[ { "id": "TR1862162", "type_id": "techreport", "tu_id": null, "repositum_id": null, "title": "Visual Analysis of Volume Ensembles Based on Local Features", "date": "2016-05", "abstract": "Ensemble datasets describe a specific phenomenon (e.g., a simulation scenario or a measurements series) through a large set of individual ensemble members. These individual members typically do not differ too much from each other but rather feature slightly changing characteristics. In many cases, the ensemble members are defined in 3D space, which implies severe challenges when exploring the complete ensembles such as handling occlusions, focus and context or its sheer datasize. In this paper we address these challenges and put our focus on the exploration of local features in 3D volumetric ensemble datasets, not only by visualizing local characteristics, but also by identifying connections to other local features with similar characteristics in the data. We evaluate the variance in the dataset and use the the spatial median (medoid) of the ensemble to visualize the differences in the dataset. This medoid is subsequently used as a representative of the ensemble in 3D. The variance information is used to guide users during the exploration, as regions of high variance also indicate larger changes within the ensemble members. The local characteristics of the regions can be explored by using our proposed 3D probing widgets. These widgets consist of a 3D sphere, which can be positioned at any point in 3D space. While moving a widget, the local data characteristics at the corresponding position are shown in a separate detail view, which depicts the local outliers and their surfaces in comparison to the medoid surface. The 3D probing widgets can also be fixed at a user-defined position of interest. The fixed probing widgets are arranged in a similarity graph to indicate similar local data characteristics. The similarity graph thus allows to explore whether high variances in a certain region are caused by the same dataset members or not. Finally, it is also possible to compare a single member against the rest of the ensemble. We evaluate our technique through two demonstration cases using volumetric multi-label segmentation mask datasets, two from the\nindustrial domain and two from the medical domain.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 599, "image_height": 277, "name": "TR1862162-teaser.png", "type": "image/png", "size": 498904, "path": "Publication:TR1862162", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/TR1862162/TR1862162-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/TR1862162/TR1862162-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "authors": [ { "id": 950, "drupal_id": 292, "orcid_id": "0000-0002-9638-6344", "website": "https://www.cg.tuwien.ac.at/staff/JohannaSchmidt", "firstname": "Johanna", "lastname": "Schmidt", "searchname": "Johanna Schmidt", "is_teacher": false, "name": "Johanna Schmidt", "publications": [ "karimov-2013-vivisection", "medeiros-2023-gwf", "Mistelbauer_Gabriel_2016", "piccolotto-2023-dta", "rsabin-2013", "schmidt-2011-mt", "schmidt-phd", "TR1862162", "vaico", "ymca" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "2015-image-coll", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "audioflow", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Mlinaric-2015-MT", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "textures-3d-printing", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "tuscher-2023-qeo", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "vaico", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "ymca", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Zhu-2014-flowvis", "field_id": "supervisor", "ordernum": 1 } ], "url": 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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-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" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2016/TR1862162/", "__class": "Publication" }, { "id": "beham-2014-cupid", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "Cupid: Cluster-based Exploration of Geometry Generators with Parallel Coordinates and Radial Trees", "date": "2014-12", "abstract": "Geometry generators are commonly used in video games and evaluation systems for computer vision to create geometric shapes such as terrains, vegetation or airplanes. The parameters of the generator are often sampled automatically which can lead to many similar or unwanted geometric shapes. In this paper, we propose a novel visual exploration approach that combines the abstract parameter space of the geometry generator with the resulting 3D shapes in a composite visualization. Similar geometric shapes are first grouped using hierarchical clustering and then nested within an illustrative parallel coordinates visualization. This helps the user to study the sensitivity of the generator with respect to its parameter space and to identify invalid parameter settings. Starting from a compact overview representation, the user can iteratively drill-down into local shape differences by clicking on the respective clusters. Additionally, a linked radial tree gives an overview of the cluster hierarchy and enables the user to manually split or merge clusters. We evaluate our approach by exploring the parameter space of a cup generator and provide feedback from domain experts.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "teaser", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 307, "image_height": 255, "name": "beham-2014-cupid-teaser.png", "type": "image/png", "size": 235549, "path": "Publication:beham-2014-cupid", "url": "https://www.cg.tuwien.ac.at/research/publications/2014/beham-2014-cupid/beham-2014-cupid-teaser.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2014/beham-2014-cupid/beham-2014-cupid-teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "authors": [ { "id": 816, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Michael", "lastname": "Beham", "searchname": "Michael Beham", "is_teacher": false, "name": "Michael Beham", "publications": [ "beham_2009.2009-EVS", "Beham_Michael_PSC", "beham-2014-cupid", "BEHAM-2014-RCR" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "beham-2014-cupid", "field_id": "lecturer", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=816", "__class": "Author" }, { "id": 1193, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Wolfgang", "lastname": "Herzner", "searchname": "Wolfgang Herzner", "is_teacher": false, "name": "Wolfgang Herzner", "publications": [ "beham-2014-cupid" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1193", "__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, 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"thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2014/beham-2014-cupid/beham-2014-cupid-transitions:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "ViMaL", "workgroup_id": "vis", "drupal_id": 4222, "name": "ViMaL: A Visualization Mapping Language", "name_de": null, "website": null, "status": "active", "short_abstract": "Visualization is the discipline dealing with the depiction of data. The assignment of visual abstractions to data abstractions is referred to as the visualization mapping. \nExpressive visualization mappings proofed in many cases to be more effective than the examination of raw data (i.e., large tables of numbers). Although visualization mapping is a crucial step in the visualization pipeline surprisingly few general approaches exist.