Overview of research data management, for UC Davis EDU 292, Spring quarter 2015.

1. Data management for
EDU 292
http://data.ucdavis.edu
http://guides.lib.ucdavis.edu/education
Laura Soito
Phoebe Ayers
Melissa Browne
UC Davis Libraries
http://www.slideshare.net/phoebeayers/data-
management-martorell-class

2. http://lib.ucdavis.edu
UC Davis Libraries

3. http://guides.lib.ucdavis.edu/education

4. http://guides.lib.ucdavis.edu/dataresources

5. Why should I care?
• Reproducibility is a tenet of science.
• Research needs to be credible.
• You are a good person.
• Because you have to.
Ideas from presentations by Carly Strasser

6. Why should I care?
Ideas from presentations by Carly Strasser

7. http://dmptool.org

8. http://dmptool.org

10. Metadata exercise
• Write down all the things you would
want to know about a dataset in order to
use it.
• Then, compare with a partner. Are your
lists the same?

11. • Title – Name of the dataset or research project that produced it
• Creator – Names and addresses of the organization or people who created the data
• Identifier – Number used to identify the data, such as project reference number
• Dates – Key dates associated with the data, including project start and end date, data
modification data release date, and time period covered by the data
• Subject – Keywords or phrases describing the subject or content of the data
• Funders – Organizations or agencies who funded the research
• Rights – Any known intellectual property rights held for the data
• Language – Language(s) of the intellectual content of the resource, when applicable
• Location – Where the data relates to a physical location, record spatial coverage
• Methodology – How the data was generated, including equipment or software used,
experimental protocol, other things you might include in a lab notebook
From MIT libraries: https://libraries.mit.edu/data-
management/store/documentation

12. Considerations for data
storage
• How long?
• Who maintains?
• Who pays?
• Who can access? (and is it
findable?)

13. Options
• Discipline repository (i.e. ICPSR: find
a list at http://re3data.org)
• General repository (i.e. Harvard
Dataverse, Figshare)
• Whatever the journal offers
• UC repository (Merritt)
• DIY (but be careful!)

14. http://slideshare.net/carlystrasser

16. http://dataverse.org

17. More questions to ask
• Backups?
• What file formats?
Compressed?
• Security/confidentiality?
• Is this the right version?

18. Citing data
• Tell people how to cite your
data
• Cite other people’s data
accurately
• Provide a unique link/ID

19. Link up all of your work
http://guides.lib.ucdavis.edu/authorid

20. Take 1 minute…
• What did you learn?
• What’s still confusing?

21. Thank you
Questions? Need help?
UC Davis libraries data management
group:
http://data.ucdavis.edu
dataserv@ucdavis.edu