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11 to 20 of 773 Results
Replication Data for: Communicating the Politics of the Law: Legal and Legislative Rhetoric about High Court Decisions
May 19, 2026 - UVA Researchers on Harvard Dataverse
Stone, Andrew; Rivero, Albert, 2026, "Replication Data for: Communicating the Politics of the Law: Legal and Legislative Rhetoric about High Court Decisions", https://doi.org/10.7910/DVN/6UTM1H
Replication data and files for "Communicating the Politics of the Law: Legal and Legislative Rhetoric about High Court Decisions."
This Dataset is harvested from our partners. Clicking the link will take you directly to the archival source of the data.
Replication Data for: Modeling Heart Rate Patterns to Quantify Neonatal Opioid Withdrawal Syndrome
May 19, 2026 - UVA Researchers on Harvard Dataverse
Kausch, Sherry, 2026, "Replication Data for: Modeling Heart Rate Patterns to Quantify Neonatal Opioid Withdrawal Syndrome", https://doi.org/10.7910/DVN/BZGDMV
Anonymized data set for replication of study findings.
This Dataset is harvested from our partners. Clicking the link will take you directly to the archival source of the data.
Published Dataset File
May 18, 2026 - UVA Resource and Data Exchange Public Datasets
Loomba, Johanna, 2026, "Published Dataset File", https://doi.org/10.18130/V3/LFHOUW, University of Virginia Dataverse, V2
This file is being shared here to demostrate the file publishing capabilities of the RDE.
AI-Enabled Synthesis of Open Source Multi-Attribute, Temporal Dataset Related to Data Centers in Virginia
May 18, 2026 - Department of Computer Science
Riya Ghate; Jingran Chen; Aparna Kishore; Madhav V Marathe, 2026, "AI-Enabled Synthesis of Open Source Multi-Attribute, Temporal Dataset Related to Data Centers in Virginia", https://doi.org/10.18130/V3/AYLB4S, University of Virginia Dataverse, V2, UNF:6:Xfi38fbR1I/lROEteajzow== [fileUNF]
Data centers are among the fastest-growing loads on the U.S. electrical grid. Virginia, the world's largest data center market, is an ideal testbed for analyzing energy and infrastructure impacts. However, researchers and policymakers lack open, consistent facility-level data for effective regional planning and impact analysis. Existing datasets ar...
Synthetic Population for California, US (ver. 2.5.0)
May 14, 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, 2026, "Synthetic Population for California, US (ver. 2.5.0)", https://doi.org/10.18130/V3/A7DQWM, University of Virginia Dataverse, V1, UNF:6:i+YB7Rre5h9cv3VjPNxfew== [fileUNF]
The synthetic population for the state of California 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 (...
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...
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