Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
3,853
datasets available to search
ShareScore release 0.7.1
Dataset results
3,853 results for “Video”
DEEPICE Stories Videos series - Insight into Ice & Climate - Videos with English subtitles
<p><em>DEEPICE Stories – Insights into Ice & Climate </em>is a series of 15 videos<em> </em>created in collaboration with the 15 PhD students of the European research project <a href="https://deepice.cnrs.fr/">DEEPICE</a>. These 3-minute educational video clips give an overview of scientific research on ice cores. <a href="https://deepice.cnrs.fr">https://deepice.cnrs.fr</a></p> <p> </p> <p><u>Credits</u></p> <p>Writing & presentation: Geunwoo Lee, Hanne <span>Notø</span>, Eirini <span>Malegiannaki</span>, Piers Larkman, Miguel Angel Sanchez Moreno, Lison Soussaintjean, Florian Painer, Niklas Kappelt, Lisa Ardoin, Inès Ollivier, Romilly Harris Stuart, Fyntan Shaw, Qinggang Gao, Ailsa Chung, Daniel Gunning</p> <p>Coordination : Marie Kazeroni (LSCE-CNRS)</p> <p>Direction: Dorothée Adam-Mazard (Inuaprod) & Marie Kazeroni (LSCE-CNRS)</p> <p>Editing: Thomas d’Aram</p> <p>Motion Design: Pauline Fuchs</p> <p>Co-production: DEEPICE & Inuaprod</p>
Mouse Lockboxes - 3D printing files and videos
<p>This repository contains 3D printable STL files for the mouse lockboxes (LB) and videos of mice solving the lockboxes. Lockboxes are mechanical puzzles consisting of one or more steps, which are baited with a food reward. The mice manipulate the lockboxes on a voluntary basis.</p> <p><strong>LB sets</strong>: Two LB sets were designed, each consisting of four single mechanism LBs (1-step) and a combined mechanism LBs (4-step). For the latter, the fours single mechanisms block each other and have to be removed in the correct order to open the box. The LB can be baited with a food reward to motivate the animals to open them.<br>In the folder titled <em>"LB_solutions"</em>, there are GIFs of each single and combined mechanism LB, which demonstrate how the LBs are supposed to be opened.<br>In the construction manual <em>("Instruction_Manual_Lock_Boxes.pdf")</em>, the STL files for each LB are listed and construction plans are provided. The STL files can be found in the folder titled <em>"LB_sets.zip"</em>.</p> <p><strong>Door system</strong>: The door systems can be used to connect two cages.</p> <p><strong>Printing</strong>: We used an Ultimaker 3 Extended and an Ultimaker S3, 0.4 mm nozzles, and PLA of different colors as material. The gcode was generated with Cura_SteamEngine 4.4.0. Since the mice may gnaw on the LB, it is advisable to choose a higher value for the thickness of walls and top, e.g., 1.5 mm. For most elements, the normal profile (0.15 mm) can be used; for small elements such as the seals, the fine profile is beneficial.</p> <ul> <li>Wall Thickness: 1 mm</li> <li>Wall Line Count: 10</li> <li>Top/Bottom Thickness: 1 mm</li> <li>Top Layers: 10</li> <li>Bottom Layers: 3</li> <li>Infill Density: 20 %</li> <li>Infill Pattern: Triangles</li> <li>Support should be generated for the following elements: LB#1_single_drawer.stl, LB#1_single_cube.stl, LB#1_single_disc.stl, LB#2_single_lever.stl, LB#2_single_stick.stl, LB#1_combined_stick.stl, LB#1_combined_cube.stl, LB#1_combined_disc.stl, LB#2_combined_ lever.stl, LB#2_combined_ stick1.stl, LB#2_combined_ stick2.stl</li> <li>Build Plate Adhesion is necessary for the following elements: LB#1_single_drawer.stl, LB#1_single_lever.stl; LB#1_single_seal1.stl, LB#1_single_cube.stl, LB#1_single_seal2.stl, LB#2_single_lever.stl, LB#2_single_stick.stl, LB#2_single_seal4.stl, LB#2_single_seal5.stl, LB#2_single_seal6.stl, LB#1_combined_stick.stl, LB#1_combined_lever.stl, LB#1_combined_cube.stl, LB#1_combined_seal1.stl, LB#1_combined_seal2.stl, LB#2_combined_lever.stl, LB#2_combined_stick1.stl, LB#2_combined_stick2.stl, LB#2_combined_ball.stl, LB#2_combined_seal3.stl, LB#2_combined_seal6.stl</li> </ul> <p><strong>Videos</strong>: The videos in the folder titled "videos" demonstrate how mice solve the lockboxes.</p>
Compiled version of UniStuttgart-VISUS/tpeqd-rendered-transitions with rendered videos
<p>The compiled static files and the generated data and video for the UniStuttgart-VISUS/tpeqd-rendered-transitions (<a href="https://github.com/UniStuttgart-VISUS/tpeqd-rendered-transitions" target="_blank" rel="noopener">GitHub repository</a>) prototype. The data.zip file needs to be extracted first, such that the data/ directory is placed in the same directory as the other files. The prototype should be viewed in a web browser other than Firefox for now (May 2024) to use the requestVideoFrameCallback API.</p>
