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Dataset results
558 results for “VR”
Head movement and heartbeat data while playing VR games
<p>This dataset was collected while 30 different participants played five different VR games (Aircar, Beat Saber, Moss, Arizona Sunshine, and SUPERHOT). It includes the head movement data, heartbeat data, and SSQ data.</p>
VR Locomotion Taxonomies
<p>Publication of JSON-modelled VR locomotion taxonomies and sources for the extracted locomotion taxonomies (see references).</p> <p> </p> <p> </p>
Multi-objective optimization of equation of state molecular parameters: SAFT-VR Mie models for water
<p>Supporting document containing information on the Pareto points and thermodynamic calculations.</p>
VR Warmia. Stoczek Klasztorny. Sanktuarium
To jest wersja zmniejszona, przygotowana do oglądania w okularach VR, np. Oculus. Warmia. Stoczek Klasztorny. Sanktuarium maryjne. Bazylika Matki Pokoju. Kościół w formie rotundy wybudowano w latach 1639–1641 Digitalizacja zabytkowej architektury na terenie Warmii, w projekcie swietawarmia.pl Source: Objaverse 1.0 / Sketchfab
(VR optimized) Wing part of Wellington bomber
Remains of the starboard wing of a RAF Wellington bomber crashed in the North Sea during WO2 just above the Dutch island Ameland. See also our YouTube report/documentary about this wreck https://www.youtube.com/watch?v=81jExNR-QC8 Source: Objaverse 1.0 / Sketchfab
VR Warmia. Tłokowo. Gotycki kościół
To jest wersja zmniejszona, przygotowana do oglądania w okularach VR, np. Oculus. Poland. Warmia. Tłokowo. Gotycki kościół pw. św. Jana Chrzciciela, wybudowany w latach 1370-1390, przebudowany w 1500 r. Digitalizacja zabytkowej architektury na terenie Warmii, w projekcie swietawarmia.pl Source: Objaverse 1.0 / Sketchfab
HistoryView VR - 3D Matterport Scan
HistoryView VR is the educational platform for teachers & students to access 3D Virtual Reality Field Trips powered by Matterport. Working with museums and historical sites, HistoryView is able to share historical experiences and bring history to life for classrooms worldwide. In connection with Matterport's state of the art technology, HistoryView is able to create virtual reality field trips for education and digitally preserve anthropology. [HistoryView.org](http://HistoryView.org) Source: Objaverse 1.0 / Sketchfab
Vucedolska Golubica VR
AR/VR ready lowpoly 3D model representation of Vučedolska golubica - a hystorical item from Croatia. More info at: https://en.wikipedia.org/wiki/Vu%C4%8Dedol_culture#The_Vu%C4%8Dedol_dove Author: Igor Puškarić, portfolio & contact: https://sketchfab.com/iggy-design Developed for Equinox XR, http://equinox.vision Source: Objaverse 1.0 / Sketchfab
The Tavern, Gaspee VR
Photogrammetry test for Sabin's Taver Scene. Captured at Buckman Tavern, Lexington, Massachusetts Captured by Adam Hersko-RonaTas Source: Objaverse 1.0 / Sketchfab
PassengXR VR Headset IMU Drift Data
<p>Files with headset and vehicle-based IMU orientation data, which were compared to determine the level of IMU drift (inaccuracy) in the headset over time. From the measurements reported in "PassengXR: A Low Cost Platform for Any-Car, Multi-User, Motion-Based Passenger XR Experiences" (https://dl.acm.org/doi/10.1145/3526113.3545657)</p>
VR Interaction Techniques for Constrained Transport Spaces
<p>This is the dataset for the study reported in "A Lack of Restraint: Comparing Virtual Reality Interaction Techniques for Constrained Transport Seating": https://ieeexplore.ieee.org/document/10058530</p>
LimeSurvey-Befragung: Authentizitätszuschreibungen in den VR-Anwendungen Blackbox und "Ernst Grube - das Vermächtnis" (Phase II von II, ID435396)
