_2011_NR", "Groeller_2011_NSM", "Groeller_2011_VCD", "Groeller_2011_VSD", "Groeller_2011_VSD", "Groeller_2011_VSD", "Groeller_2011_VSS", "Groeller_2012_KAV", "Groeller_2012_VBP", "Groeller_2012_ViV", "Groeller_2012_VV", "Groeller_2014_CaQ", "Groeller_2014_CQV", "Groeller_2014_CV", "Groeller_2014_RWA", "Groeller_2014_STC", "Groeller_2014_UPS", "Groeller_2014_VND", "Groeller_2016_I2", "Groeller_2016_I7", "Groeller_2016_I8", "Groeller_2016_P2", "Groeller_2016_P4", "Groeller_2016_P6", "Groeller_2016_P7", "Groeller_2021_11", "Groeller_2021_BVM", "Groeller_2021-10", "Groeller_Edi_2013_TVC", "Groeller_Edi_2013_VCQ", "Groeller_Edi_2013TVCK", "Groeller_Edi_VKA", "Groeller_Eduard_2014_THS", "Groeller_Eduard_2014_TSP", "Groeller_Eduard_2014_UCT", "Groeller_Eduard_2015_SMV", "Groeller_Eduard_2015_TCU", "Groeller_V1_2020", "Groeller_V2_2020", "Groeller_V3_2020", "Groeller_V42020", "Groeller_V5_2020", "groeller-2004-efficient", "groeller-2004-imp", "groeller-2004-sci", "groeller-2005-dia", "Groeller-2010-CVC", "Groeller-2010-IFI", "Groeller-2010-IVVI", "Groeller-2011-HSH", "Groeller-2017-ARTORW", "Groeller-2017-AVC", "Groeller-2017-IVAMCS", "Groeller-2017-PTPMD", "Groller_2021-12-03", "Gronde_2008", "Grorller-2010-IVV", "grossmann_2019_pelvisrunner_poster", "Grossmann_MA", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", "grossmann-thesis", "Gruenauer-2011-CAT", "Gschwantner_2011_AMQ", "gundacker-2020-wlm", "Gurbat_2011_SBS", "gusenbauer-2018", "gusenbauer-2018", "gusenbauer-2018-P", "gutekunst_2019", "Hadwiger-2002-Fas", "haidacher_2010_statTF", "haidacher-2004-FVV", 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"Schernthaner-2017-MCP", "schindler_2020vis", "Schindler-2022-eurovis", "schindler2020", "schleicher-2011-VLSC", "Schmidlehner_Sandra_SbC", "schmidlehner2021", "schmidt-2011-mt", "schmidt-phd", "schmidt-phd", "schoellhuber-2008-asc", "scholz_2021", "Schrempf_2018", "Schrempf_2020", "SCHUETZ-2023-SIMLOD", "schuh-2018-mesh-blending", "Schulze_Florian_2013_CMI", "schwankl-2013-smis", "seyfert-2017", "shakhova-2023-atp", "sietzen-2019-wnn", "sietzen-2019-wnn", "sietzen-2021-perturber", "sietzen-2022-vacnnr", "sietzen-ifv-2019", "sifuentes-2018-crowd", "SifuentesGangl2017FIS", "sikachev_peter_2010_STLCI", "sikachev_peter-2011-dfc", "sikachev_peter-2011-incshad", "sikachev_peter-2011-metavis", "sikachev_peter-2011-protovis", "sikachev-2010-DFC", "sikachev-2010-ill_vis_vol_ren", "Sippl_Sebastian_EFG", "smiech-2018-tei", "Smisek_Michal_A3D", "Sollboeck_2011_FSS", "sollboeck-2011", "Solteszova-2009-VQN", "solteszova-2010-MOS", "Solteszova2016", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "sorger-2019-odn", "sorger-2021-egonet", "Soros_AVN_2011", "Soros-AV-2010", "Spechtenhauser_Florian_2016", "spegel-gruenberger-2020", "Spelitz2020", "spoerk-2010-hpgpu", "Stabel_2012_UDM", "stappen_2017_animatedcomic", "Staudacher_2022", "staudacher_florian-2016-topo3d", "stehno-2011-RVD", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "STEINLECHNER-2019-ICT", "StickmanMax-shoetta-kampfer", "stoff-concepMap-2021", "StrakaVis2004", "stritzel2022", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "suntinger-2008-etet", "suntinger-2008-tet", "Swoboda_Nicolas_VIT", "Swoboda2020", "szabo_patrik-2022-tour", "takahashi-2019-acdt", "termeer-2006-000", "termeer-2007-covicad", "termeer-2008-scmr", "termeer-2008-vis", "termeer-2009-cvc", "termeer-2009-scmr", "textures-3d-printing", "thesis-tekaya", "Thomas-2018", "Thurner-2005-IVR", "toth-2007-ndd", "TR-186-2-05-01", "TR-186-2-05-02", "TR-186-2-05-03", "TR-186-2-05-04", "TR-186-2-05-06", "TR-186-2-05-07", "TR-186-2-05-08", "TR-186-2-06-01", "TR-186-2-06-02", "TR-186-2-06-03", "TR-186-2-06-04", "TR-186-2-07-02", "TR-186-2-07-03", "TR-186-2-07-04", "TR-186-2-07-05", "TR-186-2-07-06", "TR-186-2-07-07", "TR-186-2-07-08", "TR-186-2-07-10", "TR-186-2-07-11", "TR-186-2-07-12", "TR-186-2-08-01", "TR-186-2-08-02", "TR-186-2-08-03", "TR-186-2-08-04", "TR-186-2-08-05", "TR-186-2-08-06", "TR-186-2-08-07", "TR-186-2-08-08", "TR-186-2-08-10", "TR-186-2-08-11", "TR-186-2-08-12", "TR-186-2-08-14", "TR-186-2-09-01", "TR-186-2-15-03", "TR1862162", "Tramberger_2018", "Tramberger2017BCS", "Trautner_Thomas_2014_VAE", "trautner-2018-imd", "trautner-2018-imd", "travnicek-2017-thm", "Trenkwalder-2004-MAR", "Troidl_2019", "Troidl_2021", "Troidl_2022", "turner-aso", "tut-eg-2006", "tut-siggraph-2006", "tut-vis-2006", "tut-vis-2007", "tweebo-2014", "ulschmid-2024-reo", "unger_2017", "unger-2019_vcp", "Unger2020", "vad_2015_phd", "Vad_Viktor_2015_RVV", "vad-2016-bre", "vaico", "varchola_andrej-2012-fetoscopic", "Vasileva_2022", "Vasileva-2018", "vessel2003", "Viola_2013_IDV", "Viola_Ivan_2013_CAI", "Viola_Ivan_2013_D3D", "Viola_Ivan_2013_DC", "Viola_Ivan_2013_GS", "Viola_Ivan_2013_HQ3", "Viola_Ivan_2013_RMA", "Viola_Ivan_2013_RSb", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_DAC", "Viola_Ivan_IIP", "Viola_Ivan_UVP", "Viola_Ivan_VDP", "Viola-05-Smart", "Viola-2003-GPU", "Viola-2003-Har", "viola-2003-hbn", "Viola-2003-NON", "viola-2004-gbf", "Viola-2004-GPU", "viola-2004-har", "viola-2004-har2", "viola-2004-idv", "viola-2004-imp", "Viola-2004-ImpX", "Viola-2004-ImpX2", "viola-2005-imp", "viola-2006-FoA", "viola-evr", "Viola-Pondering-2017", "viola-popular-article-2006", "Viola-vistutillustrativevis", "vis-foa", "VisWeek-Tutorial-2012-Uncertainty", "vitruvian_2019", "voglreiter-2023-tro", "Vucenovic_2022", "vucini_2006", "vucini_2008_rnp", "vucini_2009", "vucini_erald-2007-FRI", "vucini-2009-phd", "vucini-2011", "Wagner_032017", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "Waldin_Nicholas_2017_FlickerObserver", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2017-thesis", "waldin-2019-ccm", "waldin-2019-ccm", "Waldner_2017_11", "Waldner_2017_11", "waldner-2013-facetCloudsGI", "waldner-2013-ubiWM", "waldner-2014-af", "waldner-2014-ghi", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "waser_2011_VSD", "Waser-2010-WL", "webGPU_aggregateVis-2023", "weiner_2011", "Weissenboeck_2019", "Weissenboeck_2019_PhD", "weissenboeck-2014", "Wihann_2017", "wolf-2023-cc", "Woschizka_2021", "wu-2017-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-shonan", "wu-2018-story", "wu-2019-bmc", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-smwp", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg", "wu-2021", "wu-2021-vi", "xmastree2002", "xmastree2005", "ymca", "YOGHOURDJIAN2019", "Zambal-2003-SWA", "zambal-2005-3dact", "Zaufel_2021", "zauner-2013-svkinect", "zechmeister2020", "Zeng_2021", "Zhu-2014-flowvis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Workgroup&id=vis", "__class": "Workgroup" }, { "id": "deskollage", "workgroup_id": "vis", "drupal_id": 4198, "name": "Visual Information Foraging on the Desktop", "name_de": null, "website": null, "status": "active", "short_abstract": "The goal of this project is to design and develop novel interactive visualization techniques to support knowledge workers in making sense of their unstructured, dynamic information collections. ", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. On the one hand, the studies show that, in some situations, interactive visualization can be less efficient than working with unprocessed text-based information. On the other hand, the studies also show that combining automatic data analysis with interactive visualization can lead to more unexpected findings, especially when exploring large data. The extent of manual information organization varies with the task: the less users know about the gathered information, the more automatic organization they expect. \n\nIn summary, this project contributed novel user interface concepts and design guidelines for user interfaces supporting information foraging and sensemaking. The techniques and study results were published at high-ranking peer-reviewed venues, and it can be expected that the findings of this project shape the way how users seek and organize their information in the future. \n\n", "start_date": "2015-12-01", "end_date": "2018-12-31", "leader_id": 1110, "logo": { "name": "logo.png", "path": "project:deskollage", "type": "image/png", "size": 331697, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/deskollage/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "T 752-N30", "comment": null } ], "research_areas": [ "InfoVis" ], "publications": [ "2019-ic", "byska-2019-mdfc", "casellato-2016-pkg", "cizmic-2018-evd", "donabauer-2015-asc", "dworschak-2016-szcm", "edlinger-2018-vwr", "georgiev-2019-cbg", "geymayer-2017-std", "gundacker-2020-wlm", "gusenbauer-2018", "hromniak-2019-vcn", "Koszticsak-2017-ewt", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "polatsek-2018-stv", "samoul-2019-cnp", "sietzen-2019-wnn", "sietzen-ifv-2019", "smiech-2018-tei", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "trautner-2018-imd", "unger-2019_vcp", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg" ], "url": "https://www.cg.tuwien.ac.at/research/projects/deskollage", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/polatsek-2018-stv/", "__class": "Publication" }, { "id": "Waldner_2017_11", "type_id": "talk", "tu_id": null, "repositum_id": null, "title": "Guiding Attention in Complex Visualizations