UAV-based monocular SLAM video datasets in vineyards with RTK ground truth
<p>The dataset provides a UAV-based monocular visual SLAM data, designed to evaluate the potential of using monocular visual SLAM in vineyards. It includes videos in ".mp4" format collected by UAV, and "xlsx" tables which include latitude, longitude, height, speed in x, y and z, comjpass, pitch, roll. The ".xlsx" tables were measured by RTK and can be used as ground truth of UAV trajectory and pose.</p> <p>This dataset can be combined with other datasets to enable a comprehensive view of the vineyards:</p> <p>Vélez S, Ariza-Sentís M, Valente J. EscaYard: Precision viticulture multimodal dataset of vineyards affected by Esca disease consisting of geotagged smartphone images, phytosanitary status, UAV 3D point clouds and Orthomosaics. Data in Brief. 2024 Jun 1;54:110497. <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.dib.2024.110497" target="_blank" rel="noreferrer noopener"><span>https://doi.org/10.1016/j.dib.2024.110497</span></a></p> <p><span>Ariza-Sentís M, Wang K, Cao Z, Vélez S, Valente J. GrapeMOTS: UAV vineyard dataset with MOTS grape bunch annotations recorded from multiple perspectives for enhanced object detection and tracking. Data in Brief. 2024 Jun 1;54:110432. <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.dib.2024.110432" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.dib.2024.110432</a></span></p> <p> </p> <p> </p>
Videos during training and acquisition of awake Sheep MRI
<p>These videos are provided in support of Pluchot, C., Adriaensen, H., Parias, C. <em>et al.</em> Sheep (<em>Ovis aries</em>) training protocol for voluntary awake and unrestrained structural brain MRI acquisitions. <em>Behav Res</em> (2024). <a href="https://doi.org/10.3758/s13428-024-02449-6" target="_blank" rel="noopener">https://doi.org/10.3758/s13428-024-02449-6</a> . One illustrates our technique to train sheep to lie down, while the other shows the acquisition of a T1-weighted image from an awake and unrestrained sheep.</p> <p>This Version 2 also includes the file Sheepvoice-V3.mp4, which contains footage of several training steps. </p>
Duhumbi Agricultural Practices - Description, Audio, Video, Photos
<p>This collection of videos, audio and photo files displays Duhumbi agricultural practices as they were conducted between 2012 and 2017. Accompanying video and picture files illustrating the text files can be found at the end of this document.</p> <p>Traditionally, the people of the Chug valley depended on a mix of agriculture and animal husbandry for their livelihoods, supplemented by hunting and collection of forest produce. The Chug valley and the Sangthi valley are the only places in West Kameng district where relatively large-scale wetland rice cultivation takes place. This rice has for long been the main item in the barter trade, as well as the main item collected as tax by the erstwhile Tibetan administration and raided by the Miji.</p> <p>Agriculture has always been the main-stay of the local economy, not just in terms of self-sufficiency, but also in terms of barter trade. The agricultural produce, mainly the rice, was bartered for other food and other items, a practice that, despite increasing monetisation of the economic system, continues till date.</p> <p>This material is made freely available to everyone for informative or scientific purposes as long as the source (this DOI) / the collectors are properly credited. Please note that use of the material for commercial purposes <em><strong>of any kind</strong>, which includes conversion into commercial audio-visual media (documentaries etc.), storage and dissemination through sites that require registration & payment for access, or sites that rely on advertisement (including YouTube) </em>is <strong>not</strong> permitted without <strong>specific written consent</strong> from the speakers and their community, obtained through the collectors of the material. By downloading our material, you agree to these restrictions.</p> <p>This data set falls under the Attribution-NonCommercial-ShareAlike (CC BY-NC-SA) license. This license lets you remix, tweak, and build upon this work non-commercially, as long as you credit us and license your new creations under the identical terms. License Deed on <a href="https://creativecommons.org/licenses/by-nc-sa/4.0/">https://creativecommons.org/licenses/by-nc-sa/4.0/</a>. Legal Code on <a href="https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode">https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode</a>.</p> <p>Tim Bodt: bodttim (at) gmail (dot) com</p>
