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Share, discover, and cite research data from Arizona State University.

The ASU Research Data Repository is a platform for ASU-affiliated researchers to share, preserve, and publish research data in a way that ensures long-term accessibility, usability, and citation. Our team supports researchers in preparing high-quality, well-documented datasets that comply with funder and publisher data sharing requirements.

Curated by ASU Library data professionals, the repository enables global discovery of research data through permanent digital identifiers (DOIs). It is powered by the open-source Dataverse application developed by Harvard University and complements the KEEP Institutional Repository to support the full range of ASU research outputs.

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131 to 140 of 12,668 Results
Plain Text - 6.8 KB - MD5: 3c6209bf293850634a71943fca02477b
Documentation
README
Aug 19, 2025
Peters, Sean; Clarke, Amanda; Erika L Rader, 2022, "The Effects of Unsteady Effusion Rates on Lava Flow Emplacement", https://doi.org/10.48349/ASU/LTWBGY, ASU Library Research Data Repository, V4
This dataset consists of observations from 222 lava flow simulation experiments performed to understand lava flow propagation. The crux of the dataset is two spreadsheets detailing the calculation, observations, and data visualizations from this experimental dataset. Also included are photographs from these experiments taken at the conclusion of ea...
MS Excel Spreadsheet - 1.1 MB - MD5: 7dfdebbe74fe6e410ec474305c4d072f
Data
an Excel spreadsheet containing relevant data for 150 analog experiments conducted under 4 variable extrusion rate conditions
Plain Text - 5.3 KB - MD5: e3fe78f29f552814f3b60d3feeb1fd54
Documentation
README file containing file list, dataset authors, methodology, and other relevant information
MS Excel Spreadsheet - 417.6 KB - MD5: 1563a4bad6b6ad3f97cfc056344e4d87
Data
Spreadsheet of individual experimental runs and subsequent data reduction and analysis for unsteady wax analog flows erupted on variable slopes.
Aug 18, 2025 - Artificial Social Intelligence for Successful Teams (ASIST)
Lixiao Huang; Jared Freeman; Nancy Cooke, 2025, "Artificial Social Intelligence for Successful Teams (ASIST) Study 1 Falcon Testbed Dataset", https://doi.org/10.48349/ASU/1CY5AR, ASU Library Research Data Repository, V1, UNF:6:Moq9o4psJTgh9X5zzFwDbA== [fileUNF]
Artificial Social Intelligence for Successful Teams (ASIST) has a total of 4 studies, with a program overview on this website:https://artificialsocialintelligence.org/ ASIST consists of 13 institutions and more than 300 individual contributors. Arizona State University (ASU) and Aptima as TA3 jointly developed the testbed, integrated requests from...
JSON - 26.4 KB - MD5: e77593bd90f2376c74feccfd98176e22
JSON - 23.6 KB - MD5: 585263bb168072ebb104eae3db9ff526
JSON - 23.6 KB - MD5: cbcfe92f11f9a06bfeb1ce0607880c66
JSON - 61.9 KB - MD5: c647f6f596780cfdc596e427abed3ae7
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