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Data management for
EDU 292
http://data.ucdavis.edu
http://guides.lib.ucdavis.edu/education
Laura Soito
Phoebe Ayers
Melis...
http://lib.ucdavis.edu
UC Davis Libraries
http://guides.lib.ucdavis.edu/education
http://guides.lib.ucdavis.edu/dataresources
Why should I care?
• Reproducibility is a tenet of science.
• Research needs to be credible.
• You are a good person.
• Be...
Why should I care?
Ideas from presentations by Carly Strasser
http://dmptool.org
http://dmptool.org
Metadata exercise
• Write down all the things you would
want to know about a dataset in order to
use it.
• Then, compare w...
• Title – Name of the dataset or research project that produced it
• Creator – Names and addresses of the organization or ...
Considerations for data
storage
• How long?
• Who maintains?
• Who pays?
• Who can access? (and is it
findable?)
Options
• Discipline repository (i.e. ICPSR: find
a list at http://re3data.org)
• General repository (i.e. Harvard
Dataver...
http://slideshare.net/carlystrasser
http://dataverse.org
More questions to ask
• Backups?
• What file formats?
Compressed?
• Security/confidentiality?
• Is this the right version?
Citing data
• Tell people how to cite your
data
• Cite other people’s data
accurately
• Provide a unique link/ID
Link up all of your work
http://guides.lib.ucdavis.edu/authorid
Take 1 minute…
• What did you learn?
• What’s still confusing?
Thank you
Questions? Need help?
UC Davis libraries data management
group:
http://data.ucdavis.edu
dataserv@ucdavis.edu
Data management basics, for UC Davis EDU 292
Data management basics, for UC Davis EDU 292
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Overview of research data management, for UC Davis EDU 292, Spring quarter 2015.

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Data management basics, for UC Davis EDU 292

  1. 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. 2. http://lib.ucdavis.edu UC Davis Libraries
  3. 3. http://guides.lib.ucdavis.edu/education
  4. 4. http://guides.lib.ucdavis.edu/dataresources
  5. 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. 6. Why should I care? Ideas from presentations by Carly Strasser
  7. 7. http://dmptool.org
  8. 8. http://dmptool.org
  9. 9. 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?
  10. 10. • 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
  11. 11. Considerations for data storage • How long? • Who maintains? • Who pays? • Who can access? (and is it findable?)
  12. 12. 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!)
  13. 13. http://slideshare.net/carlystrasser
  14. 14. http://dataverse.org
  15. 15. More questions to ask • Backups? • What file formats? Compressed? • Security/confidentiality? • Is this the right version?
  16. 16. Citing data • Tell people how to cite your data • Cite other people’s data accurately • Provide a unique link/ID
  17. 17. Link up all of your work http://guides.lib.ucdavis.edu/authorid
  18. 18. Take 1 minute… • What did you learn? • What’s still confusing?
  19. 19. Thank you Questions? Need help? UC Davis libraries data management group: http://data.ucdavis.edu dataserv@ucdavis.edu
  • pru_mitchell

    May. 16, 2015

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

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