Run 0 video in "Ram pressure stripping in elliptical galaxies – I. The impact of the interstellar medium turbulence"
<p>Run 0 presented in the paper "Ram pressure stripping in elliptical galaxies – I. The impact of the interstellar medium turbulence" (http://adsabs.harvard.edu/abs/2013MNRAS.428..804S or https://doi.org/10.1093/mnras/sts071).</p>
HiperLAM Project Video
<p>This is the Project Video of the HiperLAM Project, describing the laser-based additive manufacturing approach coordinated by Orbotech. The Project focuses upon a LIFT-based process (laser-induced forward transfer) in 2 demonstrator applications, namely Fingerprint sensors and RFID tags. The aim of the project is to demonstrate cost and speed improvements by displacing existing processes with the LIFT-based digital printing technology. </p>
Diversify works. introductory video of Diverfarming H2020 project
<p>Introductory video about H2020 Diverfarming project. We show here the benefits of diversified cropping systems and why Europe needs crop diversification.</p> <p>With the long-term view of increasing diversification and biodiversity in Europe and fostering sustainable development of bioeconomy, the Diverfarming consortium come together to develop and deploy innovative farming and agribusiness strategies. Diverfarming will increase the long-term resilience, sustainability and economic revenues of agriculture across the EU by assessing the real benefits and minimising the limitations, barriers and drawbacks of diversified cropping systems under low-input agronomic practices that are tailor-made to fit the unique characteristics of six EU pedoclimatic regions (Mediterranean south and north, Atlantic central, Continental, Pannonian and Boreal), and by adapting and optimising the downstream value chains organization. This approach will provide: i) increased overall land productivity; ii) more rational use of farm land and farming inputs (water, energy, machinery, fertilisers, pesticides); ii) improved delivery of ecosystem services by increments in biodiversity and soil quality; iii) proper organization of downstream value chains adapted to the new diversified cropping systems with decreased use of energy; and iv) access to new markets and reduced economy risks by adoption of new products in time and space. The diversified cropping systems will be tested in field case studies for major crops within each pedoclimatic region. In the end, Diverfarming focuses on research and innovation for rural development, with emphasis on developing new framework systems and business models adapted to the rural context of each pedoclimatic area of the EU, to foster sustainable growth through adoption of diversification, sustainable practices and efficient use of resources.</p>
Monimuotoistaminen toimii. Introductory video of Diverfarming H2020 project
<p>Introductory video about H2020 Diverfarming project. We show here the benefits of diversified cropping systems and why Europe needs crop diversification.</p> <p>With the long-term view of increasing diversification and biodiversity in Europe and fostering sustainable development of bioeconomy, the Diverfarming consortium come together to develop and deploy innovative farming and agribusiness strategies. Diverfarming will increase the long-term resilience, sustainability and economic revenues of agriculture across the EU by assessing the real benefits and minimising the limitations, barriers and drawbacks of diversified cropping systems under low-input agronomic practices that are tailor-made to fit the unique characteristics of six EU pedoclimatic regions (Mediterranean south and north, Atlantic central, Continental, Pannonian and Boreal), and by adapting and optimising the downstream value chains organization. This approach will provide: i) increased overall land productivity; ii) more rational use of farm land and farming inputs (water, energy, machinery, fertilisers, pesticides); ii) improved delivery of ecosystem services by increments in biodiversity and soil quality; iii) proper organization of downstream value chains adapted to the new diversified cropping systems with decreased use of energy; and iv) access to new markets and reduced economy risks by adoption of new products in time and space. The diversified cropping systems will be tested in field case studies for major crops within each pedoclimatic region. In the end, Diverfarming focuses on research and innovation for rural development, with emphasis on developing new framework systems and business models adapted to the rural context of each pedoclimatic area of the EU, to foster sustainable growth through adoption of diversification, sustainable practices and efficient use of resources.</p>
