Share, publish, and archive your data. Find and cite data across all research fields

Select the collection, from the scrolling list below, in which you want to add a dataset or create a dataset at the main level of LibraData with the "Add Data" button below.
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

1 to 10 of 718 Results
Particle Image Velocimetry for Bio-Inspired Vortex, Fin, and Boundary Interactions
Apr 30, 2026 - School of Engineering and Applied Science
Zhu, Yuanhang; Ormonde, Pedro C.; Liu, Leo; Pan, Yu; Westfall, Elizabeth; Han, Tianjun; Zhu, Joseph; Zhong, Qiang; Bart-Smith, Hilary; Dong, Haibo; Lauder, George V.; Moored, Keith W.; Quinn, Daniel B., 2025, "Particle Image Velocimetry for Bio-Inspired Vortex, Fin, and Boundary Interactions", https://doi.org/10.18130/V3/UL6CJE, University of Virginia Dataverse, V4
Particle Image Velocimetry for Bio-Inspired Vortex, Fin, and Boundary Interactions.
Synthetic Population for Washington, US (ver. 2.4.0)
Apr 30, 2026 - Biocomplexity Institute & Initiative
Mortveit, Henning S.; Adiga, Abhijin; Baek, Hannah; Bhattacharya, Parantapa; Eubank, Stephen; Machi, Dustin; Marathe, Madhav; Porebski, Przemyslaw; Swarup, Samarth; Venkatramanan, Srinivasan; Wilson, Mandy; Xie, Dawen, 2024, "Synthetic Population for Washington, US (ver. 2.4.0)", https://doi.org/10.18130/V3/PNGMRJ, University of Virginia Dataverse, V2, UNF:6:i+YB7Rre5h9cv3VjPNxfew== [fileUNF]
The synthetic population for the state of Washington is constructed to be statistically indistinguishable from the real population at the spatial resolution of a US block group as measured by the US Census on selected demographic variables, which in this case are age (AGEP), household income (HINCP), household size (NP), race (RAC1P) and hispanic (...
Synthetic Population for Georgia, US (ver. 2.4.0)
Apr 30, 2026 - Biocomplexity Institute & Initiative
Mortveit, Henning S.; Adiga, Abhijin; Baek, Hannah; Bhattacharya, Parantapa; Eubank, Stephen; Machi, Dustin; Marathe, Madhav; Porebski, Przemyslaw; Swarup, Samarth; Venkatramanan, Srinivasan; Wilson, Mandy; Xie, Dawen, 2025, "Synthetic Population for Georgia, US (ver. 2.4.0)", https://doi.org/10.18130/V3/4DWNRH, University of Virginia Dataverse, V2, UNF:6:i+YB7Rre5h9cv3VjPNxfew== [fileUNF]
The synthetic population for the state of Georgia is constructed to be statistically indistinguishable from the real population at the spatial resolution of a US block group as measured by the US Census on selected demographic variables, which in this case are age (AGEP), household income (HINCP), household size (NP), race (RAC1P) and hispanic (HIS...
Synthetic Population for Massachusetts, US (ver. 2.4.0)
Apr 29, 2026 - Biocomplexity Institute & Initiative
Mortveit, Henning S.; Adiga, Abhijin; Baek, Hannah; Bhattacharya, Parantapa; Eubank, Stephen; Machi, Dustin; Marathe, Madhav; Porebski, Przemyslaw; Swarup, Samarth; Venkatramanan, Srinivasan; Wilson, Mandy; Xie, Dawen, 2025, "Synthetic Population for Massachusetts, US (ver. 2.4.0)", https://doi.org/10.18130/V3/ZB0SGL, University of Virginia Dataverse, V2, UNF:6:i+YB7Rre5h9cv3VjPNxfew== [fileUNF]
The synthetic population for the state of Massachusetts is constructed to be statistically indistinguishable from the real population at the spatial resolution of a US block group as measured by the US Census on selected demographic variables, which in this case are age (AGEP), household income (HINCP), household size (NP), race (RAC1P) and hispani...
Synthetic Population for Minnesota, US (ver. 2.4.0)
Apr 29, 2026 - Biocomplexity Institute & Initiative
Mortveit, Henning S.; Adiga, Abhijin; Baek, Hannah; Bhattacharya, Parantapa; Eubank, Stephen; Machi, Dustin; Marathe, Madhav; Porebski, Przemyslaw; Swarup, Samarth; Venkatramanan, Srinivasan; Wilson, Mandy; Xie, Dawen, 2025, "Synthetic Population for Minnesota, US (ver. 2.4.0)", https://doi.org/10.18130/V3/SB2PWT, University of Virginia Dataverse, V2, UNF:6:i+YB7Rre5h9cv3VjPNxfew== [fileUNF]
The synthetic population for the state of Minnesota is constructed to be statistically indistinguishable from the real population at the spatial resolution of a US block group as measured by the US Census on selected demographic variables, which in this case are age (AGEP), household income (HINCP), household size (NP), race (RAC1P) and hispanic (H...
