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View all- Kajander A(2023)Legal Perspectives on Smart City Data as a CommonsInternational and Comparative Law Review10.2478/iclr-2022-001222:2(7-26)Online publication date: 1-Mar-2023
Data Commons to Support University-Wide Cross Discipline Research
Authors: 
Morgan E. Rodgers, Eric Franz, Alan Chalker, David E. Hudak, Christopher Stewart, Raghu Machiraju, Steve Chang, Cathie SmithAuthors Info & Claims
Article No.: 99, Pages 1 - 2
Abstract
The Translational Data Analytics Institute (TDAI) at the Ohio State University (OSU) aims to promote cross discipline work in order to improve data science and analytics in many areas of university-wide research for use in solving real world problems including areas such as smart city, smart agriculture, and biomedical research. As a result of their interest in promoting transdisciplinary work, TDAI decided that they needed to grapple with the problems of where do researchers get their data and where do they store it for the long term. In particular they were interested in improving the discoverability of and access to data sets that have already been produced by other researchers [1]. To support their mission TDAI envisioned the Data Commons as a website where researchers upload research data sets, curators link data sets together, and researchers visualize and analyze data sets in a data processing environment. Development of this data portal has gone through several phases: requirements gathering, a "ground up" implementation by a local contractor, transfer to the Ohio Supercomputer Center (OSC) for additional development and hosting, and an initial release. Requirements gathering for version 2 is in progress.
References
[1]
Translational Data Analytics Institute. 2019. OSU TDA -- About. Retrieved from https://tdai.osu.edu/about/.
[2]
Translational Data Analytics Institute. 2019. Dataset List. Retrieved from https://datacommons.tdai.osu.edu/.
[3]
Apache Airavata. 2019. Apache Airavata. Retrieved from https://airavata.apache.org/.
[4]
HubZero. 2019. HubZero -- HubZero. Retrieved from https://hubzero.org/.
[5]
Hudak et al., (2018). Open OnDemand: A web-based client portal for HPC centers. Journal of Open Source Software, 3(25), 622.
[6]
Smart Columbus. 2019. Home | Smart Columbus. Retrieved from https://smart.columbus.gov/.
[7]
HydroShare. 2019. Find, Analyze and Share Water Data | CUAHSI HydroShare. Retrieved from https://www.hydroshare.org/.
[8]
CommonsShare. 2019. Heliumdatacommons/commonsshare: CommonsShare is Helium Team's Web User interface that explores using the cloud to access and share FAIR Biomedical big data. Retrieved from https://github.com/heliumdatacommons/commonsshare
[9]
iRODS. 2019. iRODS. Retrieved from https://irods.org/.
[10]
Apache Solr. 2019. Apache Solr. Retrieved from https://lucene.apache.org/solr/.
[11]
Auth0. 2019. Never Compromise on Identity. -- Auth0. Retrieved from https://auth0.com/.
Index Terms
- Data Commons to Support University-Wide Cross Discipline Research
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 28 July 2019
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- Extended-abstract
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- Refereed limited
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PEARC '19
PEARC '19: Practice and Experience in Advanced Research Computing
July 28 - August 1, 2019
IL, Chicago, USA
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Overall Acceptance Rate 133 of 202 submissions, 66%
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View all- Kajander A(2023)Legal Perspectives on Smart City Data as a CommonsInternational and Comparative Law Review10.2478/iclr-2022-001222:2(7-26)Online publication date: 1-Mar-2023
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