This document summarizes a webinar about data management plans and tools. It discusses what a data management plan is, why researchers should create one, and what funders like NSF require in a DMP. It also introduces several tools like the DMPTool that can help researchers create DMPs and describes the goals and development of the DMPTool project. Finally, it provides information on how researchers can participate and give feedback to improve DMP tools.

1. Data Management Plans
Tips
Tricks
From Flickr by dipster1
Tools
Carly Strasser & Perry Willett
University of California Curation Center
California Digital Library
11 January 2012  Webinar Series California Digital Library
UC3

2. Roadmap
4. DMPTool
3. Toolbox
2. Data Management Plans 101
1. Welcome & Logistics

3. Roadmap
4. DMPTool
3. Toolbox
2. Data Management Plans 101
1. Welcome & Logistics

4. Logistics for Webinar
• Participants on mute
• Chat is being monitored
• ~15 minutes for Q&A after webinar
• Slides and web/voice recordings will be posted after
presentation
• Phone: 866-740-1260, access code 6408974#
• Schedule of webinars available at
www.cdlib.org/uc3/uc3webinars.html
11 January 2012  Webinar Series California Digital Library
UC3

5. Who we are
Partnership between CDL | 10 UC campuses | Peer institutions
Provide solutions, services, resources for digital assets
Pool & distribute diverse experience, expertise, & resources
11 January 2012  Webinar Series California Digital Library
UC3

6. Who we are
11 January 2012  Webinar Series California Digital Library
UC3

7. Who you are
11 January 2012  Webinar Series California Digital Library
UC3

8. Who you are
Help us improve the DMPTool
By taking this survey:
http://tinyurl.com/DMPToolsurvey
http://www.surveymonkey.com/s/LSTV8QL
11 January 2012  Webinar Series California Digital Library
UC3

9. Who you are
Help us improve the DMPTool
By taking this survey:
http://tinyurl.com/DMPToolsurvey
http://www.surveymonkey.com/s/LSTV8QL
11 January 2012  Webinar Series California Digital Library
UC3

10. Roadmap
4. DMPTool
3. Toolbox
2. Data Management Plans 101
1. Welcome & Logistics

11. From Flickr by DW0825
From Flickr by Flickmor
From Flickr by deltaMike
Digital data
www.woodrow.org
C. Strasser
Courtesey of WHOI
From Flickr by US Army Environmental Command

12. Where data end up
From Flickr by diylibrarian
www
blog.order2disorder.com
From Flickr by csessums
Data
Metadata
From Flickr by csessums
Recreated from Klump et al. 2006

13. Who cares?
www.rba.gov.au
From Flickr by AJC1
From Flickr by Redden-McAllister

14. Where data end up
From Flickr by diylibrarian
www
From Flickr by csessums
blog.order2disorder.com
Data
Metadata
From Flickr by csessums
Recreated from Klump et al. 2006

15. Where data end up
From Flickr by diylibrarian
www
Data
www
Metadata
From Flickr by torkildr
Recreated from Klump et al. 2006

16. Trends in Data Archiving
Journal publishers
Joint Data Archiving Agreement

17. Trends in Data Archiving
Journal publishers
Joint Data Archiving Agreement
Data Papers
Ecological Archives, Beyond the PDF

18. Trends in Data Archiving
Journal publishers
Joint Data Archiving Agreement
Data Papers
Ecological Archives, Beyond the PDF

19. Trends in Data Archiving
Journal publishers
Joint Data Archiving Agreement
Data Papers etc.
Ecological Archives, Beyond the PDF
Funders
Data management requirements

20. What is a data management plan?
A document that describes what you will do with your data
during and after you complete your research
Robert Stadler installation from Flickr by Dom Dada

21. Why should I prepare a DMP?
Saves time
Increases efficiency
Easier to use data
Others can understand & use data
Credit for data products
Funders require it

