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1 to 10 of 14 Results
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 22, 2024 - SFB-TRR 161 A07 "Visual Attention Modeling for Optimization of Information Visualizations"
Wang, Yao; Bulling, Andreas, 2024, "Saliency3D: A 3D Saliency Dataset Collected on Screen (Dataset and Experiment Application)", https://doi.org/10.18419/darus-4101, DaRUS, V1
While visual saliency has recently been studied in 3D, the experimental setup for collecting 3D saliency data can be expensive and cumbersome. To address this challenge, we propose a novel experimental design that utilizes an eye tracker on a screen to collect 3D saliency data. O...
Feb 6, 2024 - SFB-TRR 161 B01 "Adaptive Self-Consistent Visualization"
Rodrigues, Nils; Dennig, Frederik L.; Brandt, Vincent; Keim, Daniel; Weiskopf, Daniel, 2024, "Comparative Evaluation of Animated Scatter Plot Transitions - Supplemental Material", https://doi.org/10.18419/darus-3451, DaRUS, V1
We evaluated several animations for transitions between scatter plots in a crowd-sourcing study. We published the results in a paper and provide additional information within this supplemental material. Contents: Tables that did not fit into the original paper, due to page limits...
Feb 6, 2024 - SFB-TRR 161 D04 "Quantitative Aspects of Immersive Analytics for the Life Sciences"
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...
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.
Jan 26, 2024 - SFB-TRR 161 A07 "Visual Attention Modeling for Optimization of Information Visualizations"
Wang, Yao, 2024, "SalChartQA: Question-driven Saliency on Information Visualisations (Dataset and Reproduction Data)", https://doi.org/10.18419/darus-3884, DaRUS, V1
Understanding the link between visual attention and user’s needs when visually exploring information visualisations is under-explored due to a lack of large and diverse datasets to facilitate these analyses. To fill this gap, we introduce SalChartQA - a novel crowd-sourced datase...
Aug 1, 2023 - SFB-TRR 161 D04 "Quantitative Aspects of Immersive Analytics for the Life Sciences"
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,...
Jun 26, 2023 - SFB-TRR 161 A07 "Visual Attention Modeling for Optimization of Information Visualizations"
Wang, Yao, 2023, "Data for: "Scanpath Prediction on Information Visualizations"", https://doi.org/10.18419/darus-3361, DaRUS, V2, UNF:6:cqkNueYjBVCLYaXEqJq3yw== [fileUNF]
We propose Unified Model of Saliency and Scanpaths (UMSS) - a model that learns to predict multi-duration saliency and scanpaths (i.e. sequences of eye fixations) on information visualisations. Although scanpaths provide rich information about the importance of different visualis...
Mar 6, 2023 - SFB-TRR 161 A03 "Quantification of Visual Analytics Transformations and Mappings"
Pomerenke, David; Dennig, Frederik L.; Keim, Daniel; Fuchs, Johannes; Blumenschein, Michael, 2022, "Replication Data for: "Slope-Dependent Rendering of Parallel Coordinates to Reduce Density Distortion and Ghost Clusters"", https://doi.org/10.18419/darus-3060, DaRUS, V2, UNF:6:UBKuKSiQ9Yl4rH7r00rY3g== [fileUNF]
This is the replication data for our publication "Slope-Dependent Rendering of Parallel Coordinates to Reduce Density Distortion and Ghost Clusters." It contains the datasets and the code used to render optimized Parallel Coordinate Plots. We used the following 36 datasets for ou...
Dec 7, 2022 - SFB-TRR 161 A01 "Uncertainty Quantification and Analysis in Visual Computing"
Görtler, Jochen; Spinner, Thilo; Weiskopf, Daniel; Deussen, Oliver, 2022, "Replication Data for: Uncertainty-Aware Principal Component Analysis", https://doi.org/10.18419/darus-2321, DaRUS, V1
This dataset contains the source code for uncertainty-aware principal component analysis (UA-PCA) and a series of images that show dimensionality reduction plots created with UA-PCA. The software is a JavaScript library for performing principal component analysis and dimensionali...
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