<p>Bei den hier vorliegenden Datensätzen handelt es sich um den Appendix meiner Dissertation "Virtual Reality in Gedenkstätten – Eine empirische Untersuchung zu Authentizitätskonstruktionen". Diese wurde am 30.04.2024 an der Universität zu Köln eingereicht, eine Veröffentlichung steht noch aus.</p> <p>Der Datensatz enthält alle derzeit möglichen Exportformate der Authentizitätszuschreibungen in den VR-Anwendungen Blackbox und "Ernst Grube - das Vermächtnis" (Phase II von II, ID435396). (Limesurvey: Community Edition, Version 5.6.13+230327). Gesichert wurden sowohl die Umfragestruktur, als auch die Statistiken (limesurvey_survey_435396.xls, BERGIS~1.PDF)</p> <p> </p> <p>Die folgenden Beschreibungen wurden wörtlich von https://umfrage.uni-wuppertal.de/ übernommen:</p> <ul> <li><strong>Umfrage-Struktur (*.lss)</strong> <ul> <li>Bei diesem Export werden alle Gruppen, Fragen, Antworten und Bedingungen für Ihre Umfrage in einer .lss-Datei (die im Grunde eine XML-Datei ist) abgelegt. Diese Umfragestruktur kann beim Erstellen einer neuen Umfrage mit der Funktion 'Umfrage importieren' verwendet werden. Eine Umfrage, die ein benutzerdefinierte Designvorlage verwendet, wird zwar importiert, aber die Vorlage, auf die sie verweist,könnte dem neuen Server nicht vorhanden sein. In diesem Fall verwendet das System die globale Standarddesignvorlage.</li> </ul> </li> <li><strong>Umfragearchiv (.lsa)</strong> <ul> <li>Dieser Export soll eine vollständige Sicherung einer aktiven Umfrage zu Archivierungszwecken erstellen. Es enthält die folgenden Daten in einer ZIP-Datei, die mit '.lsa' endet. Umfragestruktur Antwortdaten (Achtung: Enthält keine in eine Datei-Upload-Frage hochgeladenen Dateien. Diese müssen separat exportiert werden.) <ul> <li>Umfrageteilnehmerdaten (wenn verfügbar)</li> <li>Timings (falls aktiviert)</li> <li>queXML Format (*.xml)</li> </ul> </li> <li>queXML ist eine XML-Beschreibung eines Fragebogens. Es ist nicht für die Sicherung einer LimeSurvey-Umfrage geeignet, da es keine Bedingungen exportieren kann und es ist nicht möglich, alle Fragetypen zu exportieren. Durch das Exportieren eines Fragebogens nach queXML können Sie PDF-Dokumente erstellen, die gedruckt, ausgefüllt, gescannt und mit der queXF-Software verarbeitet werden können. Um mehr über queXML zu erfahren, sehen Sie sich diese Seite an: quexml.acspri.org.au.</li> </ul> </li> <li><strong>queXML PDF-Export</strong> <ul> <li>queXML ist eine XML-Beschreibung eines Fragebogens. Auf der folgenden Seite können Sie eine PDF-Datei erstellen, die ausgedruckt und erneut gescannt werden kann. Es ist nicht für die Sicherung einer LimeSurvey-Umfrage geeignet, da es keine Bedingungen exportieren kann und es ist nicht möglich, alle Fragetypen zu exportieren. Um mehr über queXML zu erfahren, klicken Sie auf diese Seite: quexml.acspri.org.au .</li> </ul> </li> <li><strong>Tab-getrennte-Werte Format (*.txt)</strong> <ul> <li>Diese Funktion erleichtert die Verwendung von Excel zum Verfassen und Bearbeiten von Umfragen. Es beseitigt vollständig die Abhängigkeit von SGQA-Codes. Darüber hinaus erleichtert es die Bulk-Bearbeitung Ihrer Umfrage, z. B. Suchen/Ersetzen, Bulk-Neuordnung, Schleifen (sich wiederholende Gruppen) und Testen (z. B. vorübergehende Deaktivierung von Pflicht- oder Validierungskriterien).</li> </ul> </li> <li><strong>Druckbare Umfrageversion (* .html)</strong> <ul> <li>Dadurch wird eine .zip-Datei mit der Umfrage in allen Sprachen heruntergeladen. Es enthält auch die notwendigen Stylesheets, um es auf jedem HTML-fähigen Gerät oder Browser zu anzeigen zu können. Dies wird keine Logik oder EM-Funktionalität enthalten, das müssen Sie selbst berücksichtigen.</li> </ul> </li> </ul>