using Flicker", "date": "2017-11-17", "abstract": "Drawing the user’s gaze to an important item in an image or a graphical user interface is a common challenge. Usually, some form of highlighting is used, such as a clearly distinct color or a border around the item. Flicker is also a strong visual attractor in the entire visual field, without distorting, suppressing, or adding any scene elements. While it is very salient, it is often perceived as annoying. In this talk, I will present our research on how flicker can be used as attention guidance technique in cluttered visualizations while lowering its negative side-effects. In particular, I will first present results of studies examining a two-stage flicker technique for dynamic visualizations on large displays. Then, I will present we our explorations of high frequency flicker (60 to 72 Hz) to guide the user’s attention in images. At such high frequencies, the critical flicker frequency (CFF) threshold is reached, which makes the flicker appear to fuse into a stable signal. However, the CFF is not uniform across the visual field, but is higher in the peripheral vision at normal lighting conditions. We show that high frequency flicker, using personalized attributes like patch size and luminance, can be easily detected by observers in the peripheral vision, but the signal is hardly visible in the foveal vision when users directly look at the flickering patch. We demonstrate that this property can be used to draw the user’s attention to important image regions using a standard high refresh-rate computer monitor with minimal visible modifications to the image.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "authors": [ { "id": 1110, "drupal_id": 625, "orcid_id": "0000-0003-1387-5132", "website": "https://www.cg.tuwien.ac.at/staff/ManuelaWaldner", "firstname": "Manuela", "lastname": "Waldner", "searchname": "Manuela Waldner", "is_teacher": true, "name": "Manuela Waldner", "publications": [ "2019-ic", "Alharbi_2021", "bernhard-2016-gft", "byska-2019-mdfc", "eschner-2023-evl", "eschner-2023-ims", "geymayer-2017-std", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", "indirectBiasLanguageModels-2023", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "mazurek-2018-veq", "polatsek-2018-stv", "reina-2020-mtv", "sietzen-2021-perturber", "sietzen-ifv-2019", "sMolBoxes_2022", "sorger-2019-odn", 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"wolf-2023-cc", "field_id": "supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1110", "__class": "Author" } ], "event": "S&T Cooperation Austria-Czech Republic", "location": "Czech Technical University", "research_areas": [ { "id": "IllVis", "drupal_id": 4131, "name": "Illustrative Visualization", "short_abstract": "In this research area, we develop rendering methods that are inspired by scientific illustrations, in order to make complex biological information more intuitive to understand and more pleasant to read.", "abstract": "Scientific illustration is concerned with researching ways in which complex biological and medical data can be abstracted in order to convey a desired information that would otherwise be impossible or hard to retrieve from the original data. Illustrators apply such techniques, for instance, to present non-important parts of an organ in a simplified way, while using detailed representations to put the focus of attention on a region where a tumor might be situated.\n\nTo identify such meaningful visual abstractions for visualization, their effectiveness for human perception and cognition has to be assessed, and they have to be formalized in order to make them applicable in rendering algorithms. In this project, we try to advance the understanding of procedural visual abstraction of complex physiological processes that describe the complex machinery of biological life.", "website": "https://www.cg.tuwien.ac.at/research/area/IllVis", "teaser": { "name": "teaser.jpg", "path": "research_area:IllVis", "type": "image/jpeg", "size": 34861, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/IllVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "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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"Reh_Andreas_VoP", "reh-2013", "reina-2020-mtv", "Reisacher_Matthias_CPW", "Reisacher2016", "Reiter_2009_IXIA", "Reiter2017CVAP", "Rezk06Vis", "Ribicic_2012_SUS", "Ribicic_2012_VAS", "Ribicic-2010-CRS", "Riegelnegg_2019", "rinortner_susanne-2019-vpicc", "rinortner_susanne-2019-vpicc", "Rippberger_2019", "rippl-2023-atg", "ritzberger-2010-nar", "Ropinski-2012-UBT", "rraidou_clinical", "rraidou_EG17", "rraidou_phdbook", "rsabin-2013", "ruiz-2008-OVR", "ruiz-2008-SEV", "samoul-2019-cnp", "Sanjin_Rados_RV", "Sarkis_2021", "Sbardellati-2019-vcbm", "Sbardellati-2019-vcbm", "sbardellati-2021-eveos", "scharsach-2005-adv", "Schernthaner-2017-MCP", "schindler_2020vis", "Schindler-2022-eurovis", "schindler2020", "schleicher-2011-VLSC", "Schmidlehner_Sandra_SbC", "schmidlehner2021", "schmidt-2011-mt", "schmidt-phd", "schmidt-phd", "schoellhuber-2008-asc", "scholz_2021", "Schrempf_2018", "Schrempf_2020", "SCHUETZ-2023-SIMLOD", "schuh-2018-mesh-blending", "Schulze_Florian_2013_CMI", 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"Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_DAC", "Viola_Ivan_IIP", "Viola_Ivan_UVP", "Viola_Ivan_VDP", "Viola-05-Smart", "Viola-2003-GPU", "Viola-2003-Har", "viola-2003-hbn", "Viola-2003-NON", "viola-2004-gbf", "Viola-2004-GPU", "viola-2004-har", "viola-2004-har2", "viola-2004-idv", "viola-2004-imp", "Viola-2004-ImpX", "Viola-2004-ImpX2", "viola-2005-imp", "viola-2006-FoA", "viola-evr", "Viola-Pondering-2017", "viola-popular-article-2006", "Viola-vistutillustrativevis", "vis-foa", "VisWeek-Tutorial-2012-Uncertainty", "vitruvian_2019", "voglreiter-2023-tro", "Vucenovic_2022", "vucini_2006", "vucini_2008_rnp", "vucini_2009", "vucini_erald-2007-FRI", "vucini-2009-phd", "vucini-2011", "Wagner_032017", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "Waldin_Nicholas_2017_FlickerObserver", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2017-thesis", "waldin-2019-ccm", "waldin-2019-ccm", "Waldner_2017_11", "Waldner_2017_11", "waldner-2013-facetCloudsGI", "waldner-2013-ubiWM", "waldner-2014-af", "waldner-2014-ghi", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "waser_2011_VSD", "Waser-2010-WL", "webGPU_aggregateVis-2023", "weiner_2011", "Weissenboeck_2019", "Weissenboeck_2019_PhD", "weissenboeck-2014", "Wihann_2017", "wolf-2023-cc", "Woschizka_2021", "wu-2017-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-shonan", "wu-2018-story", "wu-2019-bmc", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-smwp", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg", "wu-2021", "wu-2021-vi", "xmastree2002", "xmastree2005", "ymca", "YOGHOURDJIAN2019", "Zambal-2003-SWA", "zambal-2005-3dact", "Zaufel_2021", "zauner-2013-svkinect", "zechmeister2020", "Zeng_2021", "Zhu-2014-flowvis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Workgroup&id=vis", "__class": "Workgroup" }, { "id": "deskollage", "workgroup_id": "vis", "drupal_id": 4198, "name": "Visual Information Foraging on the Desktop", "name_de": null, "website": null, "status": "active", "short_abstract": "The goal of this project is to design and develop novel interactive visualization techniques to support knowledge workers in making sense of their unstructured, dynamic information collections. ", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. On the one hand, the studies show that, in some situations, interactive visualization can be less efficient than working with unprocessed text-based information. On the other hand, the studies also show that combining automatic data analysis with interactive visualization can lead to more unexpected findings, especially when exploring large data. The extent of manual information organization varies with the task: the less users know about the gathered information, the more automatic organization they expect. \n\nIn summary, this project contributed novel user interface concepts and design guidelines for user interfaces supporting information foraging and sensemaking. The techniques and study results were published at high-ranking peer-reviewed venues, and it can be expected that the findings of this project shape the way how users seek and organize their information in the future. \n\n", "start_date": "2015-12-01", "end_date": "2018-12-31", "leader_id": 1110, "logo": { "name": "logo.png", "path": "project:deskollage", "type": "image/png", "size": 331697, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/deskollage/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "T 752-N30", "comment": null } ], "research_areas": [ "InfoVis" ], "publications": [ "2019-ic", "byska-2019-mdfc", "casellato-2016-pkg", "cizmic-2018-evd", "donabauer-2015-asc", "dworschak-2016-szcm", "edlinger-2018-vwr", "georgiev-2019-cbg", "geymayer-2017-std", "gundacker-2020-wlm", "gusenbauer-2018", "hromniak-2019-vcn", "Koszticsak-2017-ewt", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "polatsek-2018-stv", "samoul-2019-cnp", "sietzen-2019-wnn", "sietzen-ifv-2019", "smiech-2018-tei", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "trautner-2018-imd", "unger-2019_vcp", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg" ], "url": "https://www.cg.tuwien.ac.at/research/projects/deskollage", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2017/Waldner_2017_11/", "__class": "Publication" }, { "id": "geymayer-2017-std", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "How Sensemaking Tools Influence Display Space Usage", "date": "2017-06", "abstract": "We explore how the availability of a sensemaking tool influences users’ knowledge externalization strategies. On a large display,\nusers were asked to solve an intelligence analysis task with or without a bidirectionally linked concept-graph (BLC) to organize\ninsights into concepts (nodes) and relations (edges). In BLC, both nodes and edges maintain “deep links” to the exact source\nphrases and sections in associated documents. In our control condition, we were able to reproduce previously described spatial\norganization behaviors using document windows on the large display. When using BLC, however, we found that analysts apply\nspatial organization to BLC nodes instead, use significantly less display space and have significantly fewer open windows.