\nWe propose to develop the Visualization Mapping Language (ViMaL) that is capable of describing expressive visualization mappings and provides user interfaces suitable for non-experts in visualization. \nViMaL will be a language that is used to specify visualization pipelines. We will provide language concepts for the specification of data abstraction processes, visual concretization processes and the required visualization mapping. With this approach the semantics of a specific domain are modeled by the domain experts while the semantics of the visualization domain are modeled by the visualization expert. The visualization mapping is described using domain semantics as well as visualization semantics. Unlike other general purpose visualization systems, ViMaL systems explicitly use the semantics of the visualization mapping process. It incorporates information and knowledge assisted methods in the visualization mapping pipeline.\nIn the scope of this project we will define a novel Visualization Mapping Language and implement a toolbox that aids researchers from other areas to integrate the ViMaL concepts into their systems. The toolbox will provide basic ViMaL document setup and parsing as well as components for each step in the visualization pipeline. We will make use of fuzzy logic in our components for the abstraction of data, for the visual concretization, and for the visualization mapping. \nWe believe that the formalization of the visualization pipeline that is achieved with the visualization mapping language will enable many researchers from other domains to benefit from existing visualization methods. Further, the introduction of domain and visualization semantics for the specification of visualization mappings enables meta-visualization approaches that provide insight into the visualization process itself. Laypersons will benefit from such meta-visualization systems that are able to illustrate the involved components.", "abstract": "Visualization is the discipline dealing with the depiction of data. The assignment of visual abstractions to data abstractions is referred to as the visualization mapping. \nExpressive visualization mappings proofed in many cases to be more effective than the examination of raw data (i.e., large tables of numbers). Although visualization mapping is a crucial step in the visualization pipeline surprisingly few general approaches exist.\nWe propose to develop the Visualization Mapping Language (ViMaL) that is capable of describing expressive visualization mappings and provides user interfaces suitable for non-experts in visualization. \nViMaL will be a language that is used to specify visualization pipelines. We will provide language concepts for the specification of data abstraction processes, visual concretization processes and the required visualization mapping. With this approach the semantics of a specific domain are modeled by the domain experts while the semantics of the visualization domain are modeled by the visualization expert. The visualization mapping is described using domain semantics as well as visualization semantics. Unlike other general purpose visualization systems, ViMaL systems explicitly use the semantics of the visualization mapping process. It incorporates information and knowledge assisted methods in the visualization mapping pipeline.\nIn the scope of this project we will define a novel Visualization Mapping Language and implement a toolbox that aids researchers from other areas to integrate the ViMaL concepts into their systems. The toolbox will provide basic ViMaL document setup and parsing as well as components for each step in the visualization pipeline. We will make use of fuzzy logic in our components for the abstraction of data, for the visual concretization, and for the visualization mapping. \nWe believe that the formalization of the visualization pipeline that is achieved with the visualization mapping language will enable many researchers from other domains to benefit from existing visualization methods. Further, the introduction of domain and visualization semantics for the specification of visualization mappings enables meta-visualization approaches that provide insight into the visualization process itself. Laypersons will benefit from such meta-visualization systems that are able to illustrate the involved components.", "start_date": "2010-01-01", "end_date": "2014-12-31", "leader_id": 166, "logo": { "name": "logo.png", "path": "project:ViMaL", "type": "image/png", "size": 51461, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/ViMaL/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "P 21695-N23", "comment": null } ], "research_areas": [], "publications": [ "beham-2014-cupid", "Birkeland-2012-IMC", "borgo-2013-gly", "bruckner-2010-HVC", "Csebfalvi-2012-IOM", "Groeller_2011_NR", "Herghelegiu-2012-BPV", "kehrer-2013-IVA", "kehrer-2013-SBC", "Kehrer-2014-CSD", "Labschuetz_Matthias_2016_JIT", "Labschuetz_Matthias_2016_JITT", "mindek_peter-2014-cs_kaust", "mindek-2013-cs_cvut", "mindek-2013-csl", "mindek-2013-pel", "mindek-2014-mcs", "mindek-2014-vivi_cvut", "mindek-2015-mctalk", "mindek-thesis", "oeltze-2013-tut", "Peter_2012_AIV", "rautek2010", "Ropinski-2012-UBT", "schmidt-phd", "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", "Soros_AVN_2011", "vaico", "ymca" ], "url": "https://www.cg.tuwien.ac.at/research/projects/ViMaL", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2014/beham-2014-cupid/", "__class": "Publication" }, { "id": "Kehrer-2014-CSD", "type_id": "talk", "tu_id": null, "repositum_id": null, "title": "Interactive Visual Analysis of Complex Scientific Data", "date": "2014", "abstract": "", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "authors": [ { "id": 983, "drupal_id": 629, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/JohannesKehrer", "firstname": "Johannes", "lastname": "Kehrer", "searchname": "Johannes Kehrer", "is_teacher": false, "name": "Johannes Kehrer", "publications": [ "beham-2014-cupid", "borgo-2013-gly", "daae-lampe-2010-dif", "Kehrer-2007-Mas", "Kehrer-2008-hyp", "Kehrer-2010-mom", "Kehrer-2011-PhD", "kehrer-2011-vai", "kehrer-2012-mod", "kehrer-2013-IVA", "kehrer-2013-SBC", "Kehrer-2013-STAR", "Kehrer-2014-CSD", "Ladstaedter-2009-sim", "Ladstaedter-2010-exp", "lie-2009-cri", "Muigg-2008-four", "oeltze-2013-tut", "TR1862162" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "Beham_Michael_PSC", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "borgo-2013-gly", "field_id": "lecturer", "ordernum": 1 }, { "publ_id": "Kehrer-2008-hyp", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Kehrer-2010-mom", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "kehrer-2011-vai", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "kehrer-2012-mod", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "kehrer-2013-SBC", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "oeltze-2013-tut", "field_id": "lecturer", "ordernum": 2 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=983", "__class": "Author" } ], "date_from": "2014-01-07", "event": "TU München", "location": "Munich, Germany", "research_areas": [], "keywords": [], "weblinks": [], "files": [], "projects_workgroups": [ { "id": "ViMaL", "workgroup_id": "vis", "drupal_id": 4222, "name": "ViMaL: A Visualization Mapping Language", "name_de": null, "website": null, "status": "active", "short_abstract": "Visualization is the discipline dealing with the depiction of data. The assignment of visual abstractions to data abstractions is referred to as the visualization mapping. \nExpressive visualization mappings proofed in many cases to be more effective than the examination of raw data (i.e., large tables of numbers). Although visualization mapping is a crucial step in the visualization pipeline surprisingly few general approaches exist.