Postprocessed output from VR-CESM with refinement over the greater Greenland area and a CAM-SE control experiment
<p>This dataset contains post-processed monthly output from two VR-CESM simulations that were performed with CAM5.4 and CLM5, with refinement patches over the greater Greenland area. Data from a standard, quasi-uniform CAM-SE simulations is included as well. These are the data that are analysed and discussed by our paper in The Cryosphere, <a href="https://www.the-cryosphere-discuss.net/tc-2018-257/">https://www.the-cryosphere-discuss.net/tc-2018-257/</a>.</p> <p>The postprocessing involved (A) regridding from the respective unstructured CAM grids to regular latitude-longitude grids to allow for easy plotting and comparison, (B) vertical interpolation of some atmospheric fields to constant pressure levels, and (C) averaging in time to compute climatological means and variances.</p> <p><strong>Contact</strong><br> Leo van Kampenhout (L.vankampenhout@uu.nl)</p> <p><strong>Raw data</strong><br> The raw, ungridded monthly timeseries data are currently available on NCAR's HPSS tape system, under file path /home/lvank/archive_pp, and can be requested through the contact person. There exists also daily data for selected variables.</p> <p><strong>Dataset contents</strong></p> <pre><code>Global_Uniform.tar Global_VR28.tar Global_VR55.tar</code></pre> <p>Atmospheric CAM output regridded to a global regular 1 degree latitude-longitude grid. Variables are PHIS, T200, T500, T700, Z200, Z500, Z700.</p> <pre><code>Greenland_0.25_Uniform.tar Greenland_0.25_VR28.tar Greenland_0.25_VR55.tar</code></pre> <p>Atmospheric CAM output and CLM land model output regridded to a 0.25x0.25 degree grid stretching from 40N - 90N and 100W - 0W. Variables are FLDS, FLNS, FSDS, FSNS, H2OSNO, LHFLX, SHFLX, PHIS, PRECC, PRECL, PRECSC, PRECSL, TGCLDCWP, TREFHT, TSOI_10CM, TS, U10.</p> <pre><code>acab_c2b8_UNI_fdm.004_timmean.nc acab_c2b8_VRGRN_28.005_timmean.nc acab_c2b8_VRGRN_55.005_timmean.nc</code></pre> <p>Downscaled SMB on the 4km CISM grid, in meters of ice equivalent. These files represent time means over the period 1980-1999.</p> <pre><code> cism_thickness.nc </code></pre> <p>CISM ice thickness and ice elevation at 4 km. Note that the ice sheet was non-evolving in our simulations, so both these fields are constant in time.</p>
Replication Kit for the Paper "Alternative Interaction Methods for VR Environments with Leap Motion" submitted to UIST 2019
<p>This file contains the replication kit for the paper "Alternative Interaction Methods for VR Environments with Leap Motion" submitted to the "32nd ACM User Interface Software and Technology Symposium (UIST 2019)". It consists of the Virtual Reality implemented for the case study of the paper as well as all introductory material for participants, measurements, and analysis scripts.</p>
Inputdata for VR_CESM 2.2.beta01.ver3 (ne0np4uoslo30x8)
<p>Input data needed for use with a docker container with the variable resolution CESM</p> <p>From ne30np4 (global mesh) to x8 refinment</p> <p>Resolution ne0uoslone30x8_ne0uoslone30x8_mt12</p> <p>Compset longname is HIST_CAM60_CLM50%BGC_CICE%PRES_DOCN%DOM_MOSART_CISM2%NOEVOLVE_SWAV</p> <p> </p>
Investigating the Auditory Selective Attention Switch using Matrix Sentences in VR
