RDAP14: An analysis and characterization of DMPs in NSF proposals from the University of Illinois
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This document analyzes data management plans (DMPs) required for NSF proposals from the University of Illinois, focusing on 1,260 proposals between July 2011 and November 2013. It categorizes DMPs based on storage venues and usage, revealing insights on compliance, partnerships, and best practices. The analysis indicates no significant storage venue advantages between funded and unfunded proposals while noting increased utilization of institutional and disciplinary repositories in more recent submissions.
RDAP14: An analysis and characterization of DMPs in NSF proposals from the University of Illinois
- 1. An Analysis and Characterization of DMPs in NSF Proposals from the University of Illinois RDAP14 Research Data Access & Preservation Summit March 26, 2014 William H. Mischo, Mary C. Schlembach, Megan A. O’Donnell University of Illinois at Urbana-Champaign Iowa State University
- 2. NSF data Management Plans • Data Management Plans (DMPs): required element in NSF proposals, January 2011 • July 2011: the Library, working with the campus Office of Sponsored Programs and Research Administration (OSPRA) began an analysis of DMPs in submitted NSF grant proposals • Currently, looked at 1,600 grants with 1,260 in the analysis.
- 3. Reasons for DMPs • Make key research data available and sharable • Allow the use of data for verification of results and reproducibility of research work • Agency can show significant return on investment to justify funding • We want to know storage venues and mechanisms for sharing and reuse • Also use of local templates and local campus resources such as IDEALS
- 4. Follow-on • Develop campus-wide infrastructure (Research Data Service - RDS) to support UIUC researchers in managing their data • Assist in compliance with federal agencies • Develop important partnerships with campus units (CITES, NCSA, Colleges) and national entities • Develop best practices and standard approaches
- 5. Analysis • Analysis attempts to characterize and classify DMPs into categories • DMPs assigned multiple categories • 1,260 DMPs from July 2011 to November 2013
- 6. Categories • PI Server – Servers and workstations that the PIs (and their students/staff) use to store project data. Examples: laboratory server, external hard drive, and group computer. • PI Website – Websites edited or administered by the PI or a group they belong to. If a departmental URL was given, it was also given the term “department.” Examples: lab website, project website, wiki, PI’s website
- 7. Categories • Campus – Services located, operated by, run by UIUC or endorsed by UIUC. This includes IDEALS, netfiles and Box.net, NCSA, and Beckman. • Department – Used when a department was specifically mentioned as providing a storage or hosting resource. Examples: Departmental website, departmental server, departmental backup service or a web address traced back to an academic department. Also given the “campus” label.
- 8. Categories • Remote – Services and sites not located on the UIUC campus. Examples: NASA, other campuses, collaborative projects, non-UIUC institutes • Disciplinary – Disciplinary repositories. Many are open access but not all. Examples: GenBank, arXiv, ICPSR, SEAD, Nanohub, and Dryad • Cloud – Storage services using cloud technology. Examples: Google Documents, Google Code, Box.net, Amazon, Microsoft, Dropbox
- 9. Categories • Publication – Scholarly outputs including journal articles, workshops, and conference presentations or posters. Very few DMPs were explicit as to how their “publications” and data were related or separated. • Analog - Physical records including lab notebooks, photographs, and files. Does not include specimens or artifacts. • Specimens - – Physical specimens; usually biological or artifacts
- 10. Categories • Optical Disc - DVD, CD, and Blu-ray discs. Often used as a backup mechanism • Not specified – the DMP was not specific enough for us to record details • No Data – Indicated the proposal will produce no data products. Many were theoretical studies (math), travel grants, or workshop planning sessions. • Local Template Used
- 11. All DMPs (including “no data”) n = 1260 Category Number Percent PI Server 503 39.9% PI Website 529 41.9% Campus 667 52.9% Department 142 11.2% Remote 353 28.0% Disciplinary 275 21.8% Publication 556 44.1% Cloud 63 5.0% Optical Disc 56 4.0% Analog 131 10.4% Specimens 111 8.8% Not Specified 66 5.2% Collaborative 164 13.0% No Data 103 8.2%
- 12. Data Venue and Risk Data Location Submitted Proposals Funded Proposals Since July 2011 n = 1260 Risk of Loss, Corruption, Breach n = 298 Risk of Loss, Corruption, Breach PI Server/Website 64% High 61% High Departmental Server/Website 11.2% Medium to High 7% Medium to High Campus-Wide Resource 52.9% Low 45% Low IDEALS Institutional Repository 21.9% 19.8% NCSA 4.3% 16.4% Disciplinary Repository/Cloud 25.8% Medium to Low 21.4% Medium to Low Remote Repository 28% Medium to High 22.8% Medium to High Optical Disk, Specimens, Analog 19.4% Out of Scope 11% Out of Scope
- 13. Notables • Funded: 298 • Used locally developed template: 254 • IDEALS: 275 • NCSA/XSEDE: 55 • Dryad: 22 • ICPSR: 17 • Genbank/Genetics Repository: 55 • ArX: 61 • Only 87 DMPS contained information about file types
- 14. Analysis • Any differences in storage venue or technologies between the unfunded proposals and the funded proposals? • Any differences between the proposals from the first year and the more current proposals? • Can look at differences in any of the proposal categories between funded and unfunded • 734 active NSF awards, $861.8 million
- 15. Analysis • Use of IDEALS institutional repository: 62 funded, 197 not funded: chi-square: 0.17 • Storing data on PI server or website: 183 funded, 569 not funded: chi-square: 0.7 • Disciplinary or Cloud: 67 funded, 241 not funded: chi-square: 0.85 • Remote storage: 68 funded, 267 not funded: chi-square: 3.01
- 16. Analysis • Use of IDEALS before August 2012 = 108, after (thru November 2013) = 166, chi-square: 4.59, p < .05 • Use of disciplinary or Cloud before August 2012 = 121, after = 182, chi-square: 4.33, p < .05
- 17. Implications • Conclusions: 1: no significant differences between funded/unfunded proposals in storage venues -- no advantage in IDEALS, Disciplinary; 2: more recent proposals suggest IDEALS and disciplinary repositories included at a significantly higher level • What is the role of the library? The campus? The subject discipline? • Connecting data to the literature important