\nWe propose to develop the Visualization Mapping Language (ViMaL) that is capable of describing expressive visualization mappings and provides user interfaces suitable for non-experts in visualization. \nViMaL will be a language that is used to specify visualization pipelines. We will provide language concepts for the specification of data abstraction processes, visual concretization processes and the required visualization mapping. With this approach the semantics of a specific domain are modeled by the domain experts while the semantics of the visualization domain are modeled by the visualization expert. The visualization mapping is described using domain semantics as well as visualization semantics. Unlike other general purpose visualization systems, ViMaL systems explicitly use the semantics of the visualization mapping process. It incorporates information and knowledge assisted methods in the visualization mapping pipeline.\nIn the scope of this project we will define a novel Visualization Mapping Language and implement a toolbox that aids researchers from other areas to integrate the ViMaL concepts into their systems. The toolbox will provide basic ViMaL document setup and parsing as well as components for each step in the visualization pipeline. We will make use of fuzzy logic in our components for the abstraction of data, for the visual concretization, and for the visualization mapping. \nWe believe that the formalization of the visualization pipeline that is achieved with the visualization mapping language will enable many researchers from other domains to benefit from existing visualization methods. Further, the introduction of domain and visualization semantics for the specification of visualization mappings enables meta-visualization approaches that provide insight into the visualization process itself. Laypersons will benefit from such meta-visualization systems that are able to illustrate the involved components.", "abstract": "Visualization is the discipline dealing with the depiction of data. The assignment of visual abstractions to data abstractions is referred to as the visualization mapping. \nExpressive visualization mappings proofed in many cases to be more effective than the examination of raw data (i.e., large tables of numbers). Although visualization mapping is a crucial step in the visualization pipeline surprisingly few general approaches exist.\nWe propose to develop the Visualization Mapping Language (ViMaL) that is capable of describing expressive visualization mappings and provides user interfaces suitable for non-experts in visualization. \nViMaL will be a language that is used to specify visualization pipelines. We will provide language concepts for the specification of data abstraction processes, visual concretization processes and the required visualization mapping. With this approach the semantics of a specific domain are modeled by the domain experts while the semantics of the visualization domain are modeled by the visualization expert. The visualization mapping is described using domain semantics as well as visualization semantics. Unlike other general purpose visualization systems, ViMaL systems explicitly use the semantics of the visualization mapping process. It incorporates information and knowledge assisted methods in the visualization mapping pipeline.\nIn the scope of this project we will define a novel Visualization Mapping Language and implement a toolbox that aids researchers from other areas to integrate the ViMaL concepts into their systems. The toolbox will provide basic ViMaL document setup and parsing as well as components for each step in the visualization pipeline. We will make use of fuzzy logic in our components for the abstraction of data, for the visual concretization, and for the visualization mapping. \nWe believe that the formalization of the visualization pipeline that is achieved with the visualization mapping language will enable many researchers from other domains to benefit from existing visualization methods. Further, the introduction of domain and visualization semantics for the specification of visualization mappings enables meta-visualization approaches that provide insight into the visualization process itself. Laypersons will benefit from such meta-visualization systems that are able to illustrate the involved components.", "start_date": "2010-01-01", "end_date": "2014-12-31", "leader_id": 166, "logo": { "name": "logo.png", "path": "project:ViMaL", "type": "image/png", "size": 51461, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/ViMaL/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "P 21695-N23", "comment": null } ], "research_areas": [], "publications": [ "beham-2014-cupid", "Birkeland-2012-IMC", "borgo-2013-gly", "bruckner-2010-HVC", "Csebfalvi-2012-IOM", "Groeller_2011_NR", "Herghelegiu-2012-BPV", "kehrer-2013-IVA", "kehrer-2013-SBC", "Kehrer-2014-CSD", "Labschuetz_Matthias_2016_JIT", "Labschuetz_Matthias_2016_JITT", "mindek_peter-2014-cs_kaust", "mindek-2013-cs_cvut", "mindek-2013-csl", "mindek-2013-pel", "mindek-2014-mcs", "mindek-2014-vivi_cvut", "mindek-2015-mctalk", "mindek-thesis", "oeltze-2013-tut", "Peter_2012_AIV", "rautek2010", "Ropinski-2012-UBT", "schmidt-phd", "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", "Soros_AVN_2011", "vaico", "ymca" ], "url": "https://www.cg.tuwien.ac.at/research/projects/ViMaL", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2014/Kehrer-2014-CSD/", "__class": "Publication" }, { "id": "kehrer-2013-SBC", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "A Model for Structure-based Comparison of Many Categories in Small-Multiple Displays", "date": "2013-12", "abstract": "Many application domains deal with multi-variate data that consists of both categorical and numerical information. Small-multiple\ndisplays are a powerful concept for comparing such data by juxtaposition. For comparison by overlay or by explicit encoding\nof computed differences, however, a specification of references is necessary. In this paper, we present a formal model for defining\nsemantically meaningful comparisons between many categories in a small-multiple display. Based on pivotized data that are hierarchically\npartitioned by the categories assigned to the x and y axis of the display, we propose two alternatives for structure-based\ncomparison within this hierarchy. With an absolute reference specification, categories are compared to a fixed reference category.\nWith a relative reference specification, in contrast, a semantic ordering of the categories is considered when comparing them either to\nthe previous or subsequent category each. Both reference specifications can be defined at multiple levels of the hierarchy (including\naggregated summaries), enabling a multitude of useful comparisons. We demonstrate the general applicability of our model in several\napplication examples using different visualizations that compare data by overlay or explicit encoding of differences.