<h2>General</h2> <p>The audio-visual Auditory Selective Attention VR - Long Stimuli (avASAlongStimuli) project serves to investigate the extensions by matrix sentences of a paradigm on the auditory selective attention switch in a close-to-real-life classroom setting. This dataset consists of a Unity project and Matlab code used to collect data on the voluntary switching of auditory selective attention in a virtual reality classroom scenario.</p> <p><strong>The dataset contains:</strong></p> <p> Unity project for audiovisual display and the experiment structure<br> Matlab code for experiment preparation and HpFT measurement<br> Data collected in the experiment (experiment performance, head tracking)</p> <h2>Experiment preparation using Matlab</h2> <p>The code and software used to prepare the experiment is provided in the folder "matlab_avASAlongStimuli".</p> <p>The Matlab code used to prepare the trials for each participant as well as to measure the HpTFs. For the HpTF measurements, the ITA Toolbox for Matlab was used and is provided (https://git.rwth-aachen.de/ita/toolbox). A developmental version of Virtual acoustics (VA) 2022a (https://www.virtualacoustics.org/VA/overview/) is provided.</p> <p><strong>Software requirements:</strong></p> <p> Matlab 2020a or higher<br> ITA Toolbox for Matlab installed</p> <h2><br>Experiment conduction in Unity</h2> <p>The Unity project is provided in the folder "unity_avASAlongStimuli".</p> <p>Therefore, a virtual classroom with some basic furniture is provided. The used models, prefabs and plugins can be found in the Assets folder.</p> <p>The acoustic stimuli for the task were created using Voicemaker (https://voicemaker.in/).</p> <p>This Unity project was intended for the use in virtual reality using an HMD and respective controllers for input. However, it can also be used on a desktop pc. The mode can be changed using the "VRMode" toggle as described below.<br>The audio reproduction is realized using the Unity plugin for Virtual Acoustics (VA, http://www.virtualacoustics.org/ and https://git.rwth-aachen.de/ita/vaunity_package).</p> <p><strong>Software requirements:</strong></p> <p> Unity 2019.4.21.f1.<br> SteamVR 1.19.7<br> Virtual Acoustics v2022a, VAUnity: https://git.rwth-aachen.de/ita/VAUnity</p> <h2><br>Data evaluation</h2> <p>The collected data is provided in the folder "dataEvaluation_avASAlongStimuli". This folder contains two types of data: the raw data collected in the experiment (reaction times and error rates), the head tracking data.</p>
NANCY SNS JU Project - VR Video Streaming & iPerf3 on O-RAN 5G Testbed Dataset
<p>This dataset was developed in the context of the NANCY project and it is the output of the experiments involving streaming a virtual reality (VR) video in a 5G coverage expansion scenario. Additionally, iPerf3 experiments in both TCP and UDP modes were carried out. The coverage expansion scenario involves a main operator and a micro-operator which extends the main operator’s coverage and can also provide additional services.</p> <p>The dataset includes network traffic, which was captured and stored in a .pcap files, as well as various performance metrics that were collected by an xApp running in the near-real-time Radio Access Network Intelligent Controller.</p> <p>The NANCY project has received funding from the Smart Networks and Services Joint Undertaking (SNS JU) under the European Union's Horizon Europe research and innovation programme under Grant Agreement No 101096456.</p>
Investigating the Impact of Visual Stimuli on the Auditory Selective Attention in a VR Classroom
