rdap14: an analysis and characterization of dmps in nsf proposals from the university of illinois
DESCRIPTION
Research Data Access and Preservation Summit, 2014 San Diego, CA March 26-28, 2014 Lightning Talks William Mischo, University of Illinois at Urbana-ChampaignTRANSCRIPT
An Analysis and Characterization of DMPs in NSF Proposals from the University of Illinois
RDAP14 Research Data Access & Preservation SummitMarch 26, 2014
William H. Mischo, Mary C. Schlembach, Megan A. O’DonnellUniversity of Illinois at Urbana-ChampaignIowa State University
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.
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
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
Analysis• Analysis attempts to characterize and classify
DMPs into categories• DMPs assigned multiple categories• 1,260 DMPs from July 2011 to November 2013
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
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.
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
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
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
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%
Data Venue and Risk
Data Location
Submitted ProposalsFunded ProposalsSince July 2011
n = 1260Risk of Loss,
Corruption, Breach n = 298Risk 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%
LowIDEALS 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
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
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
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
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
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