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 759, "image_height": 903, "name": "kehrer-2013-SBC-image.jpg", "type": "image/jpeg", "size": 208520, "path": "Publication:kehrer-2013-SBC", "url": "https://www.cg.tuwien.ac.at/research/publications/2013/kehrer-2013-SBC/kehrer-2013-SBC-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/kehrer-2013-SBC/kehrer-2013-SBC-image:thumb{{size}}.png" }, "sync_repositum_override": null, "authors": [ { "id": 983, "drupal_id": 629, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/JohannesKehrer", "firstname": "Johannes", "lastname": "Kehrer", "searchname": "Johannes Kehrer", "is_teacher": false, "name": "Johannes Kehrer", "publications": [ "beham-2014-cupid", "borgo-2013-gly", "daae-lampe-2010-dif", "Kehrer-2007-Mas", "Kehrer-2008-hyp", "Kehrer-2010-mom", "Kehrer-2011-PhD", "kehrer-2011-vai", "kehrer-2012-mod", "kehrer-2013-IVA", "kehrer-2013-SBC", "Kehrer-2013-STAR", "Kehrer-2014-CSD", "Ladstaedter-2009-sim", "Ladstaedter-2010-exp", "lie-2009-cri", "Muigg-2008-four", "oeltze-2013-tut", "TR1862162" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "Beham_Michael_PSC", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "borgo-2013-gly", "field_id": "lecturer", "ordernum": 1 }, { "publ_id": "Kehrer-2008-hyp", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Kehrer-2010-mom", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "kehrer-2011-vai", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "kehrer-2012-mod", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "kehrer-2013-SBC", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "oeltze-2013-tut", "field_id": "lecturer", "ordernum": 2 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=983", "__class": "Author" }, { "id": 451, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Harald", "lastname": "Piringer", "searchname": "Harald Piringer", "is_teacher": false, "name": "Harald Piringer", "publications": [ "Berger_2011_UAE", "Bittner-2004-CHC", "kehrer-2012-mod", "kehrer-2013-SBC", "Muigg-2008-four", "ortner-2016-tunnel", "ortner-2016-visaware", "PH-2011-LDS", "PIRINGER-2003-HBOQ", "piringer-2009-hds", "sorger-2015-litevis", "sorger-2015-taxintec" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "froschauer-2009-iod", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "ludwig-2012-MT", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Muehlbacher_diss_2018", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Pajer_2012_VoM", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "piringer-2009-hds", "field_id": "lecturer", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=451", "__class": "Author" }, { "id": 961, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Wolfgang", "lastname": "Berger", "searchname": "Wolfgang Berger", "is_teacher": false, "name": "Wolfgang Berger", "publications": [ "Berger_2011_UAE", "kehrer-2013-SBC" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "Berger_2011_UAE", "field_id": "lecturer", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=961", "__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", 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The assignment of visual abstractions to data abstractions is referred to as the visualization mapping. \nExpressive visualization mappings proofed in many cases to be more effective than the examination of raw data (i.e., large tables of numbers). Although visualization mapping is a crucial step in the visualization pipeline surprisingly few general approaches exist.\nWe propose to develop the Visualization Mapping Language (ViMaL) that is capable of describing expressive visualization mappings and provides user interfaces suitable for non-experts in visualization. \nViMaL will be a language that is used to specify visualization pipelines. We will provide language concepts for the specification of data abstraction processes, visual concretization processes and the required visualization mapping. With this approach the semantics of a specific domain are modeled by the domain experts while the semantics of the visualization domain are modeled by the visualization expert. The visualization mapping is described using domain semantics as well as visualization semantics. Unlike other general purpose visualization systems, ViMaL systems explicitly use the semantics of the visualization mapping process. It incorporates information and knowledge assisted methods in the visualization mapping pipeline.\nIn the scope of this project we will define a novel Visualization Mapping Language and implement a toolbox that aids researchers from other areas to integrate the ViMaL concepts into their systems. The toolbox will provide basic ViMaL document setup and parsing as well as components for each step in the visualization pipeline. We will make use of fuzzy logic in our components for the abstraction of data, for the visual concretization, and for the visualization mapping. \nWe believe that the formalization of the visualization pipeline that is achieved with the visualization mapping language will enable many researchers from other domains to benefit from existing visualization methods. Further, the introduction of domain and visualization semantics for the specification of visualization mappings enables meta-visualization approaches that provide insight into the visualization process itself. Laypersons will benefit from such meta-visualization systems that are able to illustrate the involved components.", "abstract": "Visualization is the discipline dealing with the depiction of data. The assignment of visual abstractions to data abstractions is referred to as the visualization mapping. \nExpressive visualization mappings proofed in many cases to be more effective than the examination of raw data (i.e., large tables of numbers). Although visualization mapping is a crucial step in the visualization pipeline surprisingly few general approaches exist.\nWe propose to develop the Visualization Mapping Language (ViMaL) that is capable of describing expressive visualization mappings and provides user interfaces suitable for non-experts in visualization. \nViMaL will be a language that is used to specify visualization pipelines. We will provide language concepts for the specification of data abstraction processes, visual concretization processes and the required visualization mapping. With this approach the semantics of a specific domain are modeled by the domain experts while the semantics of the visualization domain are modeled by the visualization expert. 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We will make use of fuzzy logic in our components for the abstraction of data, for the visual concretization, and for the visualization mapping. \nWe believe that the formalization of the visualization pipeline that is achieved with the visualization mapping language will enable many researchers from other domains to benefit from existing visualization methods. Further, the introduction of domain and visualization semantics for the specification of visualization mappings enables meta-visualization approaches that provide insight into the visualization process itself. 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Interactive visual analysis (IVA) comprises concepts and techniques for a user-guided knowledge discovery in such complex data. Through a tight feedback loop of computation,\r\nvisualization and user interaction, it provides new insight into the data and serves as a vehicle for\r\nhypotheses generation or validation. It is often implemented via a multiple coordinated view framework where each view is equipped with interactive drill-down operations for focusing on data features.