Slides from NCURA's webinar "Part I: Public Access: Practical Ways To Assist Faculty To Comply With Public Access Policies". This is the last section on the webinar on open data.

1. Public Access
to Research Data
Kristin Briney
Data Services Librarian
University of Wisconsin-Milwaukee

2. Learning Objective
• Learn to navigate grant mandates around
data management and sharing, and provide
support for researchers' data needs at key
places in the data lifecycle.

3. Why Data?

4. “a scientific publication is not
the scholarship itself, it is merely
advertising of the scholarship”
Buckheit, J. B., & Donoho, D. L. (1995). WaveLab and Reproducible Research. In
Lecture Notes in Statistics Volume 103 (pp. 55–81). New York: Springer.

5. http://www.nytimes.com/2013/04/28/magazine/diederik-
stapels-audacious-academic-fraud.html

6. Vines, T. H., Albert, A. Y. K., Andrew, R. L., Débarre, F., Bock, D. G., Franklin, M. T., … Rennison, D. J. (2014). The
availability of research data declines rapidly with article age. Current Biology : CB, 24(1), 94–7.
http://doi.org/10.1016/j.cub.2013.11.014

7. Data Requirements
1.Data sharing
2.Data management plan

9. Data Management Plans (DMP)

10. Participant Poll
• Have you ever helped a researcher with a
DMP?
– Yes
– No

11. What is a DMP?
• 2-page document
• Describes:
– What data will be produced
– How the data will be managed during the
project
– How the data will be handled after the project
– How the data will be shared

12. NSF General Template
• Types of data produced
• Data and metadata standards
• Policies for access and sharing
• Policies for re-use, redistribution
• Plans for archiving and preservation

13. DMP FYI
• DMP expectations are tightening over time
• Poor data management plans can make the
difference in getting funding!

14. Researchers Need
• Help navigating DMP requirements
– Usually easy to find requirements
– Sometimes hard to fulfill them
• Assistance with DMP drafts
– Ask for boilerplate language/examples
– Need holes filled

15. Researchers Need
• Help navigating DMP requirements
– Usually easy to find requirements
– Sometimes hard to fulfill them
• Assistance with DMP drafts
– Ask for boilerplate language/examples
– Need holes filled

16. Agency DMP Requirements
• Always check grant information for specifics
• DMPTool
– https://dmptool.org/guidance
• SPARC
– http://datasharing.sparcopen.org/

17. NSF General Template
• Types of data produced
• Data and metadata standards
• Policies for access and sharing
• Policies for re-use, redistribution
• Plans for archiving and preservation

18. Alfred P. Sloan Foundation
• Description
• Management
• Dissemination
• Archiving and Stewardship

19. Researchers Need
• Help navigating DMP requirements
– Usually easy to find requirements
– Sometimes hard to fulfill them
• Assistance with DMP drafts
– Ask for boilerplate language/examples
– Need holes filled

20. DMP Examples
• DMPTool
– https://dmptool.org/public_dmps
– Good and bad examples

21. Common Pitfalls
1. Not including enough background on data
2. Not being specific about what happens to
different data
– What data is being created v. what is being
shared?

22. Common Pitfalls
3. Not detailing timelines for sharing and
retention
– Sharing is common at time of publication
– Retention is MINIMUM 3 years, better 10 years
4. Insufficient information on sharing
– Sharing “by request”
– Not listing an option for where data may be
shared

23. Common Pitfalls
5. Copying old DMPs without improving
them
– Reviewers can spot boilerplate
• 1 sentence is fine, half of the DMP is not
– Sharing expectations shifting

24. Researchers Need
• Help navigating DMP requirements
– Usually easy to find requirements
– Sometimes hard to fulfill them
• Assistance with DMP drafts
– Ask for boilerplate language/examples
– Need holes filled

25. DMP Help
• Librarians!
• DMPTool

26. dmptool.org

27. Data Sharing

28. Participant Poll
• Have you ever helped a researcher meet
their data sharing mandates?
– Yes
– No

29. Participant Poll
• Have you ever gotten push back from a
researcher about data sharing mandates?
– Yes
– No

30. Data Sharing
• Data sharing usually occurs with publication
• Share what is needed to reproduce the
research
• Limitations for human subject/sensitive
data

31. Data Sharing FYI
• No compliance measures for following
sharing plan from DMP
• Researchers are not all on board with new
data sharing requirements
• Sharing expectations still shifting
• New sharing requirements from journals

32. Researchers Need
1. To know how to share
– Several data sharing venues exist
2. Help identifying where to share
– Many data repositories exist
3. Help identifying what to share

33. Researchers Need
1. To know how to share
– Several data sharing venues exist
2. Help identifying where to share
– Many data repositories exist
3. Help identifying what to share

34. Sharing Venues
• By request
• On researcher’s personal website
• In the institutional repository
• In a data repository

35. Sharing Venues
• By request
• On researcher’s personal website
• In the institutional repository
• In a data repository
Preferred

36. Researchers Need
1. To know how to share
– Several data sharing venues exist
2. Help identifying where to share
– Many data repositories exist
3. Help identifying what to share

37. Where to Share Data
• What repositories does the researcher
know about?
• Journal recommended repositories
– Scientific Data:
https://www.nature.com/sdata/policies/reposit
ories
• re3data: https://www.re3data.org/

38. Where to Share Data
• Defaults:
– Dryad (biology): www.datadryad.org
– ICPSR (social science): www.icpsr.umich.edu
– Figshare: figshare.com
– Zenodo: zenodo.org

39. Researchers Need
1. To know how to share
– Several data sharing venues exist
2. Help identifying where to share
– Many data repositories exist
3. Help identifying what to share

40. What Data to Share
• Depends…
– on the project
– on disciplinary norms
• Reproducibility is target
– Include enough to let someone redo your work
• Exclusions for sensitive data
– Usually human subjects data

41. Researchers Need
1. To know how to share
– Several data sharing venues exist
2. Help identifying where to share
– Many data repositories exist
3. Help identifying what to share

42. Don’t Forget
• Many of these details will go in the DMP

43. Data Sharing Help
• Librarians!

44. Conclusion

45. Data Requirements
1.Data management plan
– Help navigating DMP requirements
– Assistance with DMP drafts
2.Data sharing
– To know how to share
– Help identifying where to share
– Help identifying what to share

46. Data Requirements
1.Data management plan [MANDATORY]
– Help navigating DMP requirements
– Assistance with DMP drafts
2.Data sharing [NO COMPLIANCE MEASURES]
– To know how to share
– Help identifying where to share
– Help identifying what to share

47. Thanks!
• This presentation is available under a CC BY
4.0 license

48. Note on Copyright/Licensing
• Copyright does not always apply to data
– Cannot copyright facts (Feist v. Rural)
• Best to license data when sharing
– Data is meant to be used
• CC0 and CC BY preferred
– Panton Principles argue for CC0
– Some repositories have a default license