Diversificare funziona. Introductory video of Diverfarming H2020 project
<p>Introductory video in Italian about H2020 Diverfarming project. We show here the benefits of diversified cropping systems and why Europe needs crop diversification.</p> <p>With the long-term view of increasing diversification and biodiversity in Europe and fostering sustainable development of bioeconomy, the Diverfarming consortium come together to develop and deploy innovative farming and agribusiness strategies. Diverfarming will increase the long-term resilience, sustainability and economic revenues of agriculture across the EU by assessing the real benefits and minimising the limitations, barriers and drawbacks of diversified cropping systems under low-input agronomic practices that are tailor-made to fit the unique characteristics of six EU pedoclimatic regions (Mediterranean south and north, Atlantic central, Continental, Pannonian and Boreal), and by adapting and optimising the downstream value chains organization. This approach will provide: i) increased overall land productivity; ii) more rational use of farm land and farming inputs (water, energy, machinery, fertilisers, pesticides); ii) improved delivery of ecosystem services by increments in biodiversity and soil quality; iii) proper organization of downstream value chains adapted to the new diversified cropping systems with decreased use of energy; and iv) access to new markets and reduced economy risks by adoption of new products in time and space. The diversified cropping systems will be tested in field case studies for major crops within each pedoclimatic region. In the end, Diverfarming focuses on research and innovation for rural development, with emphasis on developing new framework systems and business models adapted to the rural context of each pedoclimatic area of the EU, to foster sustainable growth through adoption of diversification, sustainable practices and efficient use of resources.</p>
Diversify werke. Introductory video of Diverfarming H2020 project
<p>Introductory video in Dutch about H2020 Diverfarming project. We show here the benefits of diversified cropping systems and why Europe needs crop diversification.</p> <p>With the long-term view of increasing diversification and biodiversity in Europe and fostering sustainable development of bioeconomy, the Diverfarming consortium come together to develop and deploy innovative farming and agribusiness strategies. Diverfarming will increase the long-term resilience, sustainability and economic revenues of agriculture across the EU by assessing the real benefits and minimising the limitations, barriers and drawbacks of diversified cropping systems under low-input agronomic practices that are tailor-made to fit the unique characteristics of six EU pedoclimatic regions (Mediterranean south and north, Atlantic central, Continental, Pannonian and Boreal), and by adapting and optimising the downstream value chains organization. This approach will provide: i) increased overall land productivity; ii) more rational use of farm land and farming inputs (water, energy, machinery, fertilisers, pesticides); ii) improved delivery of ecosystem services by increments in biodiversity and soil quality; iii) proper organization of downstream value chains adapted to the new diversified cropping systems with decreased use of energy; and iv) access to new markets and reduced economy risks by adoption of new products in time and space. The diversified cropping systems will be tested in field case studies for major crops within each pedoclimatic region. In the end, Diverfarming focuses on research and innovation for rural development, with emphasis on developing new framework systems and business models adapted to the rural context of each pedoclimatic area of the EU, to foster sustainable growth through adoption of diversification, sustainable practices and efficient use of resources.</p>
Diversifikation funktioniert. Introductory video of Diverfarming H2020 project