Synthetic Population for Virginia, US (ver. 2.4.0)
Apr 28, 2026 - Biocomplexity Institute & Initiative
Mortveit, Henning S.; Adiga, Abhijin; Baek, Hannah; Bhattacharya, Parantapa; Eubank, Stephen; Machi, Dustin; Marathe, Madhav; Porebski, Przemyslaw; Swarup, Samarth; Venkatramanan, Srinivasan; Wilson, Mandy; Xie, Dawen, 2024, "Synthetic Population for Virginia, US (ver. 2.4.0)", https://doi.org/10.18130/V3/5LSDCY, University of Virginia Dataverse, V2, UNF:6:i+YB7Rre5h9cv3VjPNxfew== [fileUNF]
The synthetic population for the state of Virginia is constructed to be statistically indistinguishable from the real population at the spatial resolution of a US block group as measured by the US Census on selected demographic variables, which in this case are age (AGEP), household income (HINCP), household size (NP), race (RAC1P) and hispanic (HI...
Optimizing Machine Learning Approaches to Explore Binary Metallic Alloys for Active Cooling Applications
Apr 26, 2026
Das, Sree Sourav, 2026, "Optimizing Machine Learning Approaches to Explore Binary Metallic Alloys for Active Cooling Applications", https://doi.org/10.18130/V3/7NYJAE, University of Virginia Dataverse, V1
Data as a part of data sharing for journal publication
A global dataset of household-level water, sanitation, and hygiene (WASH) predicted conditions
Apr 22, 2026 - School of Engineering and Applied Science
Fang, Bin, 2026, "A global dataset of household-level water, sanitation, and hygiene (WASH) predicted conditions", https://doi.org/10.18130/V3/O58DEE, University of Virginia Dataverse, V3
The dataset includes GeoTIFF raster layers representing the predicted probability of each ordinal class. Files are named using a standardized convention that encodes the WASH component and ordinal class name.
Code for modeling WASH components by RTMB
Apr 22, 2026 - School of Engineering and Applied Science
Fang, Bin, 2026, "Code for modeling WASH components by RTMB", https://doi.org/10.18130/V3/ED1WNW, University of Virginia Dataverse, V3
The repository contains two R code files: data preprocessing and model/prediction/evaluation files.
Data Manifest for Collaborative Hospital Repository Uniting Standards (CHoRUS) April 2026
Apr 21, 2026 - School of Medicine
Rosenthal, Eric S.; Kamaleswaran, Rishikesan; Strekalova, Yulia Levites; Williams, Andrew E.; Cordes, Ashley; Williams, Ishan C.; Rashidi, Parisa; Evans, Barbara J.; Moorman, J. Randall; Park, Soojin; Amorim, Edilberto; Vespa, Paul M.; Jiang, Xiaoqian; Liu, Hongfang; Podgoreanu, Mihai V.; Herasevich, Vitaly; Wainwright, Mark; Barros, Andrew J.; Sullivan, Brynne A.; Young, Michael J.; Alvarez, Marta; Talapova, Polina; Muszynski, Jennifer A.; Gent, Alasdair; Bold, Delgersuren; Kwong, Manlik; Gunda, Dileep; Le, Jackie; Loar, India; Gow, Brian J.; Schmidt, Heidi; Houghtaling, Jared; Miller, Robert T.; Clark, Timothy; Ashe, William B.; Pan, Tony C.; Pollard, Tom J.; McCrary, Ciera; Bihorac, Azra; Hu, Xiao; Clermont, Gilles, 2026, "Data Manifest for Collaborative Hospital Repository Uniting Standards (CHoRUS) April 2026", https://doi.org/10.18130/V3/XNBOPG, University of Virginia Dataverse, V1
Access Protected Enclave Data: http://chorus4ai.org/dataset The Collaborative Hospital Repository Uniting Standards (CHoRUS) for Clinical Care AI is a clinical data network developing a flagship multi-hospital, multimodal, high-resolution dataset under the NIH Bridge2AI program. CHoRUS harmonizes electronic health record (EHR) data, imaging, high-r...
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.