1 to 10 of 33 Results
Becher, Michael; Müller, Christoph; Reina, Guido; Weiskopf, Daniel; Ertl, Thomas, 2024, "Your visualisations are going places: Performance data for scientific visualisation on gaming consoles", https://doi.org/10.18419/darus-4003, DaRUS, V1
The data set contains performance data (mainly frame times) for rendering spherical glyphs and scalar fields on Xbox Series consoles, mobile game consoles and a reference PC with different GPUs. |
Apr 8, 2024 - SFB-TRR 161 A07 "Visual Attention Modeling for Optimization of Information Visualizations"
Wang, Yao; Bulling, Andreas, 2024, "VisRecall++: Analysing and Predicting Recallability of Information Visualisations from Gaze Behaviour (Dataset and Reproduction Data)", https://doi.org/10.18419/darus-3138, DaRUS, V1, UNF:6:NwphGtoYrBQqd2TyRh0OHA== [fileUNF]
This dataset contains stimuli and collected participant data of VisRecall++. The structure of the dataset is described in the README-File. Further, if you are interested in related codes of the publication, you can find a copy of the code repository (see Metadata for Research Sof... |
Mar 13, 2024 - SFB-TRR 161 B01 "Adaptive Self-Consistent Visualization"
Krake, Tim; Klötzl, Daniel; Hägele, David; Weiskopf, Daniel, 2024, "Uncertainty-Aware Seasonal-Trend Decomposition Based on Loess - Supplemental Material", https://doi.org/10.18419/darus-3845, DaRUS, V1
In this supplemental material, we provide the appendix (mathematically exact propagation of uncertainty) and the video material for uncertainty-aware seasonal-trend decomposition based on loess (UASTL). This material complements the main document: The paper on Uncertainty-Aware S... |
Oct 11, 2022 - SFB-TRR 161 B07 "Computational Uncertainty Quantification"
Beschle, Cedric; Barth, Andrea, 2022, "Uncertainty visualization: Fundamentals and recent developments, code to produce data and visuals used in Section 5", https://doi.org/10.18419/darus-3154, DaRUS, V1
Python code to generate the meshes and FEM solutions to Section 5 of the paper Uncertainty visualization: Fundamentals and recent developments. Comments are in the code to explain it. Paraview is used for the visualization. |
Jan 26, 2024 - SFB-TRR 161 A03 "Quantification of Visual Analytics Transformations and Mappings"
Dennig, Frederik L.; Joos, Lucas; Paetzold, Patrick; Blumberg, Daniela; Deussen, Oliver; Keim, Daniel; Fischer, Maximilian T., 2024, "The Categorical Data Map - Replication Data", https://doi.org/10.18419/darus-3372, DaRUS, V1, UNF:6:4NrkBxJKpeeQqsRmi8XRPw== [fileUNF]
Source code and datasets used for our experiments are shared for replication purposes along our publication "The Categorical Data Map". We describe each of the six datasets individually on a per-file basis. All datasets are purely nominal datasets. |
Mikheev, Vladimir; Skukies, Rene; Ehinger, Benedikt, 2023, "Supplementary material: "The Art of Brainwaves: A Survey on Event-Related Potential Visualization Practices"", https://doi.org/10.18419/darus-3729, DaRUS, V2, UNF:6:+qePfVjlqif+DUSlAZSsrw== [fileUNF]
The purpose related to this dataset is to investigate the state of visualization in ERP (Event-Related Potential) research. The investigation was conducted through an online questionnaire administered via LimeSurvey Community Edition v5.4.7, hosted by the University of Stuttgart.... |
Aichem, Michael; Klein, Karsten; Kobourov, Stephen; Schreiber, Falk, 2023, "Supplemental Materials for: "De-emphasise, Aggregate, and Hide: A Study on Interactive Visual Transformations for Group Structures in Network Visualisations"", https://doi.org/10.18419/darus-3706, DaRUS, V2
This dataset contains the supplemental materials for our publication "De-emphasise, Aggregate, and Hide: A Study on Interactive Visual Transformations for Group Structures in Network Visualisations". The publication reports on an experiment that we conducted to explore the effect... |
Feyer, Stefan Paul; Pinaud, Bruno; Kobourov, Stephen; Brich, Nicolas; Krone, Michael; Kerren, Andreas; Schreiber, Falk; Klein, Karsten, 2023, "Supplemental Material: "2D, 2.5D, or 3D? An Exploratory Study on Multilayer Network Visualizations in Virtual Reality"", https://doi.org/10.18419/darus-3387, DaRUS, V1, UNF:6:PSjD1vZ/FkCWAinPKFoFOg== [fileUNF]
Dataset containing supplemental material for the publication "2D, 2.5D, or 3D? An Exploratory Study on Multilayer Network Visualizations in Virtual Reality" This dataset contains: 1) archive containing all raw quantitative results, 2) archive containing all raw qualitative data,... |
Oct 13, 2022 - SFB-TRR 161 A01 "Uncertainty Quantification and Analysis in Visual Computing"
Hägele, David; Krake, Tim; Weiskopf, Daniel, 2022, "Supplemental Material for Uncertainty-Aware Multidimensional Scaling", https://doi.org/10.18419/darus-3104, DaRUS, V1
This dataset contains the supplemental material for "Uncertainty-Aware Multidimensional Scaling". Uncertainty-aware multidimensional scaling (UAMDS) is a nonlinear dimensionality reduction technique for sets of random vectors. This dataset consists of a PDF document that contains... |
Angerbauer, Katrin; Rodrigues, Nils; Cutura, Rene; Öney, Seyda; Pathmanathan, Nelusa; Morariu, Cristina; Weiskopf, Daniel; Sedlmair, Michael, 2022, "Supplemental Material for the paper : Accessibility for Color Vision Deficiencies: Challenges and Findings of a Large Scale Study on Paper Figures", https://doi.org/10.18419/darus-2608, DaRUS, V1, UNF:6:uNArOgq9AXAmdvLcE/mMVA== [fileUNF]
Study data and supplemental material for the paper- Accessibility for Color Vision Deficiencies: Challenges and Findings of a Large Scale Study on Paper Figures presented at CHI 2022. We performed a large scale data study on the color vision deficiency (CVDs) accessibility of pap... |