<p>Introductory video in German about H2020 Diverfarming project. We show here the benefits of diversified cropping systems and why Europe needs crop diversification.</p> <p>With the long-term view of increasing diversification and biodiversity in Europe and fostering sustainable development of bioeconomy, the Diverfarming consortium come together to develop and deploy innovative farming and agribusiness strategies. Diverfarming will increase the long-term resilience, sustainability and economic revenues of agriculture across the EU by assessing the real benefits and minimising the limitations, barriers and drawbacks of diversified cropping systems under low-input agronomic practices that are tailor-made to fit the unique characteristics of six EU pedoclimatic regions (Mediterranean south and north, Atlantic central, Continental, Pannonian and Boreal), and by adapting and optimising the downstream value chains organization. This approach will provide: i) increased overall land productivity; ii) more rational use of farm land and farming inputs (water, energy, machinery, fertilisers, pesticides); ii) improved delivery of ecosystem services by increments in biodiversity and soil quality; iii) proper organization of downstream value chains adapted to the new diversified cropping systems with decreased use of energy; and iv) access to new markets and reduced economy risks by adoption of new products in time and space. The diversified cropping systems will be tested in field case studies for major crops within each pedoclimatic region. In the end, Diverfarming focuses on research and innovation for rural development, with emphasis on developing new framework systems and business models adapted to the rural context of each pedoclimatic area of the EU, to foster sustainable growth through adoption of diversification, sustainable practices and efficient use of resources.</p>
Negative Staining Electron Microscopy Procedure - Video
<p>The Video shows the procedure of negative staining which is used to prepare particles of suspensions for transmission electron microscopy. The procedure is described in a document available at https://zenodo.org/record/1468676.</p>
Video S1 - GEXP02 surface reconstruction
<p>Transgenic Plasmodium falciparum stage III gametocyte expressing GEXP02-HA and PF3D7_0424600-GFP treated with paraformaldehyde and glutaraldehyde and then labeled with antibodies against PF3D7_0936800 (green), HA-tag (red), and GFP-tag (blue). Sections obtained with a confocal microscope were visualized in Imaris and a surface resconstruction of all three channels was obtained.</p>
DOGA Video about Internet Safety
<p>This video presents a webinar developed by Doga (Turkey) and Early Years (North Ireland) about Internet Safety last 5<sup>th</sup> February 2019 within the online conversations of WYRED Project</p>
CVD2014 - A database for evaluating no-reference video quality assessment algorithms
<p>The CVD video database is developed to provide an useful tool for researchers in the validation and developing processes of no-reference (NR) objective video quality assessment (VQA) algorithms. It consists of 234 videos from five different scenes captured by 78 different cameras (mobile phones, compact camera, video camera, SLR). The subjective experiments are conducted following the Single-Stimulus (SS) procedure to collect ratings of video quality.</p> <p><strong>Setup</strong></p> <p>We implement our experiments according to the Single Stimulus methodology using VQone MATLAB toolboxon high quality monitors (Eizo ColorEdge CG241W) with 1920x1200 pixel resolution in a dark room (ambient light < 20 lux). Video stimuli were displayed at their original size of VGA (640 x 480) or HD (1280 x 720). The subjects viewing distance (80 cm) was controlled by a string hanging from a ceiling and they were instructed to keep their head steady next to it. The monitors were calibrated to according to sRGB (target values were: 6500 K, 80 lux, and gamma 2.2) using EyeOne Pro calibrator (X-rite co.). The laboratory setup is showed in the figure below.</p> <p><strong>Subjects</strong></p> <p>Subjects (n = 30, 30, 28, 33, 30, 32 and 27 for Tests 1 - 7 respectively) were naïve in a sense that they did not study or work with image quality or related fields. They were recruited through student mailing lists consisting mainly humanities and behavioral science students. Subjects’ vision was controlled for the near visual acuity, near contrast vision (near F.A.C.T.) and color vision (Farnsworth D15) before the participation. They received movie tickets as a reward.</p> <p><strong>Procedure</strong></p> <p>Subjects evaluated one video sample at a time and all video samples of one scene were presented in a row. The order of video samples and scenes was randomized. Subjects had the option to view video samples again as many times as they wanted.