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 805, "image_height": 344, "name": "geymayer-2017-std-image.PNG", "type": "image/png", "size": 604999, "path": "Publication:geymayer-2017-std", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/geymayer-2017-std/geymayer-2017-std-image.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/geymayer-2017-std/geymayer-2017-std-image:thumb{{size}}.png" }, "sync_repositum_override": null, "authors": [ { "id": 1477, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Thomas", "lastname": "Geymayer", "searchname": "Thomas Geymayer", 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"status": "active", "short_abstract": "The goal of this project is to design and develop novel interactive visualization techniques to support knowledge workers in making sense of their unstructured, dynamic information collections. ", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. On the one hand, the studies show that, in some situations, interactive visualization can be less efficient than working with unprocessed text-based information. On the other hand, the studies also show that combining automatic data analysis with interactive visualization can lead to more unexpected findings, especially when exploring large data. The extent of manual information organization varies with the task: the less users know about the gathered information, the more automatic organization they expect. \n\nIn summary, this project contributed novel user interface concepts and design guidelines for user interfaces supporting information foraging and sensemaking. The techniques and study results were published at high-ranking peer-reviewed venues, and it can be expected that the findings of this project shape the way how users seek and organize their information in the future. \n\n", "start_date": "2015-12-01", "end_date": "2018-12-31", "leader_id": 1110, "logo": { "name": "logo.png", "path": "project:deskollage", "type": "image/png", "size": 331697, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/deskollage/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "T 752-N30", "comment": null } ], "research_areas": [ "InfoVis" ], "publications": [ "2019-ic", "byska-2019-mdfc", "casellato-2016-pkg", "cizmic-2018-evd", "donabauer-2015-asc", "dworschak-2016-szcm", "edlinger-2018-vwr", "georgiev-2019-cbg", "geymayer-2017-std", "gundacker-2020-wlm", "gusenbauer-2018", "hromniak-2019-vcn", "Koszticsak-2017-ewt", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "polatsek-2018-stv", "samoul-2019-cnp", "sietzen-2019-wnn", "sietzen-ifv-2019", "smiech-2018-tei", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "trautner-2018-imd", "unger-2019_vcp", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg" ], "url": "https://www.cg.tuwien.ac.at/research/projects/deskollage", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2017/geymayer-2017-std/", "__class": "Publication" }, { "id": "Waldin_Nicholas_2017_FlickerObserver", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "Flicker Observer Effect: Guiding Attention Through High Frequency Flicker in Images", "date": "2017-05", "abstract": "Drawing the user's gaze to an important item in an image or a graphical user interface is a common challenge. Usually, some form of highlighting is used, such as a clearly distinct color or a border around the item. Flicker can also be very salient, but is often perceived as annoying. In this paper, we explore high frequency flicker (60 to 72 Hz) to guide the user's attention in an image. At such high frequencies, the critical flicker frequency (CFF) threshold is reached, which makes the flicker appear to fuse into a stable signal. However, the CFF is not uniform across the visual field, but is higher in the peripheral vision at normal lighting conditions. Through experiments, we show that high frequency flicker can be easily detected by observers in the peripheral vision, but the signal is hardly visible in the foveal vision when users directly look at the flickering patch. We demonstrate that this property can be used to draw the user's attention to important image regions using a standard high refresh-rate computer monitor with minimal visible modifications to the image. In an uncalibrated visual search task, users could in a crowded image easily spot the specified search targets flickering with very high frequency. They also reported that high frequency flicker was distracting when they had to attend to another region, while it was hardly noticeable when looking at the flickering region itself.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "authors": [ { "id": 1461, "drupal_id": 1003, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/NicholasWaldin", "firstname": "Nicholas", "lastname": "Waldin", "searchname": "Nicholas Waldin", "is_teacher": false, "name": "Nicholas Waldin", "publications": [ "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2016_Colormaps", "Waldin_Nicholas_2016_Individualization", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2017-thesis" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1461", "__class": "Author" }, { "id": 1110, "drupal_id": 625, "orcid_id": "0000-0003-1387-5132", "website": 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By understanding the limits of human perception, we can design and optimize rendering algorithms that perfectly fit users' needs, tailor visualizations to make data better understandable, and effectively draw the user's attention to important information.
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"termeer-2007-covicad", "termeer-2008-scmr", "termeer-2008-vis", "termeer-2009-cvc", "termeer-2009-scmr", "textures-3d-printing", "thesis-tekaya", "Thomas-2018", "Thurner-2005-IVR", "toth-2007-ndd", "TR-186-2-05-01", "TR-186-2-05-02", "TR-186-2-05-03", "TR-186-2-05-04", "TR-186-2-05-06", "TR-186-2-05-07", "TR-186-2-05-08", "TR-186-2-06-01", "TR-186-2-06-02", "TR-186-2-06-03", "TR-186-2-06-04", "TR-186-2-07-02", "TR-186-2-07-03", "TR-186-2-07-04", "TR-186-2-07-05", "TR-186-2-07-06", "TR-186-2-07-07", "TR-186-2-07-08", "TR-186-2-07-10", "TR-186-2-07-11", "TR-186-2-07-12", "TR-186-2-08-01", "TR-186-2-08-02", "TR-186-2-08-03", "TR-186-2-08-04", "TR-186-2-08-05", "TR-186-2-08-06", "TR-186-2-08-07", "TR-186-2-08-08", "TR-186-2-08-10", "TR-186-2-08-11", "TR-186-2-08-12", "TR-186-2-08-14", "TR-186-2-09-01", "TR-186-2-15-03", "TR1862162", "Tramberger_2018", "Tramberger2017BCS", "Trautner_Thomas_2014_VAE", "trautner-2018-imd", "trautner-2018-imd", "travnicek-2017-thm", "Trenkwalder-2004-MAR", "Troidl_2019", "Troidl_2021", "Troidl_2022", "turner-aso", "tut-eg-2006", "tut-siggraph-2006", "tut-vis-2006", "tut-vis-2007", "tweebo-2014", "ulschmid-2024-reo", "unger_2017", "unger-2019_vcp", "Unger2020", "vad_2015_phd", "Vad_Viktor_2015_RVV", "vad-2016-bre", "vaico", "varchola_andrej-2012-fetoscopic", "Vasileva_2022", "Vasileva-2018", "vessel2003", "Viola_2013_IDV", "Viola_Ivan_2013_CAI", "Viola_Ivan_2013_D3D", "Viola_Ivan_2013_DC", "Viola_Ivan_2013_GS", "Viola_Ivan_2013_HQ3", "Viola_Ivan_2013_RMA", "Viola_Ivan_2013_RSb", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_DAC", "Viola_Ivan_IIP", "Viola_Ivan_UVP", "Viola_Ivan_VDP", "Viola-05-Smart", "Viola-2003-GPU", "Viola-2003-Har", "viola-2003-hbn", "Viola-2003-NON", "viola-2004-gbf", "Viola-2004-GPU", "viola-2004-har", "viola-2004-har2", "viola-2004-idv", "viola-2004-imp", "Viola-2004-ImpX", "Viola-2004-ImpX2", "viola-2005-imp", "viola-2006-FoA", "viola-evr", "Viola-Pondering-2017", "viola-popular-article-2006", "Viola-vistutillustrativevis", "vis-foa", "VisWeek-Tutorial-2012-Uncertainty", "vitruvian_2019", "voglreiter-2023-tro", "Vucenovic_2022", "vucini_2006", "vucini_2008_rnp", "vucini_2009", "vucini_erald-2007-FRI", "vucini-2009-phd", "vucini-2011", "Wagner_032017", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "Waldin_Nicholas_2017_FlickerObserver", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2017-thesis", "waldin-2019-ccm", "waldin-2019-ccm", "Waldner_2017_11", "Waldner_2017_11", "waldner-2013-facetCloudsGI", "waldner-2013-ubiWM", "waldner-2014-af", "waldner-2014-ghi", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "waser_2011_VSD", "Waser-2010-WL", "webGPU_aggregateVis-2023", "weiner_2011", "Weissenboeck_2019", "Weissenboeck_2019_PhD", "weissenboeck-2014", "Wihann_2017", "wolf-2023-cc", "Woschizka_2021", "wu-2017-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-shonan", "wu-2018-story", "wu-2019-bmc", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-smwp", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg", "wu-2021", "wu-2021-vi", "xmastree2002", "xmastree2005", "ymca", "YOGHOURDJIAN2019", "Zambal-2003-SWA", "zambal-2005-3dact", "Zaufel_2021", "zauner-2013-svkinect", "zechmeister2020", "Zeng_2021", "Zhu-2014-flowvis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Workgroup&id=vis", "__class": "Workgroup" }, { "id": "deskollage", "workgroup_id": "vis", "drupal_id": 