A Case for Data Commons: Toward Data Science as a Service
Open accessAbstract
Data commons collocate data, storage, and computing infrastructure with core services and commonly used tools and applications for managing, analyzing, and sharing data to create an interoperable resource for the research community. An architecture for data commons is described, as well as some lessons learned from operating several large-scale data commons.
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The INPC has supported pioneering work developing and using research data commons.
“The INPC has also supported pioneering work developing and using research data commons, which collocate data, storage, and computing infrastructure with commonly used tools for analyzing and sharing data to create an interoperable resource for the research community [48].”
From Evolution of clinical Health Information Exchanges to population health resources: a case study of the Indiana network for patient care (2025) · cites this paper as [48]
The Abstract (page unavailable) supports the sentence’s definition of data commons as collocating data, computing infrastructure, and tools for an interoperable research resource. The OSDC and OCC Data Commons section describes the OCC’s work, but our copy does not identify the INPC or say it supported that work (searched: INPC and the claim’s wording). (LLM, conf=0.85)
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References 25 · Cited by 78
Research works printed but not linked: 13
- [3]Dooley R Software-as-a-Service: The iPlant Foundation API Proc. 5th IEEE Workshop Many-Task Computing on Grids and Supercomputers 2012 https://www.semanticscholar.org/paper/Software-as-a-service-the-Iplant-Foundation-Api-Dooley-Vaughn/ccde19b95773dbb55328f3269fa697a4a7d60e03/pdf
- [4]Foster I Globus Online: Accelerating and Democratizing Science through Cloud-Based Services IEEE Internet Computing 3 2011 70 73
- [5]Simmhan YL Plale B Gannon D A Survey of Data Provenance in E-Science ACM Sigmod Record 34 3 2005 31 36
- [10]Weil SA Ceph: A Scalable, High-Performance Distributed File System Proc. 7th Symp. Operating Systems Design and Implementation 2006 307 320
- [11]Mayernik MS Data Citation Initiatives and Issues Bulletin Am Soc Information Science and Technology 38 5 2012 23 28
- [13]Lagoze C CED 2 AR: The Comprehensive Extensible Data Documentation and Access Repository Proc. IEEE/ACM Joint Conf. Digital Libraries 2014 267 276
- [14]Kunze J Towards Electronic Persistence Using ARK Identifiers Proc. 3rd ECDL Workshop Web Archives 2003 https://wiki.umiacs.umd.edu/adapt/images/0/0a/Arkcdl.pdf
- [20]Mandl D Use of the Earth Observing One (EO-1) Satellite for the Namibia Sensor Web Flood Early Warning Pilot IEEE J Selected Topics in Applied Earth Observations and Remote Sensing 6 2 2013 298 308
- [21]Heath AP Bionimbus: A Cloud for Managing, Analyzing and Sharing Large Genomics Datasets J Am Medical Informatics Assoc 21 6 2014 969 975 PMC4215034 24464852
- [22]Paltoo DN Data Use under the NIH GWAS Data Sharing Policy and Future Directions Nature Genetics 46 9 2014 934 25162809 PMC4182942
- [23]Future Directions for NSF Advanced Computing Infrastructure to Support US Science and Engineering in 2017–2020 Nat’l Academies Press 2016
- [25]Dean J Ghemawat S MapReduce: Simplified Data Processing on Large Clusters Comm ACM 51 1 2008 107 113
- [26]DeCandia G Dynamo: Amazon’s Highly Available Key-Value Store ACM SIGOPS Operating Systems Rev 41 6 2007 205 220
- Authors
- Grossman, R. L., Heath, A., Murphy, M., Patterson, M., & Wells, W.
- Affiliations
- University of Chicago (US)
- Venue
- Computing in Science & Engineering
- Published
- 2016-09
- Volume
- 18
- Issue
- 5
- Pages
- 10-20
- ISSN
- 1521-9615 (ISSN-L)
- PMC
- PMC5636009
- OpenAlex
- W2336067426
- Cited by
- 78
- References
- 25
- Citations by year
- 2026: 4 · 2025: 4 · 2024: 6 · 2023: 12 · 2022: 11 · 2021: 12 · 2020: 5 · 2019: 9 · 2018: 9 · 2017: 4 · 2016: 2
- FWCI
- 15.18
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Computing in Science & Engineering (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Science Foundation
- Ohio State University
- Rice University
- Leidos
- Universiteit van Amsterdam
- National Institutes of Health (HHSN261200800001C)
- Directorate for Computer and Information Science and Engineering
- National Cancer Institute (HHSN261200800001E))
- Office of International Science and Engineering
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Scientific Computing and Data Management
- Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
- Physical Sciences › Computer Science › Computer Networks and Communications › Distributed and Parallel Computing Systems
- Keywords
- data commons, data infrastructure, interoperability, data sharing, data management, data analysis software, research data services
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