</p> <p><strong>Data</strong></p> <p>The results are processed and reported in the form of Mean Opinion Score (MOS) for the tested video samples. In addition, we provide the whole raw data from the subjective experiments instead of just pre-calculated mean opinion scores from each video sample. This allows further analyses to be made by those who wish to use this database and gives them better opportunity to utilize the data to its full potential.</p> <p>Realignment study (test 7) contains the data from the additional study in which the mappings from the test and scene specific quality scales (test 1-6) to the global quality scale were formed. The global scale is valuable when studying and developing VQA algorithms. With the global scale, all of the samples (234 video samples in the case of the CVD2014) are in the same scale, and the performance analysis for algorithms can be conducted with a high number of samples.</p> <p><strong>If you use this database in your research, we kindly ask that you follow The Copyright notice below and cite the following paper:</strong></p> <p> </p> <p>M. Nuutinen, T. Virtanen, M. Vaahteranoksa, T. Vuori, P. Oittinen and J. Häkkinen, "CVD2014—A Database for Evaluating No-Reference Video Quality Assessment Algorithms," in <em>IEEE Transactions on Image Processing</em>, vol. 25, no. 7, pp. 3073-3086, July 2016. doi: 10.1109/TIP.2016.2562513</p> <p> </p> <p> </p> <p>-----------COPYRIGHT NOTICE STARTS WITH THIS LINE------------</p> <p>Copyright (c) 2014 The University of Helsinki<br> All rights reserved.</p> <p>Permission is hereby granted, without written agreement and without license or royalty fees, to use, copy, modify, and distribute this database (the videos, the images, the results and the source files) and its documentation for any purpose, provided that the copyright notice in its entirely appear in all copies of this database, and the original source of this database,Visual Cognition research group (www.helsinki.fi/psychology/groups/visualcognition/index.htm) and the Institute of Behavioral Science (www.helsinki.fi/ibs/index.html) at the University of Helsinki (www.helsinki.fi/university/), is acknowledged in any publication that reports research using this database. Individual videos and images may not be used outside the scope of this database (e.g. in marketing purposes) without prior permission.</p> <p>The database and our paper are to be cited in the bibliography as: M. Nuutinen, T. Virtanen, M. Vaahteranoksa, T. Vuori, P. Oittinen and J. Häkkinen, "CVD2014—A Database for Evaluating No-Reference Video Quality Assessment Algorithms," in <em>IEEE Transactions on Image Processing</em>, vol. 25, no. 7, pp. 3073-3086, July 2016.<br> doi: 10.1109/TIP.2016.2562513</p> <p>-----------------------------------------------------------------------------</p> <p>LIMITATION OF LIABILITY</p> <p>UNIVERSITY OF HELSINKI SHALL IN NO CASE BE LIABLE IN CONTRACT, TORT OR OTHERWISE FOR ANY LOSS OF REVENUE, PROFIT, BUSINESS OR GOODWILL OR ANY DIRECT, INDIRECT, SPECIAL, CONSEQUENTIAL, INCIDENTAL OR PUNITIVE COST, DAMAGES OR EXPENSE OF ANY KIND HOWEVER CAUSED OR HOWEVER ARISING UNDER OR IN CONNECTION WITH THE USE OF THIS DATABASE.</p> <p>THE UNIVERSITY OF HELSINKI SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE DATABASE PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF HELSINKI HAS NO OBLIGATION TO PROVIDE MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.</p> <p>THIS AGREEMENT SHALL BE CONSTRUED AND INTERPRETED IN ACCORDANCE WITH THE LAWS OF FINLAND, EXCLUDING ITS RULES FOR CHOICE OF LAW.</p> <p>-----------COPYRIGHT NOTICE ENDS WITH THIS LINE------------</p>
FT2 Adler (2) 13-key tenoroon: measurements, photos, endoscopic video
<p> Dataset of FT2 Adler (2) 13-key tenoroon containing detailed external and internal measurements, photos, and an endoscopic video. </p>
VRTogether Pilot 2 Presenter video
<p>Video of the presenter in stereo format and green background for real-time background removal.</p> <p>Codec: H264 - MPEG-4 AVC</p> <p>Dimensions: 1040x600</p> <p>Framerate: 29.97 fps</p> <p>Bitrate: 13500kbps</p> <p>Audio: Stereo 48000 kHz</p>
VRTogether Pilot 2 Howard Anchor video
<p>Video of the news anchor in stereo format.</p> <p>Codec: H264 - MPEG-4 AVC</p> <p>Dimensions: 1536x768</p> <p>Framerate: 30 fps</p> <p>Bitrate: 3579kbps</p> <p>Audio: Stereo 48000 kHz</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.