\r\nTwo classes of views are integrated:\r\nphysical views, such as direct volume rendering, show information in the context of the spatiotemporal observation space while\r\nattribute views, such as scatter\r\nplots and parallel coordinates, show relationships between multiple data attributes. The user may drill-down the data by selecting interesting regions of the observation space or attribute ranges leading to\r\na consistent highlighting of this selection in all other views (brushing-and-linking). Three patterns of\r\nexplorative/analytical procedures may be accomplished by doing so. In a\r\nfeature localization, the user\r\nsearches for places in the 3D/4D observation space where certain attribute values are present. In a\r\nmulti-variate analysis, relations between data attributes are investigated, e.g., by searching for correla-\r\ntions. In a local investigation, the user inspects the values of selected attributes with respect to certain\r\nspatiotemporal subsets of the observation space.\r\n\r\nIn this tutorial, we discuss examples for successful applications of IVA to scientific data from various\r\nfields: climate research, medicine, epidemiology, and flow simulation / computation, in particular for\r\nautomotive engineering. We base our discussions on a theoretical foundation of IVA which helps the\r\ntutorial attendees in transferring the subject matter to their own data and application area. In the course\r\nof the tutorial, the attendees will become acquainted with techniques from statistics and knowledge\r\ndiscovery, which proved to be particularly useful for a specific IVA application. The tutorial further\r\ncomprises an overview of off-the-shelf IVA solutions, which may be be particularly interesting for\r\nvisualization practitioners. 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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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Chung", "filetitle": "slides Chung", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 1161, "preview_image_height": 865, "name": "borgo-2013-gly-slides Chung.pdf", "type": "application/pdf", "size": 2236108, "path": "Publication:borgo-2013-gly", "preview_name": "borgo-2013-gly-slides Chung:preview.png", "preview_type": "image/png", "preview_size": 3018582, "url": "https://www.cg.tuwien.ac.at/research/publications/2013/borgo-2013-gly/borgo-2013-gly-slides Chung.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/borgo-2013-gly/borgo-2013-gly-slides Chung:thumb{{size}}.png" }, { "description": "presentation by J. Kehrer", "filetitle": "slides J. Kehrer", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 1161, "preview_image_height": 866, "name": "borgo-2013-gly-slides J. Kehrer.pdf", "type": "application/pdf", "size": 2141660, "path": "Publication:borgo-2013-gly", "preview_name": "borgo-2013-gly-slides J. Kehrer:preview.png", "preview_type": "image/png", "preview_size": 3022083, "url": "https://www.cg.tuwien.ac.at/research/publications/2013/borgo-2013-gly/borgo-2013-gly-slides J. Kehrer.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/borgo-2013-gly/borgo-2013-gly-slides J. Kehrer:thumb{{size}}.png" }, { "description": "teaser image", "filetitle": "teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 640, "image_height": 533, "name": "borgo-2013-gly-teaser.jpg", "type": "image/jpeg", "size": 127128, "path": "Publication:borgo-2013-gly", "url": "https://www.cg.tuwien.ac.at/research/publications/2013/borgo-2013-gly/borgo-2013-gly-teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/borgo-2013-gly/borgo-2013-gly-teaser:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "ViMaL", "workgroup_id": "vis", "drupal_id": 4222, "name": "ViMaL: A Visualization Mapping Language", "name_de": null, "website": null, "status": "active", "short_abstract": "Visualization is the discipline dealing with the depiction of data. The assignment of visual abstractions to data abstractions is referred to as the visualization mapping. \nExpressive visualization mappings proofed in many cases to be more effective than the examination of raw data (i.e., large tables of numbers). Although visualization mapping is a crucial step in the visualization pipeline surprisingly few general approaches exist.\nWe propose to develop the Visualization Mapping Language (ViMaL) that is capable of describing expressive visualization mappings and provides user interfaces suitable for non-experts in visualization. \nViMaL will be a language that is used to specify visualization pipelines. We will provide language concepts for the specification of data abstraction processes, visual concretization processes and the required visualization mapping. With this approach the semantics of a specific domain are modeled by the domain experts while the semantics of the visualization domain are modeled by the visualization expert. The visualization mapping is described using domain semantics as well as visualization semantics. Unlike other general purpose visualization systems, ViMaL systems explicitly use the semantics of the visualization mapping process. It incorporates information and knowledge assisted methods in the visualization mapping pipeline.\nIn the scope of this project we will define a novel Visualization Mapping Language and implement a toolbox that aids researchers from other areas to integrate the ViMaL concepts into their systems. The toolbox will provide basic ViMaL document setup and parsing as well as components for each step in the visualization pipeline. We will make use of fuzzy logic in our components for the abstraction of data, for the visual concretization, and for the visualization mapping. \nWe believe that the formalization of the visualization pipeline that is achieved with the visualization mapping language will enable many researchers from other domains to benefit from existing visualization methods. Further, the introduction of domain and visualization semantics for the specification of visualization mappings enables meta-visualization approaches that provide insight into the visualization process itself. Laypersons will benefit from such meta-visualization systems that are able to illustrate the involved components.", "abstract": "Visualization is the discipline dealing with the depiction of data. The assignment of visual abstractions to data abstractions is referred to as the visualization mapping. \nExpressive visualization mappings proofed in many cases to be more effective than the examination of raw data (i.e., large tables of numbers). Although visualization mapping is a crucial step in the visualization pipeline surprisingly few general approaches exist.\nWe propose to develop the Visualization Mapping Language (ViMaL) that is capable of describing expressive visualization mappings and provides user interfaces suitable for non-experts in visualization. \nViMaL will be a language that is used to specify visualization pipelines. We will provide language concepts for the specification of data abstraction processes, visual concretization processes and the required visualization mapping. With this approach the semantics of a specific domain are modeled by the domain experts while the semantics of the visualization domain are modeled by the visualization expert. The visualization mapping is described using domain semantics as well as visualization semantics. Unlike other general purpose visualization systems, ViMaL systems explicitly use the semantics of the visualization mapping process. It incorporates information and knowledge assisted methods in the visualization mapping pipeline.