4198, "name": "Visual Information Foraging on the Desktop", "name_de": null, "website": null, "status": "active", "short_abstract": "The goal of this project is to design and develop novel interactive visualization techniques to support knowledge workers in making sense of their unstructured, dynamic information collections. ", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. On the one hand, the studies show that, in some situations, interactive visualization can be less efficient than working with unprocessed text-based information. On the other hand, the studies also show that combining automatic data analysis with interactive visualization can lead to more unexpected findings, especially when exploring large data. The extent of manual information organization varies with the task: the less users know about the gathered information, the more automatic organization they expect. \n\nIn summary, this project contributed novel user interface concepts and design guidelines for user interfaces supporting information foraging and sensemaking. The techniques and study results were published at high-ranking peer-reviewed venues, and it can be expected that the findings of this project shape the way how users seek and organize their information in the future. \n\n", "start_date": "2015-12-01", "end_date": "2018-12-31", "leader_id": 1110, "logo": { "name": "logo.png", "path": "project:deskollage", "type": "image/png", "size": 331697, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/deskollage/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "T 752-N30", "comment": null } ], "research_areas": [ "InfoVis" ], "publications": [ "2019-ic", "byska-2019-mdfc", "casellato-2016-pkg", "cizmic-2018-evd", "donabauer-2015-asc", "dworschak-2016-szcm", "edlinger-2018-vwr", "georgiev-2019-cbg", "geymayer-2017-std", "gundacker-2020-wlm", "gusenbauer-2018", "hromniak-2019-vcn", "Koszticsak-2017-ewt", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "polatsek-2018-stv", "samoul-2019-cnp", "sietzen-2019-wnn", "sietzen-ifv-2019", "smiech-2018-tei", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "trautner-2018-imd", "unger-2019_vcp", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg" ], "url": "https://www.cg.tuwien.ac.at/research/projects/deskollage", "__class": "Project" }, { "id": "illvisation", "workgroup_id": "vis", "drupal_id": 4171, "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" }, { "id": "Perception", "drupal_id": 4136, "name": "Perception", "short_abstract": "In this area, our research focuses on understanding and using the capabilities of human perception for designing high-quality graphics algorithms and effective visualizations.", "abstract": "In computer graphics we produce images, videos, visualizations and other content that is perceived by humans. By understanding the limits of human perception, we can design and optimize rendering algorithms that perfectly fit users' needs, tailor visualizations to make data better understandable, and effectively draw the user's attention to important information.
\r\n", "website": "https://www.cg.tuwien.ac.at/research/area/Perception", "teaser": { "name": "teaser.PNG", "path": "research_area:Perception", "type": "image/png", "size": 259428, "orig_name": "teaser.PNG", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/Perception/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "rend", "vis" ], "publications": [ "bernhard-2011-maicg", "bernhard-2014-EFD", "bernhard-2014-GTOM", "bernhard-2016-gft", "birkeland_aasmund_2014_pums", "cardoso-2022-rtpercept", "ERLER-2017-HVR", "eschner-2023-ims", "eschner-blur-2022", "georgiev-2019-cbg", "Groeller_2016_P7", "grossmann-2021-layout", "hecher-2012-MH", "hecher-2014-MH", "HECHER-2017-HDY", "huerbe-2019-BA", "Kathi-2018-VRB", "koch-2019-PR", "Koszticsak-2017-ewt", "KREUZER-2017-PBF", "kristmann-2022-occ", "kroesl-2018-DC", "kroesl-2018-TVS", "kroesl-2019-ICthroughVR", "kroesl-2019-ThesisFF", "kroesl-2020-XREye", "Laschober-2018", "Luidolt-2020-DA", "luidolt-2020-lightperceptionVR", "mayr-2021-wec", "mindek-2017-dsn", "panfili-2019-VAVR", "panfili-2021-myop", "plank-2017-sldg", "polatsek-2018-stv", "Reichinger-2016-spaghetti", "schindler_2020vis", "schuller_reichl-2019-avt", "Semmelrath-2022-IRS", "stappen_SteFAS", "steinkellner-2022-dll", "sundstedt-2013-vag", "trautner-2018-imd", "Vasylevska_Khrystyna-2019-TEFVR", "viola-evr", "Waldin_Nicholas_2016_Colormaps", "Waldin_Nicholas_2016_Individualization", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2017-thesis", "waldner-2013-facetCloudsGI", "waldner-2014-af", "waldner-2017-vph", "waldner-2019-rld" ], "projects": [ "CROSSMOD" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=Perception", "__class": "ResearchArea" } ], "keywords": [ "information visualization", "highlighting", "focus+context", "visual prominence" ], "weblinks": [], "files": [ { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 160, "image_height": 124, "name": "waldner-2017-vph-.png", "type": "image/png", "size": 20447, "path": "Publication:waldner-2017-vph", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/waldner-2017-vph/waldner-2017-vph-.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/waldner-2017-vph/waldner-2017-vph-:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "waldner-2017-vph-paper.pdf", "type": "application/pdf", "size": 1851221, "path": "Publication:waldner-2017-vph", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/waldner-2017-vph/waldner-2017-vph-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/waldner-2017-vph/waldner-2017-vph-paper:thumb{{size}}.png" }, { "description": "Details about experiment design and results. ", "filetitle": "supplemental material", "main_file": false, "use_in_gallery": false, "access": "public", "name": "waldner-2017-vph-supplemental material.pdf", "type": "application/pdf", "size": 1396255, "path": "Publication:waldner-2017-vph", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/waldner-2017-vph/waldner-2017-vph-supplemental material.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/waldner-2017-vph/waldner-2017-vph-supplemental material:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "deskollage", "workgroup_id": "vis", "drupal_id": 4198, "name": "Visual Information Foraging on the Desktop", "name_de": null, "website": null, "status": "active", "short_abstract": "The goal of this project is to design and develop novel interactive visualization techniques to support knowledge workers in making sense of their unstructured, dynamic information collections. ", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. On the one hand, the studies show that, in some situations, interactive visualization can be less efficient than working with unprocessed text-based information. On the other hand, the studies also show that combining automatic data analysis with interactive visualization can lead to more unexpected findings, especially when exploring large data. The extent of manual information organization varies with the task: the less users know about the gathered information, the more automatic organization they expect. \n\nIn summary, this project contributed novel user interface concepts and design guidelines for user interfaces supporting information foraging and sensemaking. The techniques and study results were published at high-ranking peer-reviewed venues, and it can be expected that the findings of this project shape the way how users seek and organize their information in the future. \n\n", "start_date": "2015-12-01", "end_date": "2018-12-31", "leader_id": 1110, "logo": { "name": "logo.png", "path": "project:deskollage", "type": "image/png", "size": 331697, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/deskollage/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "T 752-N30", "comment": null } ], "research_areas": [ "InfoVis" ], "publications": [ "2019-ic", "byska-2019-mdfc", "casellato-2016-pkg", "cizmic-2018-evd", "donabauer-2015-asc", "dworschak-2016-szcm", "edlinger-2018-vwr", "georgiev-2019-cbg", "geymayer-2017-std", "gundacker-2020-wlm", "gusenbauer-2018", "hromniak-2019-vcn", "Koszticsak-2017-ewt", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "polatsek-2018-stv", "samoul-2019-cnp", "sietzen-2019-wnn", "sietzen-ifv-2019", "smiech-2018-tei", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "trautner-2018-imd", "unger-2019_vcp", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg" ], "url": "https://www.cg.tuwien.ac.at/research/projects/deskollage", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2017/waldner-2017-vph/", "__class": "Publication" }, { "id": "Koszticsak-2017-ewt", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Generating Expressive Window Thumbnails through Seam Carving", "date": "2017", "abstract": "Thumbnails are used to display lists of open windows or tabs when switching between\nthem on computers and on mobile devices. These images make it easier to recognize the\nopened applications, and help to find the needed window quicker. Thumbnails however\nonly display a screenshot of the windows, so they get potentially confusing if there are\nmore opened windows or if the same application is opened multiple times. Depending\non the resolution of the display, the screenshot size decreases as the number of opened\nwindows increases. Furthermore, within the same application (like MS Office World)\nthe screenshots are similar in appearance (e.g. : white paper and tool bar), but the\nimportant text is not readable. There are several approaches that filter the important\nareas of the images to enhance the main region. In this bachelor thesis an application is\nimplemented that uses the above methods on screenshots. Screenshots of windows are\nreduced by cropping the irrelevant elements of the margin area using seam carving, i.e.\nby eliminating the non-important pixel paths; and by common down-sampling. As a\nresult the thumbnails show only relevant information, which makes them more expressive\nand easier to fulfill their purpose.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 858, "image_height": 481, "name": "Koszticsak-2017-ewt-.png", "type": "image/png", "size": 397429, "path": "Publication:Koszticsak-2017-ewt", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/Koszticsak-2017-ewt/Koszticsak-2017-ewt-.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/Koszticsak-2017-ewt/Koszticsak-2017-ewt-:thumb{{size}}.png" }, "sync_repositum_override": null, "authors": [ { "id": 1351, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Rebeka", "lastname": "Koszticsak", "searchname": "Rebeka Koszticsak", "is_teacher": false, "name": "Rebeka Koszticsak", "publications": [ "Koszticsak-2017-ewt" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1351", "__class": "Author" } ], "date_end": "2017-02", "date_start": "2016-06", "duration": "10 months", "matrikelnr": "1325492", "supervisor": [ { "id": 1110, "drupal_id": 625, "orcid_id": "0000-0003-1387-5132", "website": "https://www.cg.tuwien.ac.at/staff/ManuelaWaldner", "firstname": "Manuela", "lastname": "Waldner", "searchname": "Manuela Waldner", "is_teacher": true, "name": "Manuela Waldner", "publications": [ "2019-ic", "Alharbi_2021", "bernhard-2016-gft", "byska-2019-mdfc", "eschner-2023-evl", "eschner-2023-ims", "geymayer-2017-std", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", "indirectBiasLanguageModels-2023", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "mazurek-2018-veq", "polatsek-2018-stv", "reina-2020-mtv", "sietzen-2021-perturber", "sietzen-ifv-2019", "sMolBoxes_2022", "sorger-2019-odn", "sorger-2021-egonet", "steinboeck-2018-lbg", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2013-facetCloudsGI", "waldner-2013-ubiWM", "waldner-2014-af", "waldner-2014-ghi", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "webGPU_aggregateVis-2023", "wu-2021", "wu-2021-vi" ], "publications_first": [], "project_leader": [ "d9282", "d9522", "d9555", "deskollage" ], "publication_field": [ { "publ_id": "arbesser_ba_2023", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "bayat-2022-mva", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "boesch_2014_browserHistoryVis", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "breitenecker-2020-bct", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "bugnar-esk-2021", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "casellato-2016-pkg", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "cizmic-2018-evd", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "da_cunha_melo-2023-c3m", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "donabauer-2015-asc", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "dworschak-2016-szcm", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "edlinger-2018-vwr", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "eiweck-hnv-2021", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "eschner-2023-rar", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "eschner-blur-2022", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "georgiev-2019-cbg", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Gogel2020", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "grammatikaki-thesis", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "grossmann-2021-layout", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "gundacker-2020-wlm", 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1 }, { "publ_id": "mazurek-2017-sio", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "mazurek-2017-vows", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "mazurek-2018-vac", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Panayotov", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Presch_2020", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "samoul-2019-cnp", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "sbardellati-2021-eveos", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "sietzen-2019-wnn", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "sietzen-2022-vacnnr", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "smiech-2018-tei", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "spegel-gruenberger-2020", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "staats-2024-atr", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "steinboeck-2017-vbn", "field_id": "supervisor", "ordernum": 1 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"publ_id": "wolf-2023-cc", "field_id": "supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1110", "__class": "Author" } ], "research_areas": [ { "id": "IllVis", "drupal_id": 4131, "name": "Illustrative Visualization", "short_abstract": "In this research area, we develop rendering methods that are inspired by scientific illustrations, in order to make complex biological information more intuitive to understand and more pleasant to read.", "abstract": "Scientific illustration is concerned with researching ways in which complex biological and medical data can be abstracted in order to convey a desired information that would otherwise be impossible or hard to retrieve from the original data. Illustrators apply such techniques, for instance, to present non-important parts of an organ in a simplified way, while using detailed representations to put the focus of attention on a region where a tumor might be situated.\n\nTo identify such meaningful visual abstractions for visualization, their effectiveness for human perception and cognition has to be assessed, and they have to be formalized in order to make them applicable in rendering algorithms. In this project, we try to advance the understanding of procedural visual abstraction of complex physiological processes that describe the complex machinery of biological life.", "website": "https://www.cg.tuwien.ac.at/research/area/IllVis", "teaser": { "name": "teaser.jpg", "path": "research_area:IllVis", "type": "image/jpeg", "size": 34861, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/IllVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "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": "Perception", "drupal_id": 4136, "name": "Perception", "short_abstract": "In this area, our research focuses on understanding and using the capabilities of human perception for designing high-quality graphics algorithms and effective visualizations.", "abstract": "In computer graphics we produce images, videos, visualizations and other content that is perceived by humans. By understanding the limits of human perception, we can design and optimize rendering algorithms that perfectly fit users' needs, tailor visualizations to make data better understandable, and effectively draw the user's attention to important information.
