1 to 10 of 84 Results
Oct 6, 2025 - SFB-TRR 161 INF "Collaboration Infrastructure"
Garkov, Dimitar; Piselli, Tommaso; Di Giacomo, Emilio; Klein, Karsten; Liotta, Giuseppe; Montecchiani, Fabrizio; Schreiber, Falk, 2024, "Collaborative Problem Solving in Mixed Reality: A Study on Visual Graph Analysis - Replication data", https://doi.org/10.18419/DARUS-4231, DaRUS, V2
This dataset contains the supplementary materials to our publication "Collaborative Problem Solving in Mixed Reality: A Study on Visual Graph Analysis", where we report on a study we conducted. Please refer to publication for more details, also the abstract can be found at the end of this description. The dataset contains: The collection of graphs... |
Sep 3, 2025 - SFB-TRR 161 A07 "Visual Attention Modeling for Optimization of Information Visualizations"
Wang, Yao; Zhang, Lin; Zhang, Ying; Kerle-Malcharek, Wilhelm; Klein, Karsten; Schreiber, Falk; Bulling, Andreas, 2025, "Replication Data for: Towards a Better Understanding of Graph Perception in Immersive Environments", https://doi.org/10.18419/DARUS-5259, DaRUS, V1
As Immersive Analytics (IA) increasingly uses Virtual Reality (VR) for stereoscopic 3D (S3D) graph visualisation, it is crucial to understand how users perceive network structures in these immersive environments. However, little is known about how humans read S3D graphs during task solving, and how gaze behaviour indicates task performance. To addr... |
Aug 5, 2025 - SFB-TRR 161 A03 "Quantification of Visual Analytics Transformations and Mappings"
Joos, Lucas; Mooney, Gavin James; Fischer, Maximilian; Keim, Daniel; Schreiber, Falk; Purchase, Helen; Klein, Karsten, 2025, "Replication Data for: "Show Me Your Best Side: Characteristics of User-Preferred Perspectives for 3D Graph Drawings"", https://doi.org/10.18419/DARUS-5108, DaRUS, V1
We provide the supplemental material for our paper 'Show Me Your Best Side: Characteristics of User-Preferred Perspectives for 3D Graph Drawings', allowing additional analysis and replication. The files and collections are described in 'README.txt'. |
Jun 11, 2025 - SFB-TRR 161 INF "Collaboration Infrastructure"
Garkov, Dimitar; Lein, Etienne; Kielkopf, Niklas; Dullin, Christian; Klein, Karsten; Sommer, Bjorn; Jordan, Alex; Schreiber, Falk, 2025, "Software and Data for: Interactive delineation and quantification of anatomical structure with virtual reality", https://doi.org/10.18419/DARUS-4779, DaRUS, V1
This dataset contains the supplemental materials, the used tools, and the release of the software presented in the paper Interactive delineation and quantification of anatomical structure with virtual reality. The dataset is structured in the typical order of data processing: Imaging Tomographic Reconstruction Brainacle Software (Delineation, Quant... |
May 14, 2025 - SFB-TRR 161 B04 "Adaptive Algorithms for Motion Estimation"
Schmalfuss, Jenny; Oei, Victor; Mehl, Lukas; Bartsch, Madlen; Agnihotri, Shashank; Keuper, Margret; Bruhn, Andres, 2025, "RobustSpring: Benchmarking Robustness to Image Corruptions for Optical Flow, Scene Flow and Stereo", https://doi.org/10.18419/DARUS-5047, DaRUS, V1
The RobustSpring dataset contains the image corruption data files for scene flow, optical flow and stereo estimation with the Spring dataset. Note that this repository contains only the Spring test data files. For easier handling, we organized them into sub-directories by image corruption type: brightness.zip : brightness image corruption contrast.... |
May 14, 2025 - SFB-TRR 161 INF "Collaboration Infrastructure"
Müller, Christoph; Ertl, Thomas, 2024, "Performance Data for the Visualisation of Time-Dependent Particles using DirectStorage", https://doi.org/10.18419/DARUS-4017, DaRUS, V2
Results of a series of performance measurements (frame times) to determine the impact of using the DirectStorage API for rendering time-dependent particle data sets in contrast to using traditional POSIX-style I/O APIs. |
May 9, 2025 - Visualisierungsinstitut der Universität Stuttgart
Vriend, Sita; Hägele, David; Weiskopf, Daniel, 2025, "Supplemental materials for "Two Empirical Studies on Audiovisual Semiotics of Uncertainty"", https://doi.org/10.18419/DARUS-4137, DaRUS, V1, UNF:6:Zv5hIuIcj79NjLNQkI3uBw== [fileUNF]
We explored the potential of audiovisual semiotics, the use of audiovisual channels, to enhance users' intuitive perception of uncertainty by conducting two user studies. In the first experiment we assessed the intuitiveness of audio/visual pairs. In the second experiment, we investigated the intuitive audiovisual mappings of uncertainty. These sup... |
Nov 22, 2024 - SFB-TRR 161 A07 "Visual Attention Modeling for Optimization of Information Visualizations"
Wang, Yao; Bulling, Andreas, 2024, "SalChartQA: Question-driven Saliency on Information Visualisations (Dataset and Reproduction Data)", https://doi.org/10.18419/DARUS-3884, DaRUS, V2
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 dataset that uses the BubbleView interface as a proxy for human gaze and a q... |
Oct 25, 2024 - SFB-TRR 161 A08 "A Learning-Based Research Methodology for Visualization"
Angerbauer, Katrin; Van Wagoner, Phoenix; Halach, Tim; Vogelsang, Jonas; Hube, Natalie; Smith, Andria Lenae; Keplinger, Ksenia; Sedlmair, Michael, 2024, "Supplemental Material for the Paper: Is it Part of Me? Exploring Experiences of Inclusive Avatar Use For Visible and Invisible Disabilities in Social VR", https://doi.org/10.18419/DARUS-4426, DaRUS, V1
Supplemental Material for the paper titled: " Is it Part of Me? Exploring Experiences of Inclusive Avatar Use For Visible and Invisible Disabilities in Social VR" accepted for presentation at the ASSETS'24 conference. The structure of the folder is as following:
.
└── avatars
|── base avatars # base avatars generated with ReadyPlayer... |
Sep 16, 2024 - SFB-TRR 161 C06 "User-Adaptive Mixed Reality"
Chiossi, Francesco; Haliburton, Luke; Ou, Changkun; Butz, Andreas; Schmidt, Albrecht, 2024, "Dataset for "Short-Form Videos Degrade Our Capacity to Retain Intentions: Effect of Context Switching On Prospective Memory"", https://doi.org/10.18419/DARUS-3327, DaRUS, V1, UNF:6:7FzpUkbNmyXLFXVYJ8abKQ== [fileUNF]
Social media platforms use short, highly engaging videos to catch users’ attention. While the short-form video feeds popularized by TikTok are rapidly spreading to other platforms, we do not yet understand their impact on cognitive functions. We conducted a between-subjects experiment (𝑁 = 60) investigating the impact of engaging with TikTok, Twit... |