\nIn the scope of this project we will define a novel Visualization Mapping Language and implement a toolbox that aids researchers from other areas to integrate the ViMaL concepts into their systems. The toolbox will provide basic ViMaL document setup and parsing as well as components for each step in the visualization pipeline. We will make use of fuzzy logic in our components for the abstraction of data, for the visual concretization, and for the visualization mapping. \nWe believe that the formalization of the visualization pipeline that is achieved with the visualization mapping language will enable many researchers from other domains to benefit from existing visualization methods. Further, the introduction of domain and visualization semantics for the specification of visualization mappings enables meta-visualization approaches that provide insight into the visualization process itself. Laypersons will benefit from such meta-visualization systems that are able to illustrate the involved components.", "start_date": "2010-01-01", "end_date": "2014-12-31", "leader_id": 166, "logo": { "name": "logo.png", "path": "project:ViMaL", "type": "image/png", "size": 51461, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/ViMaL/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "P 21695-N23", "comment": null } ], "research_areas": [], "publications": [ "beham-2014-cupid", "Birkeland-2012-IMC", "borgo-2013-gly", "bruckner-2010-HVC", "Csebfalvi-2012-IOM", "Groeller_2011_NR", "Herghelegiu-2012-BPV", "kehrer-2013-IVA", "kehrer-2013-SBC", "Kehrer-2014-CSD", "Labschuetz_Matthias_2016_JIT", "Labschuetz_Matthias_2016_JITT", "mindek_peter-2014-cs_kaust", "mindek-2013-cs_cvut", "mindek-2013-csl", "mindek-2013-pel", "mindek-2014-mcs", "mindek-2014-vivi_cvut", "mindek-2015-mctalk", "mindek-thesis", "oeltze-2013-tut", "Peter_2012_AIV", "rautek2010", "Ropinski-2012-UBT", "schmidt-phd", "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", "Soros_AVN_2011", "vaico", "ymca" ], "url": "https://www.cg.tuwien.ac.at/research/projects/ViMaL", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2013/borgo-2013-gly/", "__class": "Publication" }, { "id": "Kehrer-2013-STAR", "type_id": "journalpaper_notalk", "tu_id": null, "repositum_id": null, "title": "Visualization and Visual Analysis of Multi-faceted Scientific Data: A Survey", "date": "2013-03", "abstract": "Visualization and visual analysis play important roles in exploring, analyzing and presenting scientific data. In many disciplines, data and model scenarios are becoming multi-faceted: data are often spatio-temporal and multi-variate; they stem from different data sources (multi-modal data), from multiple simulation runs (multi-run/ensemble data), or from multi-physics simulations of interacting phenomena (multi-model data resulting from coupled simulation models). Also, data can be of different dimensionality or structured on various types of grids that need to be related or fused in the visualization. This heterogeneity of data characteristics presents new opportunities as well as technical challenges for visualization research. Visualization and interaction techniques are thus often combined with computational analysis. In this survey, we study existing methods for visualization and interactive visual analysis of multi-faceted scientific data. Based on a thorough literature review, a categorization of approaches is proposed. We cover a wide range of fields and discuss to which degree the different challenges are matched with existing solutions for visualization and visual analysis. This leads to conclusions with respect to promising research directions, for instance, to pursue new solutions for multi-run and multi-model data as well as techniques that support a multitude of facets.", "authors_et_al": false, "substitute": null, "main_image": { "description": "Overview of topics discussed in the survey", "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 600, "image_height": 218, "name": "Kehrer-2013-STAR-image.png", "type": "image/png", "size": 13343, "path": "Publication:Kehrer-2013-STAR", "url": "https://www.cg.tuwien.ac.at/research/publications/2013/Kehrer-2013-STAR/Kehrer-2013-STAR-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2013/Kehrer-2013-STAR/Kehrer-2013-STAR-image:thumb{{size}}.png" }, "sync_repositum_override": null, "authors": [ { "id": 983, "drupal_id": 629, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/JohannesKehrer", "firstname": "Johannes", "lastname": "Kehrer", "searchname": "Johannes Kehrer", "is_teacher": false, "name": "Johannes Kehrer", "publications": [ "beham-2014-cupid", "borgo-2013-gly", "daae-lampe-2010-dif", "Kehrer-2007-Mas", "Kehrer-2008-hyp", "Kehrer-2010-mom", "Kehrer-2011-PhD", "kehrer-2011-vai", "kehrer-2012-mod", "kehrer-2013-IVA", "kehrer-2013-SBC", "Kehrer-2013-STAR", "Kehrer-2014-CSD", "Ladstaedter-2009-sim", "Ladstaedter-2010-exp", "lie-2009-cri", "Muigg-2008-four", "oeltze-2013-tut", "TR1862162" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "Beham_Michael_PSC", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "borgo-2013-gly", "field_id": "lecturer", "ordernum": 1 }, { "publ_id": "Kehrer-2008-hyp", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Kehrer-2010-mom", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "kehrer-2011-vai", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "kehrer-2012-mod", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "kehrer-2013-SBC", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "oeltze-2013-tut", "field_id": "lecturer", "ordernum": 2 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=983", "__class": "Author" }, { "id": 176, "drupal_id": 273, "orcid_id": "0000-0003-0395-3192", "website": "http://www.ii.uib.no/vis/team/hauser/", "firstname": "Helwig", "lastname": "Hauser", "searchname": "Helwig Hauser", "is_teacher": false, "name": "Helwig Hauser", "publications": [ "a-2001-ah", "balabanian-2008-hvv", "borgo-2013-gly", "Bruckner-2003-The", "Buerger-2007-cmv", "Buerger-2007-eurovis", "buerger-2007-star", "Csebfalvi-2001-Fas", "Csebfalvi-2001-NPVR", "daae-lampe-2010-dif", "Freiler-2008-Set", "fuchs_raphael_2007_par", "fuchs-vom-2009", "Groeller_2016_P2", "Hadwiger-2002-Fas", "Hadwiger-2003-MIP", "Hauser-1999-SSI", "Hauser-2000-Tho", "Hauser-2000-Two", "Hauser-2000-TwoX", "Hauser-2002-SSI", "Hauser-2003-Acc", "Hauser-thesis", "Kehrer-2008-hyp", "Kehrer-2010-mom", "kehrer-2011-vai", "Kehrer-2013-STAR", "Kolesar-Fractional-2016", "kolesar-ivan-2014-polymers", "konyha_2006_int", "Konyha_2007_SCV", "Konyha_2009_survey", "Konyha-2003-Int", "Ladstaedter-2010-exp", "lie-2009-cri", "matkovic_2009_flickr", "Matkovic-2002-Pro", "matkovic-2005-multi", "matkovic-2007-clv", "Matkovic-2008-ComVis", "Matkovic-2008-Steer", "Matkovic-2014-ieee", "Mattausch-2003-SIE", "Mattausch-2003-Str", "Mroz-1999-IHQ", "Mroz-2000-Int", "Muigg-2008-four", "oeltze-2013-tut", "patel-2009-kav", "piringer-2009-hds", "Shi_2007_PathLines", "shi-2007-pla", "Theussl-2000-MWI", "vad_viktor-2017-WVE", "Viola_Ivan_2013_GS", "Viola_Ivan_2013_HQ3", "Viola_Ivan_IIP", "WIMMER-2006-CES" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "doleisch-thesis", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "freiler-2008-ste", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "fuchs-vortex", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Hadwiger-thesis", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "Kehrer-2007-Mas", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Kehrer-2011-PhD", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Konyha_2013_IVA", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Konyha_2013_IVA", "field_id": "reviewer_2", "ordernum": 