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", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. On the one hand, the studies show that, in some situations, interactive visualization can be less efficient than working with unprocessed text-based information. On the other hand, the studies also show that combining automatic data analysis with interactive visualization can lead to more unexpected findings, especially when exploring large data. The extent of manual information organization varies with the task: the less users know about the gathered information, the more automatic organization they expect. \n\nIn summary, this project contributed novel user interface concepts and design guidelines for user interfaces supporting information foraging and sensemaking. 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The data\nof these programmes, containing information about projects, corresponding topics,\nfunding sums, funding periods and recipient countries, is publicly available, but hard\nto analyze without visual support. Therefore, a multiple coordinated view approach is developed in course of this project. The different visualization techniques used, like bar charts, treemap, choropleth map and line graph, make it possible to filter, analyze and further explore the available data through brushing and linking. 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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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"Reisacher_Matthias_CPW", "Reisacher2016", "Reiter_2009_IXIA", "Reiter2017CVAP", "Rezk06Vis", "Ribicic_2012_SUS", "Ribicic_2012_VAS", "Ribicic-2010-CRS", "Riegelnegg_2019", "rinortner_susanne-2019-vpicc", "rinortner_susanne-2019-vpicc", "Rippberger_2019", "rippl-2023-atg", "ritzberger-2010-nar", "Ropinski-2012-UBT", "rraidou_clinical", "rraidou_EG17", "rraidou_phdbook", "rsabin-2013", "ruiz-2008-OVR", "ruiz-2008-SEV", "samoul-2019-cnp", "Sanjin_Rados_RV", "Sarkis_2021", "Sbardellati-2019-vcbm", "Sbardellati-2019-vcbm", "sbardellati-2021-eveos", "scharsach-2005-adv", "Schernthaner-2017-MCP", "schindler_2020vis", "Schindler-2022-eurovis", "schindler2020", "schleicher-2011-VLSC", "Schmidlehner_Sandra_SbC", "schmidlehner2021", "schmidt-2011-mt", "schmidt-phd", "schmidt-phd", "schoellhuber-2008-asc", "scholz_2021", "Schrempf_2018", "Schrempf_2020", "SCHUETZ-2023-SIMLOD", "schuh-2018-mesh-blending", "Schulze_Florian_2013_CMI", "schwankl-2013-smis", "seyfert-2017", "shakhova-2023-atp", "sietzen-2019-wnn", "sietzen-2019-wnn", "sietzen-2021-perturber", "sietzen-2022-vacnnr", "sietzen-ifv-2019", "sifuentes-2018-crowd", "SifuentesGangl2017FIS", "sikachev_peter_2010_STLCI", "sikachev_peter-2011-dfc", "sikachev_peter-2011-incshad", "sikachev_peter-2011-metavis", "sikachev_peter-2011-protovis", "sikachev-2010-DFC", "sikachev-2010-ill_vis_vol_ren", "Sippl_Sebastian_EFG", "smiech-2018-tei", "Smisek_Michal_A3D", "Sollboeck_2011_FSS", "sollboeck-2011", "Solteszova-2009-VQN", "solteszova-2010-MOS", "Solteszova2016", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "sorger-2019-odn", "sorger-2021-egonet", "Soros_AVN_2011", "Soros-AV-2010", "Spechtenhauser_Florian_2016", "spegel-gruenberger-2020", "Spelitz2020", "spoerk-2010-hpgpu", "Stabel_2012_UDM", "stappen_2017_animatedcomic", "Staudacher_2022", "staudacher_florian-2016-topo3d", "stehno-2011-RVD", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "STEINLECHNER-2019-ICT", "StickmanMax-shoetta-kampfer", "stoff-concepMap-2021", "StrakaVis2004", "stritzel2022", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "suntinger-2008-etet", "suntinger-2008-tet", "Swoboda_Nicolas_VIT", "Swoboda2020", "szabo_patrik-2022-tour", "takahashi-2019-acdt", "termeer-2006-000", "termeer-2007-covicad", "termeer-2008-scmr", "termeer-2008-vis", "termeer-2009-cvc", "termeer-2009-scmr", "textures-3d-printing", "thesis-tekaya", "Thomas-2018", "Thurner-2005-IVR", "toth-2007-ndd", "TR-186-2-05-01", "TR-186-2-05-02", "TR-186-2-05-03", "TR-186-2-05-04", "TR-186-2-05-06", "TR-186-2-05-07", "TR-186-2-05-08", "TR-186-2-06-01", "TR-186-2-06-02", "TR-186-2-06-03", "TR-186-2-06-04", "TR-186-2-07-02", "TR-186-2-07-03", "TR-186-2-07-04", "TR-186-2-07-05", "TR-186-2-07-06", "TR-186-2-07-07", "TR-186-2-07-08", "TR-186-2-07-10", "TR-186-2-07-11", "TR-186-2-07-12", "TR-186-2-08-01", "TR-186-2-08-02", "TR-186-2-08-03", "TR-186-2-08-04", "TR-186-2-08-05", "TR-186-2-08-06", "TR-186-2-08-07", "TR-186-2-08-08", "TR-186-2-08-10", "TR-186-2-08-11", "TR-186-2-08-12", "TR-186-2-08-14", "TR-186-2-09-01", "TR-186-2-15-03", "TR1862162", "Tramberger_2018", "Tramberger2017BCS", "Trautner_Thomas_2014_VAE", "trautner-2018-imd", "trautner-2018-imd", "travnicek-2017-thm", "Trenkwalder-2004-MAR", "Troidl_2019", "Troidl_2021", "Troidl_2022", "turner-aso", "tut-eg-2006", "tut-siggraph-2006", "tut-vis-2006", "tut-vis-2007", "tweebo-2014", "ulschmid-2024-reo", "unger_2017", "unger-2019_vcp", "Unger2020", "vad_2015_phd", "Vad_Viktor_2015_RVV", "vad-2016-bre", "vaico", "varchola_andrej-2012-fetoscopic", "Vasileva_2022", "Vasileva-2018", "vessel2003", "Viola_2013_IDV", "Viola_Ivan_2013_CAI", "Viola_Ivan_2013_D3D", "Viola_Ivan_2013_DC", "Viola_Ivan_2013_GS", "Viola_Ivan_2013_HQ3", "Viola_Ivan_2013_RMA", "Viola_Ivan_2013_RSb", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_DAC", "Viola_Ivan_IIP", "Viola_Ivan_UVP", "Viola_Ivan_VDP", "Viola-05-Smart", "Viola-2003-GPU", "Viola-2003-Har", "viola-2003-hbn", "Viola-2003-NON", "viola-2004-gbf", "Viola-2004-GPU", "viola-2004-har", "viola-2004-har2", "viola-2004-idv", "viola-2004-imp", "Viola-2004-ImpX", "Viola-2004-ImpX2", "viola-2005-imp", "viola-2006-FoA", "viola-evr", "Viola-Pondering-2017", "viola-popular-article-2006", "Viola-vistutillustrativevis", "vis-foa", "VisWeek-Tutorial-2012-Uncertainty", "vitruvian_2019", "voglreiter-2023-tro", "Vucenovic_2022", "vucini_2006", "vucini_2008_rnp", "vucini_2009", "vucini_erald-2007-FRI", "vucini-2009-phd", "vucini-2011", "Wagner_032017", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "Waldin_Nicholas_2017_FlickerObserver", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2017-thesis", "waldin-2019-ccm", "waldin-2019-ccm", "Waldner_2017_11", "Waldner_2017_11", "waldner-2013-facetCloudsGI", "waldner-2013-ubiWM", "waldner-2014-af", "waldner-2014-ghi", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "waser_2011_VSD", "Waser-2010-WL", "webGPU_aggregateVis-2023", "weiner_2011", "Weissenboeck_2019", "Weissenboeck_2019_PhD", "weissenboeck-2014", "Wihann_2017", "wolf-2023-cc", "Woschizka_2021", "wu-2017-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-shonan", "wu-2018-story", "wu-2019-bmc", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-smwp", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg", "wu-2021", "wu-2021-vi", "xmastree2002", "xmastree2005", "ymca", "YOGHOURDJIAN2019", "Zambal-2003-SWA", "zambal-2005-3dact", "Zaufel_2021", "zauner-2013-svkinect", "zechmeister2020", "Zeng_2021", "Zhu-2014-flowvis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Workgroup&id=vis", "__class": "Workgroup" }, { "id": "deskollage", "workgroup_id": "vis", "drupal_id": 4198, "name": "Visual Information Foraging on the Desktop", "name_de": null, "website": null, "status": "active", "short_abstract": "The goal of this project is to design and develop novel interactive visualization techniques to support knowledge workers in making sense of their unstructured, dynamic information collections. ", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. On the one hand, the studies show that, in some situations, interactive visualization can be less efficient than working with unprocessed text-based information. On the other hand, the studies also show that combining automatic data analysis with interactive visualization can lead to more unexpected findings, especially when exploring large data. The extent of manual information organization varies with the task: the less users know about the gathered information, the more automatic organization they expect. \n\nIn summary, this project contributed novel user interface concepts and design guidelines for user interfaces supporting information foraging and sensemaking. The techniques and study results were published at high-ranking peer-reviewed venues, and it can be expected that the findings of this project shape the way how users seek and organize their information in the future. \n\n", "start_date": "2015-12-01", "end_date": "2018-12-31", "leader_id": 1110, "logo": { "name": "logo.png", "path": "project:deskollage", "type": "image/png", "size": 331697, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/deskollage/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "T 752-N30", "comment": null } ], "research_areas": [ "InfoVis" ], "publications": [ "2019-ic", "byska-2019-mdfc", "casellato-2016-pkg", "cizmic-2018-evd", "donabauer-2015-asc", "dworschak-2016-szcm", "edlinger-2018-vwr", "georgiev-2019-cbg", "geymayer-2017-std", "gundacker-2020-wlm", "gusenbauer-2018", "hromniak-2019-vcn", "Koszticsak-2017-ewt", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "polatsek-2018-stv", "samoul-2019-cnp", "sietzen-2019-wnn", "sietzen-ifv-2019", "smiech-2018-tei", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "trautner-2018-imd", "unger-2019_vcp", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg" ], "url": "https://www.cg.tuwien.ac.at/research/projects/deskollage", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2017/steinboeck-2017-vefp/", "__class": "Publication" }, { "id": "mazurek-2017-vows", "type_id": "studentproject", "tu_id": null, "repositum_id": null, "title": "Visualization of Thesaurus-Based Web Search", "date": "2017", "abstract": "The general functions of current web search engines are well established. A box is\nprovided in which to type the queries and the engine returns a result list which users can\nevaluate. The autocomplete