An analysis and characterization of DMPs in NSF proposals from the University of Illinois (#RDAP14)
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An analysis and characterization of DMPs in NSF proposals from the University of Illinois (#RDAP14)

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Beginning in July 2011, the University of Illinois at Urbana-Champaign Library, working in conjunction with the campus Office of Sponsored Programs and Research Administration (OSPRA) began an ...

Beginning in July 2011, the University of Illinois at Urbana-Champaign Library, working in conjunction with the campus Office of Sponsored Programs and Research Administration (OSPRA) began an analysis of Data Management Plans (DMPs) in newly submitted National Science Foundation (NSF) grant proposals. The DMP became a required element in all NSF proposals beginning on January, 18th 2011. This analysis was undertaken to provide the Illinois campus and library with detailed information on the DMPs being submitted by Illinois researchers. In particular, the analysis allows us to categorize the grant applicant’s proposed DMP data storage venues and data reuse mechanisms, and provides us with data on the use of DMP templates developed by the University of Illinois Library.

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  • Took out (covered in keynote) <br /> - Make key research data available and sharable <br /> - Allow the use of data for verification of results and reproducibility of research work <br /> - Agency can show significant return on investment to justify funding <br />
  • to support Illinois researchers in managing their data <br />
  • Very few DMPs were explicit as to how their “publications” and data were related or separated. <br />
  • No data: Many were theoretical studies (math), travel grants, or workshop planning sessions. <br />

An analysis and characterization of DMPs in NSF proposals from the University of Illinois (#RDAP14) Presentation Transcript

  • 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 N. 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 Analysis •What storage venues and mechanisms for sharing and reuse are being used? •Are the PI’s using local templates and local campus resources such as the IDEALS?
  • 4. Follow-on • Develop campus-wide infrastructure (Research Data Service - RDS) • 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. laboratory server/workstations, external hard drives, group computer • PI Website – Websites edited or administered by the PI or a group they belong to. Examples: lab website, project website, wiki, PI’s website
  • 7. Categories • Campus – Services located, operated by, run by or endorsed by Illinois. IDEALS, Netfiles and Box.net, NCSA, and Beckman Institute. • Department – Used when a department was specifically mentioned as providing a storage or hosting resource. 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 Illinois campus. NASA, other campuses, collaborative projects, non-Illinois institutes • Disciplinary – Disciplinary repositories. GenBank, arXiv, ICPSR, SEAD, Nanohub, and Dryad • Cloud – Storage services using cloud technology. Google Drive, Google Code, Box.net, Amazon, Microsoft, Dropbox
  • 9. Categories • Publication - Scholarly outputs. Journal articles, workshops, and conference presentations/posters. • Analog - Physical records/data. Lab notebooks, photographs, files • Specimens - Physical specimens. Usually biological or artifacts
  • 10. Categories • Optical Disc - DVD, CD, and Blu-ray discs. • Not specified – the DMP was not specific enough for us to categorize further. • No Data – Indicated the proposal will produce no data products. • Local Template Used – used a library authored template.
  • 11. Category Number Percent PI Server 503 39.9% PI Website 529 41.9% Campus 667 52.9% Department 142 11.2% Remote 353 28% Disciplinary 275 21.8% Publication 556 44.1% Cloud 63 5% Optical Disc 56 4% Analog 131 10.4% Specimens 111 8.8% Not Specified 66 5.2% Collaborative 164 13% No Data 103 8.2% ALL DMPs (n=1,260)
  • 12. Data Venue and Risk Data Location Submitted Proposals Funded Proposals Risk of Loss/Corruption/ Breach n=1260 n=298 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% LowIDEALS (Institutional Repos.) 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 local template: 254 • Only 87 DMPS contained information about file types • IDEALS: 275 • NCSA/XSEDE: 55 • Dryad: 22 • ICPSR: 17 • GenBank: 55 • ArX: 61
  • 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? • Other differences in proposal categories between funded and unfunded • 734 active NSF awards, $861.8 million
  • 15. Analysis: Funded vs. Not-funded • 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 and 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