0 }, { "publ_id": "Laramee-2004-thesis", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "mantler-2007-rtv", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "miao_thesis_2019", "field_id": "reviewer_1", "ordernum": 0 }, { "publ_id": "Muehlbacher_diss_2018", "field_id": "reviewer_1", "ordernum": 0 }, { "publ_id": "oeltze-2013-tut", "field_id": "lecturer", "ordernum": 1 }, { "publ_id": "patel-2009-evr", "field_id": "supervisor", "ordernum": 1 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=176", "__class": "Author" } ], "issn": "1077-2626", "journal": "IEEE Transactions on Visualization and Computer Graphics", "note": "Spotlight paper of the March issue of TVCG", "number": "3", "pages_from": "495", "pages_to": "513", "volume": "19", "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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"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" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2013/Kehrer-2013-STAR/", "__class": "Publication" }, { "id": "kehrer-2013-IVA", "type_id": "talk", "tu_id": null, "repositum_id": null, "title": "Visual Analysis of Multi-faceted Scientific Data: Challenges and Trends", "date": "2013", "abstract": "", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "authors": [ { "id": 983, "drupal_id": 629, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/JohannesKehrer", "firstname": "Johannes", "lastname": "Kehrer", "searchname": "Johannes Kehrer", "is_teacher": false, "name": "Johannes Kehrer", "publications": [ "beham-2014-cupid", "borgo-2013-gly", "daae-lampe-2010-dif", "Kehrer-2007-Mas", "Kehrer-2008-hyp", "Kehrer-2010-mom", "Kehrer-2011-PhD", "kehrer-2011-vai", "kehrer-2012-mod", "kehrer-2013-IVA", "kehrer-2013-SBC", "Kehrer-2013-STAR", "Kehrer-2014-CSD", "Ladstaedter-2009-sim", "Ladstaedter-2010-exp", "lie-2009-cri", "Muigg-2008-four", "oeltze-2013-tut", "TR1862162" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "Beham_Michael_PSC", "field_id": "supervisor", "ordernum": 1 }, { "publ_id": "borgo-2013-gly", "field_id": "lecturer", "ordernum": 1 }, { "publ_id": "Kehrer-2008-hyp", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Kehrer-2010-mom", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "kehrer-2011-vai", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "kehrer-2012-mod", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "kehrer-2013-SBC", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "oeltze-2013-tut", "field_id": "lecturer", "ordernum": 2 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=983", "__class": "Author" } ], "date_from": "2013-10-25", "event": "Karlsruhe Institute of Technology", "location": "Karlsruhe, Germany", "research_areas": [], "keywords": [], "weblinks": [], "files": [], "projects_workgroups": [ { "id": "ViMaL", "workgroup_id": "vis", "drupal_id": 4222, "name": "ViMaL: A Visualization Mapping Language", "name_de": null, "website": null, "status": "active", "short_abstract": "Visualization is the discipline dealing with the depiction of data. The assignment of visual abstractions to data abstractions is referred to as the visualization mapping. \nExpressive visualization mappings proofed in many cases to be more effective than the examination of raw data (i.e., large tables of numbers). Although visualization mapping is a crucial step in the visualization pipeline surprisingly few general approaches exist.\nWe propose to develop the Visualization Mapping Language (ViMaL) that is capable of describing expressive visualization mappings and provides user interfaces suitable for non-experts in visualization. \nViMaL will be a language that is used to specify visualization pipelines. We will provide language concepts for the specification of data abstraction processes, visual concretization processes and the required visualization mapping. With this approach the semantics of a specific domain are modeled by the domain experts while the semantics of the visualization domain are modeled by the visualization expert. The visualization mapping is described using domain semantics as well as visualization semantics. Unlike other general purpose visualization systems, ViMaL systems explicitly use the semantics of the visualization mapping process. It incorporates information and knowledge assisted methods in the visualization mapping pipeline.\nIn the scope of this project we will define a novel Visualization Mapping Language and implement a toolbox that aids researchers from other areas to integrate the ViMaL concepts into their systems. The toolbox will provide basic ViMaL document setup and parsing as well as components for each step in the visualization pipeline. We will make use of fuzzy logic in our components for the abstraction of data, for the visual concretization, and for the visualization mapping. \nWe believe that the formalization of the visualization pipeline that is achieved with the visualization mapping language will enable many researchers from other domains to benefit from existing visualization methods. Further, the introduction of domain and visualization semantics for the specification of visualization mappings enables meta-visualization approaches that provide insight into the visualization process itself. Laypersons will benefit from such meta-visualization systems that are able to illustrate the involved components.", "abstract": "Visualization is the discipline dealing with the depiction of data. The assignment of visual abstractions to data abstractions is referred to as the visualization mapping. \nExpressive visualization mappings proofed in many cases to be more effective than the examination of raw data (i.e., large tables of numbers). Although visualization mapping is a crucial step in the visualization pipeline surprisingly few general approaches exist.\nWe propose to develop the Visualization Mapping Language (ViMaL) that is capable of describing expressive visualization mappings and provides user interfaces suitable for non-experts in visualization. \nViMaL will be a language that is used to specify visualization pipelines. We will provide language concepts for the specification of data abstraction processes, visual concretization processes and the required visualization mapping. With this approach the semantics of a specific domain are modeled by the domain experts while the semantics of the visualization domain are modeled by the visualization expert. The visualization mapping is described using domain semantics as well as visualization semantics. Unlike other general purpose visualization systems, ViMaL systems explicitly use the semantics of the visualization mapping process. It incorporates information and knowledge assisted methods in the visualization mapping pipeline.