suggestions assist users in defining their problems, however\nthere is a lack of support for an iterative manual refinement of the query. This additional\naid can be beneficial when users not know the exact terms to describe the concept they\nare looking for. Therefore, the goal of this project is to show searchers how a slight\nvariation of the query changes the results. With this information, they then can perform\na targeted refinement of the query to access useful information sources. To achieve this\ngoal, each part of the searcher’s query is varied with a thesaurus that provides synonyms\nfor the individual query terms. While performing the user’s original query in a normal\nfashion, variations of this query are conducted in the background. To provide a concise\nvisual summary of the query results, text mining techniques are performed on all gathered\nresults to retrieve the most important key terms for each query variation. This procedure\nresults in a visual overview of what the searcher’s query finds together with what could\nbe found with a slight variation of the query. Additional queries should make users aware\nthat alternative queries may be more appropriate when their original query is poorly\nformulated. In conjunction with some interaction tools, the goal is to reduce the burden\nof refining search queries and therefore making searching the web less complex.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 814, "image_height": 539, "name": "mazurek-2017-vows-teaser.PNG", "type": "image/png", "size": 405860, "path": "Publication:mazurek-2017-vows", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/mazurek-2017-vows/mazurek-2017-vows-teaser.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/mazurek-2017-vows/mazurek-2017-vows-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "authors": [ { "id": 1364, "drupal_id": 1285, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/MichaelMazurek", "firstname": "Michael", "lastname": "Mazurek", "searchname": "Michael Mazurek", "is_teacher": false, "name": "Michael Mazurek", "publications": [ "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "mazurek-2018-veq", "field_id": "lecturer", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1364", "__class": "Author" } ], "date_end": "2017-10", "date_start": "2017-08", "matrikelnr": "1126483", "supervisor": [ { "id": 1110, "drupal_id": 625, "orcid_id": "0000-0003-1387-5132", "website": "https://www.cg.tuwien.ac.at/staff/ManuelaWaldner", "firstname": "Manuela", "lastname": "Waldner", "searchname": "Manuela Waldner", "is_teacher": true, "name": "Manuela Waldner", "publications": [ "2019-ic", "Alharbi_2021", "bernhard-2016-gft", "byska-2019-mdfc", "eschner-2023-evl", "eschner-2023-ims", "geymayer-2017-std", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", 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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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"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": [], "files": [ { "description": null, "filetitle": "report", "main_file": false, "use_in_gallery": false, "access": "public", "name": "mazurek-2017-vows-report.pdf", "type": "application/pdf", "size": 540973, "path": "Publication:mazurek-2017-vows", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/mazurek-2017-vows/mazurek-2017-vows-report.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/mazurek-2017-vows/mazurek-2017-vows-report:thumb{{size}}.png" }, { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 814, "image_height": 539, "name": "mazurek-2017-vows-teaser.PNG", "type": "image/png", "size": 405860, "path": "Publication:mazurek-2017-vows", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/mazurek-2017-vows/mazurek-2017-vows-teaser.PNG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/mazurek-2017-vows/mazurek-2017-vows-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "deskollage", "workgroup_id": "vis", "drupal_id": 4198, "name": "Visual Information Foraging on the Desktop", "name_de": null, "website": null, "status": "active", "short_abstract": "The goal of this project is to design and develop novel interactive visualization techniques to support knowledge workers in making sense of their unstructured, dynamic information collections. ", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. On the one hand, the studies show that, in some situations, interactive visualization can be less efficient than working with unprocessed text-based information. On the other hand, the studies also show that combining automatic data analysis with interactive visualization can lead to more unexpected findings, especially when exploring large data. The extent of manual information organization varies with the task: the less users know about the gathered information, the more automatic organization they expect. \n\nIn summary, this project contributed novel user interface concepts and design guidelines for user interfaces supporting information foraging and sensemaking. The techniques and study results were published at high-ranking peer-reviewed venues, and it can be expected that the findings of this project shape the way how users seek and organize their information in the future. \n\n", "start_date": "2015-12-01", "end_date": "2018-12-31", "leader_id": 1110, "logo": { "name": "logo.png", "path": "project:deskollage", "type": "image/png", "size": 331697, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/deskollage/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "T 752-N30", "comment": null } ], "research_areas": [ "InfoVis" ], "publications": [ "2019-ic", "byska-2019-mdfc", "casellato-2016-pkg", "cizmic-2018-evd", "donabauer-2015-asc", "dworschak-2016-szcm", "edlinger-2018-vwr", "georgiev-2019-cbg", "geymayer-2017-std", "gundacker-2020-wlm", "gusenbauer-2018", "hromniak-2019-vcn", "Koszticsak-2017-ewt", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "polatsek-2018-stv", "samoul-2019-cnp", "sietzen-2019-wnn", "sietzen-ifv-2019", "smiech-2018-tei", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "trautner-2018-imd", "unger-2019_vcp", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg" ], "url": "https://www.cg.tuwien.ac.at/research/projects/deskollage", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2017/mazurek-2017-vows/", "__class": "Publication" }, { "id": "mazurek-2017-sio", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Stream I/O - An Interactive Visualization of Publication Data", "date": "2017", "abstract": "The publication database of the Institute of Computer Graphics and Algorithms can\ncurrently be queried by a simple UI which returns a list. Stream I/O, the application\nof this thesis, extends the interface to improve it in terms of overview, exploration and\nanalysis support. To cope with these shortcommings a visualization is added to the user\ninterface. As the publication database includes a lot of additional data attributes, a\nselection of attributes is used for the visualization to give further insight. By using the\nStreamgraph [BW08] visualization, the variations over time within attributes like authors,\npublication type and research areas are made visible. The focus of this visualization lies\nin showing individual attribute values while also conveying the sum. This relationship\nis depicted in a timeline, which allows a user to explore the past and current work of\nthe institute as well as to find relationships and trends in the publications. As the\nvisualization uses a timeline encoding, the directed flow from left to right is interpreted\nas the movement through time. It shows the evolution of different attributes, while the\noccurrence of a topic at a specific time is coded with the width of the layer at a specific\npoint. Searching the database is enriched through multiple viewpoints which give the user\ninsight how attributes relate in the underlying data and how the data is changing through\nhis/her manipulation. Selections of colored layers within the graph can represent bigger\ntrends and give insight into the data as a whole. The Stream I/O application invites\nusers to interactively explore the publication database, while simultaneously gaining new\ninsight through the visualization.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1293, "image_height": 562, "name": "mazurek-2017-sio-.png", "type": "image/png", "size": 403642, "path": "Publication:mazurek-2017-sio", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/mazurek-2017-sio/mazurek-2017-sio-.