<h2>General</h2> <p>The audio-visual Auditory Selective Attention - visual Priming (avASAvisPrim) project serves to investigate the impact of visual stimuli on auditory selective attention switch in a close-to-real-life classroom setting. This dataset consists of a Unity project and Matlab code used to collect data as well as the collected data and R scripts used for evaluation.</p> <p><strong>The dataset contains:</strong></p> <p> Unity project for audiovisual display and the experiment structure<br> Matlab code for experiment preparation and HpFT measurement<br> Data collected in the experiment (experiment performance)<br> R code for data evaluation</p> <h2>Experiment preparation using Matlab</h2> <p>The code and software used to prepare the experiment is provided in the folder "matlab_avASAvisPrim".</p> <p>The Matlab code used to prepare the trials for each participant as well as to measure the HpTFs. For the HpTF measurements, the ITA Toolbox for Matlab was used and is provided (https://git.rwth-aachen.de/ita/toolbox). A developmental version of Virtual acoustics (VA) 2021a (https://www.virtualacoustics.org/VA/overview/) is provided.</p> <p><strong>Software requirements:</strong></p> <p> Matlab 2020a or higher<br> ITA Toolbox for Matlab installed</p> <h2><br>Experiment conduction in Unity</h2> <p>The Unity project is provided in the folder "unity_avASAvisPrim".</p> <p>Therefore, a virtual classroom with some basic furniture is provided. The used models, prefabs and plugins can be found in the Assets folder.</p> <p>The acoustic stimuli for the task are taken from Loh and Fels 2023 "ChildASA dataset: Speech and Noise Material fpr Child-appropriate Paradigms on Auditory Selective Attention" https://doi.org/10.18154/RWTH-2023-00740. </p> <p>This Unity project was intended for the use in virtual reality using an HMD and respective controllers for input. However, it can also be used on a desktop pc. The mode can be changed using the "VRMode" toggle as described below.<br>The audio reproduction is realized using the Unity plugin for Virtual Acoustics (VA, http://www.virtualacoustics.org/ and https://git.rwth-aachen.de/ita/vaunity_package).</p> <p><strong>Software requirements:</strong></p> <p> Unity 2019.4.21.f1.<br> SteamVR 1.19.7<br> Virtual Acoustics v2021a, VAUnity: https://git.rwth-aachen.de/ita/VAUnity</p> <h2><br>Data evaluation</h2> <p>The collected data is provided in the folder "dataEvaluation_avASAvisPrim". This folder contains three types of data: the raw data collected in the experiment (reaction times and error rates). R code for the evaluation of the head tracking data and the questionnaires is provided.</p>
Experimental data for the study: "Hiding Assistive Robots During Training in Immersive VR Does not Affect Users' Motivation, Presence, Embodiment, and Performance"
<p>The datasets contains the motor performance metrics, the gaze fixation time ratios, and the questionnaire responses for a study involving a motor task with a rehabilitation assistive robot and an immersive virtual reality head-mounted display. The study was performed in the Motor Learning and Neurorehabilitation Laboratory at University of Bern. All data are stored in “csv” files. The variables inside the files are explained in “DataFrameDescription.rtf”. For questions, please contact nicolas.wenk@unibe.ch or L.MarchalCrespo@tudelft.nl.</p>
ISO-VR-Pointing Dataset
<p>This dataset contains the user study data of the paper "Simulating Interaction Movements via Model Predictive Control".</p> <p>Python packages using this data include <a href="https://github.com/aikkala/user-in-the-box">user-in-the-box</a>, <a href="https://github.com/mkl4r/sim-mpc">sim-mpc</a>, and <a href="https://github.com/fl0fischer/cfat">cfat</a>.</p> <p><strong>Note: </strong>The<em> ISO_VR_Pointing_Dataset.zip </em>contains all relevant files. The <em>ISO_VR_Pointing_IK_Raw.zip</em> contains a subset of this dataset with all files required by <a href="https://github.com/fl0fischer/cfat">cfat.</a><br> <br> </p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.