\nIn the scope of this project we will define a novel Visualization Mapping Language and implement a toolbox that aids researchers from other areas to integrate the ViMaL concepts into their systems. The toolbox will provide basic ViMaL document setup and parsing as well as components for each step in the visualization pipeline. We will make use of fuzzy logic in our components for the abstraction of data, for the visual concretization, and for the visualization mapping. \nWe believe that the formalization of the visualization pipeline that is achieved with the visualization mapping language will enable many researchers from other domains to benefit from existing visualization methods. Further, the introduction of domain and visualization semantics for the specification of visualization mappings enables meta-visualization approaches that provide insight into the visualization process itself. Laypersons will benefit from such meta-visualization systems that are able to illustrate the involved components.", "start_date": "2010-01-01", "end_date": "2014-12-31", "leader_id": 166, "logo": { "name": "logo.png", "path": "project:ViMaL", "type": "image/png", "size": 51461, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/ViMaL/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "P 21695-N23", "comment": null } ], "research_areas": [], "publications": [ "beham-2014-cupid", "Birkeland-2012-IMC", "borgo-2013-gly", "bruckner-2010-HVC", "Csebfalvi-2012-IOM", "Groeller_2011_NR", "Herghelegiu-2012-BPV", "kehrer-2013-IVA", "kehrer-2013-SBC", "Kehrer-2014-CSD", "Labschuetz_Matthias_2016_JIT", "Labschuetz_Matthias_2016_JITT", "mindek_peter-2014-cs_kaust", "mindek-2013-cs_cvut", "mindek-2013-csl", "mindek-2013-pel", "mindek-2014-mcs", "mindek-2014-vivi_cvut", "mindek-2015-mctalk", "mindek-thesis", "oeltze-2013-tut", "Peter_2012_AIV", "rautek2010", "Ropinski-2012-UBT", "schmidt-phd", "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", "Soros_AVN_2011", "vaico", "ymca" ], "url": "https://www.cg.tuwien.ac.at/research/projects/ViMaL", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2013/kehrer-2013-IVA/", "__class": "Publication" }, { "id": "kehrer-2011-vai", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "Interactive Visual Analysis of Heterogeneous Scientific Data across an Interface", "date": "2011-07", "abstract": "In this paper, we present a systematic approach to the interactive visual exploration and analysis of heterogeneous scientific\r\ndata. Based on a setup of coordinated multiple views (with linking and brushing) and heterogeneous data which consists of two blocks\r\nof scientific data (e.g., 2D and 3D data), we enable the joint, feature-based investigation across an interface. The interface specifies\r\n(a) which items in the one part of the data are related to which items in the other part, and vice versa, (b) how selections (in terms\r\nof feature extraction) are transferred between the two parts of the data, and (c) how interaction is realized during the visual analysis.\r\nWe also propose strategies for visual analysis across an interface resulting in interactive and iterative refinement of features specified\r\nin different parts of the data. We demonstrate the usefulness of our approach in the context of two visual analysis scenarios with\r\nheterogeneous scientific data, i.e., a multi-run climate simulation and a complex simulation of fluid-structure interaction.", "authors_et_al": false, "substitute": null, "main_image": { "description": "", "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1053, "image_height": 1000, "name": "kehrer-2011-vai-image.jpg", "type": "image/jpeg", "size": 242521, "path": "Publication:kehrer-2011-vai", "url": "https://www.cg.tuwien.ac.at/research/publications/2011/kehrer-2011-vai/kehrer-2011-vai-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2011/kehrer-2011-vai/kehrer-2011-vai-image:thumb{{size}}.png" }, "sync_repositum_override": null, "authors": [ { "id": 983, "drupal_id": 629, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/JohannesKehrer", 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"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" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2011/kehrer-2011-vai/", "__class": "Publication" }, { "id": "Kehrer-2007-Mas", "type_id": "masterthesis", "tu_id": null, "repositum_id": null, "title": "Integrating Interactive Visual Analysis of Large Time Series Data into the SimVis System", "date": "2007-10", "abstract": "Massive amounts of complex time-dependent information arise in various areas of business, science and engineering. These time series datasets commonly result from the measurement, modeling or the simulation of dynamic processes and contain multiple attributes changing over time. Examples are meteorological data, climate data, financial data, census data, or medical data, to name a few.\r\n\r\nIn this thesis the CurveView for the enhanced interactive visual analysis of multidimensional and large time series data is presented. Two approaches are proposed, one for the interactive visual representation of the data, and so-called brushing techniques allowing the user to select certain interesting subsets of the data (i.e., features) in an intuitive and interactive way. The goals are to enable analysts to gain insight into their data sets, to create, verify or reject hypotheses based on the data, and to explore the temporal evolution of different attributes in order to detect expected structures and to discover unexpected features. The presented solution is integrated into SimVis, a multiple-views system for the visual analysis of time-dependent simulation results.\r\n\r\nThe data is visualized using focus+context visualization techniques: important or selected portions of the data (focus) are visually accented, while the rest of the data (context) is shown in a less prominent style. In doing so, enhanced navigation and orientation is provided to the user. By the application of customizable transfer functions, general data trends, visual structures and patterns can be emphasized even within dense regions of the visualization. On the other hand, so-called outliers, which denote time series in low populated areas of the display or important (ie, brushed) data items hidden in regions of context information, are discriminable in the visualization. By the application of binning techniques large amounts of time-dependent information are transformed into a reduced but still meaningful representation which can be depicted at interactive frame rates.\r\n\r\nFurthermore, interactive brushing techniques are provided to the user for analysis purposes. Thus, complex time-dependent features can be specified by applying fuzzy classification to the time series data. Two kinds of brushes exist in the CurveView: similarity-based brushes where time series are classified according to their similarity to a user-defined pattern directly sketched in the view; and time step brushes, which select time series running through a certain area of the view. In SimVis, the interrelations between the specified features in multiple time-dependent dimensions can be analyzed visually using multiple linked views that show different attributes (i.e., dimensions) of the data.", "authors_et_al": false, "substitute": null, "main_image": { "description": "", "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 690, "image_height": 648, "name": "Kehrer-2007-Mas-image.jpg", "type": "image/jpeg", "size": 101131, "path": "Publication:Kehrer-2007-Mas", "url": "https://www.cg.tuwien.ac.at/research/publications/2007/Kehrer-2007-Mas/Kehrer-2007-Mas-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2007/Kehrer-2007-Mas/Kehrer-2007-Mas-image:thumb{{size}}.png" }, "sync_repositum_override": null, "authors": [ { "id": 983, "drupal_id": 629, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/JohannesKehrer", "firstname": 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