22. NSF DMP Requirements
From Grant Proposal Guidelines:
DMP supplement may include:
1. the types of data, samples, physical collections, software, curriculum
materials, and other materials to be produced in the course of the project
2. the standards to be used for data and metadata format and content (where
existing standards are absent or deemed inadequate, this should be
documented along with any proposed solutions or remedies)
3. policies for access and sharing including provisions for appropriate
protection of privacy, confidentiality, security, intellectual property, or other
rights or requirements
4. policies and provisions for re-use, re-distribution, and the production of
derivatives
5. plans for archiving data, samples, and other research products, and for
preservation of access to them

23. NSF’s Vision*
DMPs and their evaluation will grow & change over time
(similar to broader impacts)
Peer review will determine next steps
Community-driven guidelines
– Disciplines have different definitions of acceptable data
sharing
– Flexibility at the directorate and division levels
– Tailor implementation of DMP requirement
Evaluation will vary with directorate, division, & program
officer
*Unofficially
Help from Jennifer Schopf, NSF

24. NSF’s Vision*
DMPs are a good first step towards improving data
stewardship
– starting discussion
– scientists learning about data management
Additional expertise on panels to effectively evaluate
DMPs (?)
Working group will assess outcomes
*Unofficially

25. NSF DMP Requirements
From Grant Proposal Guidelines:
DMP supplement may include:
1. the types of data, samples, physical collections, software, curriculum
materials, and other materials to be produced in the course of the project
2. the standards to be used for data and metadata format and content (where
existing standards are absent or deemed inadequate, this should be
documented along with any proposed solutions or remedies)
3. policies for access and sharing including provisions for appropriate
protection of privacy, confidentiality, security, intellectual property, or other
rights or requirements
4. policies and provisions for re-use, re-distribution, and the production of
derivatives
5. plans for archiving data, samples, and other research products, and for
preservation of access to them

26. 1. Types of data & other information
• Types of data produced
• Relationship to existing data
• How/when/where will the data be captured or
created? C. Strasser
• How will the data be processed?
• Quality assurance & quality control measures
• Security: version control, backing up biology.kenyon.edu
• Who will be responsible for data management
during/after project?
From Flickr by Lazurite

27. 2. Data & metadata standards
What is
metadata?
Data reporting
• WHO created the data? Wired.com
• WHAT is the content of the data set?
• WHEN was it created?
• WHERE was it collected?
• HOW was it developed?
• WHY was it developed?
From Flickr by proteinbiochemist

28. 2. Data & metadata standards
• What metadata are needed to make the data meaningful?
• How will you create or capture these metadata?
Wired.com
• Why have you chosen particular standards and approaches
for metadata?

29. 3. Policies for access & sharing
4. Policies for re-use & re-distribution
• Are you under any obligation to share data?
• How, when, & where will you make the data available?
• What is the process for gaining access to the data?
• Who owns the copyright and/or intellectual property?
• Will you retain rights before opening data to wider use? How long?
• Are permission restrictions necessary?
• Embargo periods for political/commercial/patent reasons?
• Ethical and privacy issues?
• Who are the foreseeable data users?
• How should your data be cited?

30. 5. Plans for archiving & preservation
• What data will be preserved for the long term? For how
long?
• Where will data be preserved?
• What data transformations need to occur before
• preservation? will be submitted
What metadata
alongside the datasets?
• Who will be responsible for preparing
data for preservation? Who will be the
main contact person for the archived
data?
From Flickr by theManWhoSurfedTooMuch

31. Don’t forget: Budget
• Costs of data preparation & documentation
Hardware, software
Personnel
Archive fees
• How costs will be paid
Request funding!
dorrvs.com

32. Roadmap
4. DMPTool
3. Toolbox
2. Data Management Plans 101
1. Welcome & Logistics

33. Toolbox:
From Flickr by dipster1
www.dataone.org
• Data Education Tutorials
• Database of best practices
& software tools
• Links to DMPTool
• Primer on data
management
From Flickr by Robert Hruzek