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/mazurek-2017-sio/mazurek-2017-sio-:thumb{{size}}.png" }, "sync_repositum_override": null, "authors": [ { "id": 1364, "drupal_id": 1285, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/MichaelMazurek", "firstname": "Michael", "lastname": "Mazurek", "searchname": "Michael Mazurek", "is_teacher": false, "name": "Michael Mazurek", "publications": [ "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "mazurek-2018-veq", "field_id": "lecturer", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1364", "__class": "Author" } ], "date_end": "2017-03", "date_start": "2016-05", "duration": "4 months", "matrikelnr": "0123456", "supervisor": [ { "id": 1110, "drupal_id": 625, "orcid_id": "0000-0003-1387-5132", "website": "https://www.cg.tuwien.ac.at/staff/ManuelaWaldner", "firstname": "Manuela", "lastname": "Waldner", "searchname": "Manuela Waldner", "is_teacher": true, "name": "Manuela Waldner", "publications": [ "2019-ic", "Alharbi_2021", "bernhard-2016-gft", "byska-2019-mdfc", "eschner-2023-evl", "eschner-2023-ims", "geymayer-2017-std", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", 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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": "", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1293, "image_height": 562, "name": "mazurek-2017-sio-.png", "type": "image/png", "size": 403642, "path": "Publication:mazurek-2017-sio", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/mazurek-2017-sio/mazurek-2017-sio-.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/mazurek-2017-sio/mazurek-2017-sio-:thumb{{size}}.png" }, { "description": null, "filetitle": "thesis", "main_file": false, "use_in_gallery": false, "access": "public", "name": "mazurek-2017-sio-thesis.pdf", "type": "application/pdf", "size": 4004622, "path": "Publication:mazurek-2017-sio", "url": "https://www.cg.tuwien.ac.at/research/publications/2017/mazurek-2017-sio/mazurek-2017-sio-thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2017/mazurek-2017-sio/mazurek-2017-sio-thesis:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "deskollage", "workgroup_id": "vis", "drupal_id": 4198, "name": "Visual Information Foraging on the Desktop", "name_de": null, "website": null, "status": "active", "short_abstract": "The goal of this project is to design and develop novel interactive visualization techniques to support knowledge workers in making sense of their unstructured, dynamic information collections. ", "abstract": "Knowledge workers, such as scientists, journalists, or consultants, adaptively seek, gather, and consume information. Initially, knowledge workers may not even know what exactly they are looking for. Only after investigating more and more information, they develop a more concrete mental picture. These “information foraging” and “sensemaking” processes are often inefficient as existing user interfaces provide limited possibilities to combine information from various sources and different formats into a common knowledge representation. The goal of this project was to facilitate such knowledge-intensive tasks through user interfaces that combine manual organization strategies, such as piling of papers and text annotations, with powerful automatic data processing to reveal hidden relations in the collected data.\n \nThis project led to multiple novel user interface concepts that support knowledge-intensive tasks. For instance, visual query expansion is an extension to a search engine that visualizes the effects of suggested variations on an online query result to help users to refine their query terms. The information collage lets users capture information fragments from any online sources, which can then be freely recomposed into a common knowledge representation. Natural language processing helps users to identify common topics in their collage. BiCFlows helps users to discover hidden relations in very large information collections. For instance, they can explore which authors tend to contribute to similar topics. \n\nThe user interfaces served as foundation for empirical research with users from different knowledge work domains. This research provided new insights into the strengths but also the limitations of interactive visualization for information foraging and sensemaking. On the one hand, the studies show that, in some situations, interactive visualization can be less efficient than working with unprocessed text-based information. On the other hand, the studies also show that combining automatic data analysis with interactive visualization can lead to more unexpected findings, especially when exploring large data. The extent of manual information organization varies with the task: the less users know about the gathered information, the more automatic organization they expect. \n\nIn summary, this project contributed novel user interface concepts and design guidelines for user interfaces supporting information foraging and sensemaking. The techniques and study results were published at high-ranking peer-reviewed venues, and it can be expected that the findings of this project shape the way how users seek and organize their information in the future. \n\n", "start_date": "2015-12-01", "end_date": "2018-12-31", "leader_id": 1110, "logo": { "name": "logo.png", "path": "project:deskollage", "type": "image/png", "size": 331697, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/deskollage/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "T 752-N30", "comment": null } ], "research_areas": [ "InfoVis" ], "publications": [ "2019-ic", "byska-2019-mdfc", "casellato-2016-pkg", "cizmic-2018-evd", "donabauer-2015-asc", "dworschak-2016-szcm", "edlinger-2018-vwr", "georgiev-2019-cbg", "geymayer-2017-std", "gundacker-2020-wlm", "gusenbauer-2018", "hromniak-2019-vcn", "Koszticsak-2017-ewt", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "polatsek-2018-stv", "samoul-2019-cnp", "sietzen-2019-wnn", "sietzen-ifv-2019", "smiech-2018-tei", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "trautner-2018-imd", "unger-2019_vcp", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2019-ccm", "Waldner_2017_11", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg" ], "url": "https://www.cg.tuwien.ac.at/research/projects/deskollage", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2017/mazurek-2017-sio/", "__class": "Publication" }, { "id": "dworschak-2016-szcm", "type_id": "bachelorthesis", "tu_id": null, "repositum_id": null, "title": "Semantically Zoomable Choropleth Map", "date": "2016-09", "abstract": "Geographic visualizations, like choropleth maps, are used to visualize data on geographic\nregions. In this thesis a choropleth map was implemented to display quantities of\npublications of scientific texts and papers. With the use of a choropleth map the viewer\nis able to interpret how quantitative data changes on different geographic regions. The\nmain feature that distinguishes the implemented choropleth map from conventional ones\nis the use of map navigation. The choropleth map can be zoomed and panned to different\nmap regions. What makes this map navigation so special is the use of semantic zooming\nto allow the level of detail of the map to change on discrete zoom steps. The change\nof the level of detail means that administrative regions are being divided into smaller\nadministrative regions which are than again colorized individually to create a new, more\ndetailed, choropleth map. Other interactions with the choropleth map are introduced\nadditionally. The other interactions with the map range from the manipulation of the\nmap appearance to filtering the displayed data set.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 637, "image_height": 185, "name": "dworschak-2016-szcm-teaser.png", "type": "image/png", "size": 73351, "path": "Publication:dworschak-2016-szcm", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/dworschak-2016-szcm/dworschak-2016-szcm-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/dworschak-2016-szcm/dworschak-2016-szcm-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "authors": [ { "id": 1353, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Lucas", "lastname": "Dworschak", "searchname": "Lucas Dworschak", "is_teacher": false, "name": "Lucas Dworschak", "publications": [ "dworschak-2016-szcm" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1353", "__class": "Author" } ], "date_end": "2016-09", "date_start": "2016-05", "duration": "5 months", "matrikelnr": "1225883", "supervisor": [ { "id": 1110, "drupal_id": 625, "orcid_id": "0000-0003-1387-5132", "website": "https://www.cg.tuwien.ac.at/staff/ManuelaWaldner", "firstname": "Manuela", "lastname": "Waldner", "searchname": "Manuela Waldner", "is_teacher": true, "name": "Manuela Waldner", "publications": [ "2019-ic", "Alharbi_2021", "bernhard-2016-gft", "byska-2019-mdfc", "eschner-2023-evl", "eschner-2023-ims", "geymayer-2017-std", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", "indirectBiasLanguageModels-2023", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "mazurek-2018-veq", "polatsek-2018-stv", "reina-2020-mtv", "sietzen-2021-perturber", 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"field_id": "lecturer", "ordernum": 0 }, { "publ_id": "wolf-2023-cc", "field_id": "supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1110", "__class": "Author" } ], "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.
\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": [], "files": [ { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 637, "image_height": 185, "name": "dworschak-2016-szcm-teaser.png", "type": "image/png", "size": 73351, "path": "Publication:dworschak-2016-szcm", "url": 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"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