At the University of Stuttgart's visualisation research centre, about 30 scientists work in different areas of scientific visualisation, visual analytics, visual computing and computer graphics, as well as in interdisciplinary, applied research. The latter results in close co-operation with non-visualisation disciplines at the University of Stuttgart. This DataVerse contains research data produced by the institute in the aforementioned research areas. For additional data, we recommend also visiting the DataVerse of VIS, which is the visualisation institute of the faculty of computer science, electrical engineering and information technology.
Featured Dataverses

In order to use this feature you must have at least one published or linked dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

Advanced Search

381 to 390 of 558 Results
video.mp4
May 16, 2024 - Dataset for "How Deep Is Your Gaze? Leveraging Distance in Image-Based Gaze Analysis"
MPEG-4 Video - 1.2 MB - MD5: 51edbe11c7c9c497c6e1e6fd159c5e21
World video of trial T07 - Condition: RL at depth level 300cm
video.mp4
May 16, 2024 - Dataset for "How Deep Is Your Gaze? Leveraging Distance in Image-Based Gaze Analysis"
MPEG-4 Video - 2.0 MB - MD5: 79c3bb131c5d508abe6a9e250b767e43
World video of trial T01 - Condition: LR at depth level 300cm
Supplemental Material for "Efficient Sphere Rendering Revisited"
Jun 30, 2023
Gralka, Patrick; Reina, Guido; Ertl, Thomas, 2023, "Supplemental Material for "Efficient Sphere Rendering Revisited"", https://doi.org/10.18419/DARUS-3458, DaRUS, V1, UNF:6:VW7v4J+gjbFfXZ4iHlkqaw== [fileUNF]
This dataset contains the measured rendering times (in milliseconds) for all tested GPUs in the paper "Efficient Sphere Rendering Revisited". The timings have been measured in the visualization software MegaMol on the following hardware: AMD Ryzen 9 5900X (12c @ 4.7GHz); 64GB DDR4 RAM (@ 1,333MHz); AMD Radeon PRO W6800 (22.Q4) 32GB AMD Ryzen 9 5900...
amd_rx6900xt.tab
Jun 30, 2023 - Supplemental Material for "Efficient Sphere Rendering Revisited"
Tabular Data - 2.6 KB - 8 Variables, 40 Observations - UNF:6:Gyd2+hfikqjDrtF9l1chAQ==
amd_w6800.tab
Jun 30, 2023 - Supplemental Material for "Efficient Sphere Rendering Revisited"
Tabular Data - 2.7 KB - 8 Variables, 40 Observations - UNF:6:TXxJmzgVjyazLFvtcnSTYg==
intel_a770.tab
Jun 30, 2023 - Supplemental Material for "Efficient Sphere Rendering Revisited"
Tabular Data - 2.8 KB - 8 Variables, 40 Observations - UNF:6:8hdfrXrMaWcNyXtIGFJLvw==
nvidia_3090ti.tab
Jun 30, 2023 - Supplemental Material for "Efficient Sphere Rendering Revisited"
Tabular Data - 7.8 KB - 8 Variables, 112 Observations - UNF:6:AMlwKgpBjhYNLGclBdwOCA==
nvidia_4090.tab
Jun 30, 2023 - Supplemental Material for "Efficient Sphere Rendering Revisited"
Tabular Data - 7.7 KB - 8 Variables, 112 Observations - UNF:6:1ioGVOXEYxwTn5VbGcJH/g==
Poster for deRSE19 Conference: Software Sustainability for the Open-Source Particle Visualization Framework MegaMol
Jun 6, 2023
Braun, Matthias; Reina, Guido; Ertl, Thomas, 2023, "Poster for deRSE19 Conference: Software Sustainability for the Open-Source Particle Visualization Framework MegaMol", https://doi.org/10.18419/DARUS-3542, DaRUS, V1
MegaMol is an open-source prototyping framework for the interactive visualization of large particle-based data. Its flexible, modular architecture allows it also to serve as development platform for general visualization research. As outlined in the proposal, we planned to improve both the development and the user experience of MegaMol in several w...
deRSE19-Poster.pdf
Jun 6, 2023 - Poster for deRSE19 Conference: Software Sustainability for the Open-Source Particle Visualization Framework MegaMol
Adobe PDF - 3.2 MB - MD5: 99a4ae7dd71ba7273c096e4127be275c
Final Exported Version
Add Data

Log in to create a dataverse or add a dataset.

Log In
Share Dataverse

Share this dataverse on your favorite social media networks.

Link Dataverse
Reset Modifications

Are you sure you want to reset the selected metadata fields? If you do this, any customizations (hidden, required, optional) you have done will no longer appear.