34. Toolbox: 101
Data Management
From Flickr by dipster1
DCXL website dcxl.cdlib.org
• Data Education Tutorials
• Primer on data management
• Other resources

35. Toolbox:
From Flickr by dipster1
DCXL blog: dcxl.cdlib.org
• Data Education Tutorials
• Primer on data management
• Other resources
dcxl.cdlib.org
www.carlystrasser.net/Resources

36. Toolbox:
From Flickr by dipster1
Institutional Services
UC Community: www.cdlib.org/services/uc3
Deposit | Share | Preserve data
Precise identification of a dataset
Credit to data producers and data publishers
Link traditional literature to data
Research metrics for datasets

37. Toolbox:
From Flickr by dipster1
Institutional Services
Check with your
institution’s librarians

38. Toolbox:
From Flickr by dipster1
DMPTool dmp.cdlib.org

39. Roadmap
4. DMPTool
3. Toolbox
2. Data Management Plans 101
1. Welcome & Logistics

40. DMPTool for Data Management Plans
• Helps researchers meet requirements of NSF
and other U.S. funding agencies.
• Guides researchers through the process of
creating a data management plan.
• Is available to everyone at no cost.
• Provides additional help for researchers at
DMPTool partner institutions
http://dmp.cdlib.org Jan 11, 2012

41. Goals of the DMPTool, I
• To provide researchers a simple way to create
a Data Management Plan by giving them
information from the funding agency:
– Questions asked by the agency
– Any additional explanation or context provided
by the agency
– Links to the agency website for policies, help,
guidance
http://dmp.cdlib.org Jan 11, 2012

42. Goals of the DMPTool, II
• To provide researchers with additional
information from their local institution:
– Resources and services to help them manage data
– Help text for specific questions
– Suggested answers to questions that they can
simply cut-and-paste
– News and events related to data management on
their campus
http://dmp.cdlib.org Jan 11, 2012

43. DMPTool project
• Partners: CDL, DataONE, Smithsonian, UCLA,
UCSD, UIUC, UVa, Digital Curation Centre (UK)
– Great team!
• Started work in January 2011
• Developed requirements, divided work among
partners, self-funded
• Usability testing at Ecological Society of America
conference and Univ of Virginia
http://dmp.cdlib.org Jan 11, 2012

57. Future Development
• Partners’ meeting in late January to discuss
– User survey results
– Priorities for additional development
– Governance, development, funding models
• Additional US funding agencies (NIH, others)
coming soon
http://dmp.cdlib.org Jan 11, 2012

58. How you can participate
• User survey
• Talk to your librarian or data center staff
about:
– Shibboleth login (“single sign-on”)
– Add links to local resources, help text, suggested
answers, contact information
– Blog for local news and events
http://dmp.cdlib.org Jan 11, 2012

59. Project participants
• CDL/UC3: • Smithsonian • Univ of Illinois:
– Trisha Cruse Institution: – Michael Grady
– Perry Willett – Günter Waibel – Howard Ding
– Marisa Strong – Sarah Shreeves
– Tracy Seneca
• UCLA:
– Scott Fisher – Todd Grappone • Univ of Virginia:
– Stephen Abrams – Gary Thompson – Andrew Sallans
– Mark Reyes – Darrow Cole – Sherry Lake
– Margaret Low • UCSD: – Carla Lee
• DataONE: – Brad Westbrook • Digital Curation
– Amber Budden Centre:
– Martin Donnelly
http://dmp.cdlib.org Jan 11, 2012

60. Email us! uc3@ucop.edu
UC Community: www.cdlib.org/services/uc3
Help us improve the DMPTool
By taking this survey:
http://tinyurl.com/DMPToolsurvey
http://www.surveymonkey.com/s/LSTV8QL
11 January 2012  Webinar Series California Digital Library
UC3