IDCC14 Engineering DMP Support Pilot
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Transcript of IDCC14 Engineering DMP Support Pilot
Establishing Services & Resources to Support Faculty Writing Data
Management Plans: Lessons Learned from an Engineering Pilot
Jen Green & Natsuko NichollsPractice Paper Co-authors
Leena Lalwani, Paul Grochowski & Sara Samuel
IDCC14, San Francisco, CA24-27 Feb 2014
2
CONTEXT
3
Data@UM
Strongly decentralized campus Grassroots works: deploying multiple data initiatives & projects
Capitalizing on liaison relationshipsDefining new roles for librarians
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College of Engineering
~16 departments, ~500 faculty, ~10,000 students
Strong liaison relationshipNew Responsible Conduct of Research program
Responsive leadership
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PROGRESSEngineering Data Management Support Pilot
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2004 2005 2006 2007 2008 2009 2010 2011 2012 201310%
15%
20%
25%
30%
35%
40%
26%
32%
29%
25%
31%
36%
26%27%
28%27%
24%23%
25%26%
25%
32%
23%22%
24%22%
NSF (Total) Funding Rate, Annual Trend, FY 2004-2013U of Michigan vs. All Institutions
U of Michigan Average of all institutions
Mean value: UM=29%; All institutions=25%
7
2004 2005 2006 2007 2008 2009 2010 2011 2012 201310%
15%
20%
25%
30%
35%
40%
25%
17%
21%19%
26% 26%
21%20%
24%
27%
20%
17%18%
20% 20%
25%
18%17%
18%
21%
NSF (ENG) Funding Rate, Annual Trend, FY 2004-2013U of Michigan vs. All Institutions
U of Michigan Average of all institutions
Mean value: UM=23%; All institutions=19%
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FACULTY SURVEY
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Not at all familiar12%
Slightly famil-iar
20%
Moderately famil-iar
40%
Very familiar20%
N/A8%
Familiarity with DMP Requirements
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Yes72%
No28%
Have you written a DMP?
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DMP ANALYSIS
DMP Analysis: Criteria
Roles and responsibilities for data management
Types of data produced Metadata standards Data storage options Plans for data sharing and redistribution Plans for archiving and preservation
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High38%
Med32%
Low21%
N/A9%
Level of Detail in DMPs
Good
19%
Fair65%
Poor
7%
N/A9%
Quality of DMPs
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No info 34%
Individuals (PIs, Co-PIs, stu-
dents)41%
Project Team
8%
Institutions8%
N/A9%
Roles & Responsibilities for Data Management
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No info74%
Detailed info9%
Some info9%
N/A9%
Volume of Data Generated
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No info30%
1-3 years25%
4-5 years15%
6-10 years6%
> 10 years15%
N/A9%
Period of Data Retention
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publication42%
faculty/project website
36%
conference presenta-
tion11%
"upon request"11%
Means of data dissemination
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Preservation
~20% indicated Deep Blue (UM’s IR) as a location for preservation of access to data.
DR was not mentioned.
No info5% One
op-tion20%Two op-
tions29%
More than three op-
tions38%
N/A9%
Data Storage Options
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RESOURCES & SUPPORTResearch Guides & Faculty Workshops
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Web-based NSF DMP Guide and Resources
http://guides.lib.umich.edu/engin-dmp
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22
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OTHER RESEARCHGraduate Student Interviews about Data
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< 1 GB 1 - 50 GB
51 - 100 GB
101 GB - 1 TB
1 - 2 TB > 2 TB
Se-ries1
0.464285714285714
0.285714285714286
0.0714285714285714
0.0714285714285714
0.0178571428571429
0.0625
5%
15%
25%
35%
45%
Note: N=109; Three students answered “Don’t know.”
Q. How much data did you generate in this research project?
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Q. “What percentage of your data would it take to replicate this research?”
0% 1 to 10%
11 to 20%
21 to 30%
31 to 40%
41 to 50%
51 to 60%
61 to 70%
71 to 80%
81 to 90%
91 to 100%
Series1
20 30 4 7 0 5 3 2 4 1 27
2.57.5
12.517.522.527.532.5
student counts
Note: N=103
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NEXT STEPS
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Lessons Learned & Next Steps
Lessons:• Engage stakeholders• Time
Next steps:• Integration into key required components• Increased graduate student offerings• DM Review Service development• Iterated pilot with LS&A
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Questions?
• Jen Green: Director of Research Data Services
• Natsuko Nicholls: CLIR/DLF Data Curation Fellow