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Data 101: An Introduction toResearch Data ManagementLisa FedererHealth and Life Sciences Librarianlmfederer@library.ucla.edu
Today’s Session• General overview of research data management  best practices• Data management across the research data li...
Why Data Management?• funders often require it• makes for easier transitions with lab staff  turnover• helps better docume...
The Research Data Life Cycle                     Plan       Preserve                 Collect             Share          Ma...
Plan            The Data Management PlanNSF guidance: http://www.nsf.gov/bfa/dias/policy/dmpfaqs.jspNIH guidance: http://g...
Plan                      The Data Management Plan:                      Common Misconceptions     • Does not require that...
Plan        The Data Management Plan:        Resources for Help• Your library!• DMP Tool: http://dmp.cdlib.org• DMP Online...
Collect                       Best Practices for Data                       Collection      • Use non-proprietary file for...
Collect   Manage              Metadata: Data About Data      • Types of metadata          ▫   Descriptive metadata        ...
Manage   Improving Excel Data with              Check for best practices
Manage   Improving Excel Data with                 Create metadata
Manage   Improving Excel Data with         Get a unique identifier and citation
Manage   Improving Excel Data with • Two ways to use DataUp   ▫ DataUp Excel add-in (Windows Excel 2007+ only)    https://...
Share              Best Practices for Data Sharing       • Different communities of practice have different         cultur...
Share   UC Tools for Sharing                      creates unique identifiers                    http://www.cdlib.org/servi...
Share             Selecting Licenses for Re-Use                   Attribution (CC BY)                    Attribution-Share...
Preserve Share           Planning for Long Term           Preservation • Especially important for unique and non-   replic...
Preserve Share      Locating Repositories • Institutional repositories at the UC    ▫ Merritt https://merritt.cdlib.org/  ...
Getting Additional Help• UCLA Library Data Management Guide http://guides.library.ucla.edu/data-management• University of ...
Questions?Lisa FedererHealth and Life Sciences Librarianlmfederer@library.ucla.edu
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Data 101 - An Introduction to Research Data Management

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An introductory class on research data management for scientists, designed and presented by Lisa Federer, Health and Life Sciences Librarian at UCLA Louise M. Darling Biomedical Library.

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Data 101 - An Introduction to Research Data Management

  1. 1. Data 101: An Introduction toResearch Data ManagementLisa FedererHealth and Life Sciences Librarianlmfederer@library.ucla.edu
  2. 2. Today’s Session• General overview of research data management best practices• Data management across the research data life cycle• UC resources for data management• Your questions
  3. 3. Why Data Management?• funders often require it• makes for easier transitions with lab staff turnover• helps better document research output• ensures usefulness of data over its entire life cycle• facilitates data sharing
  4. 4. The Research Data Life Cycle Plan Preserve Collect Share Manage
  5. 5. Plan The Data Management PlanNSF guidance: http://www.nsf.gov/bfa/dias/policy/dmpfaqs.jspNIH guidance: http://grants.nih.gov/grants/policy/data_sharing/data_sharing_faqs.htm
  6. 6. Plan The Data Management Plan: Common Misconceptions • Does not require that all data must be shared ▫ Sensitive information/patient privacy ▫ Intellectual property rights and commercial value • Sharing can take many forms • Funders recognize that different disciplines have different “cultures” of data sharing • Sharing “at no more than incremental cost and within a reasonable time”11. National Science Foundation, Dissemination and Sharing of Research Results, www.nsf.gov/bfa/dias/policy/dmp.jsp
  7. 7. Plan The Data Management Plan: Resources for Help• Your library!• DMP Tool: http://dmp.cdlib.org• DMP Online: http://www.dcc.ac.uk/dmponline
  8. 8. Collect Best Practices for Data Collection • Use non-proprietary file formats ▫ Plain text/RTF vs. Microsoft .doc/.docx ▫ PDF/PNG vs. BMP/TIF • Consider future preservation and context, not just what is needed right now • Collect good metadataAdditional info on open formats: http://www.openformats.org
  9. 9. Collect Manage Metadata: Data About Data • Types of metadata ▫ Descriptive metadata ▫ Technical metadata ▫ Administrative metadata ▫ Use metadata ▫ Preservation metadata • Many fields have existing metadata standards ▫ MIAME: microarray experiments ▫ Darwin Core: biology and biodiversityAdditional info: http://www.dcc.ac.uk/resources/briefing-papers/standards-watch-papers/what-are-metadata-standardsExample of metadata standards: http://sdl.syr.edu/?page_id=32
  10. 10. Manage Improving Excel Data with Check for best practices
  11. 11. Manage Improving Excel Data with Create metadata
  12. 12. Manage Improving Excel Data with Get a unique identifier and citation
  13. 13. Manage Improving Excel Data with • Two ways to use DataUp ▫ DataUp Excel add-in (Windows Excel 2007+ only) https://bitbucket.org/dataup/main/downloads/DataUpAddIn.zip ▫ DataUp web application http://www.dataup.org/
  14. 14. Share Best Practices for Data Sharing • Different communities of practice have different cultures of sharing ▫ Institutional/subject repositories ▫ Person-to-person sharing of data ▫ Publication in data journals • Data sharing is associated with increased citations11. Piwowar HA, Day RS, Fridsma DB (2007) Sharing Detailed Research Data Is Associated with Increased Citation Rate.PLoS ONE 2(3): e308. doi:10.1371/journal.pone.0000308
  15. 15. Share UC Tools for Sharing creates unique identifiers http://www.cdlib.org/services/uc3/ezid/ cost-effective repository for sharing and storage http://www.cdlib.org/services/uc3/merritt/
  16. 16. Share Selecting Licenses for Re-Use Attribution (CC BY) Attribution-ShareAlike This license lets others distribute, (CC BY-SA) remix, tweak, and build upon your This license lets others remix, tweak, work, even commercially, as long and build upon your work even for as they credit you for the original commercial purposes, as long as they creation. credit you and license their new creations under the identical terms. Attribution- Attribution-NoDerivs NonCommercial (CC (CC BY-ND) BY-NC ) This license allows for redistribution, This license lets others remix, commercial and non-commercial, as tweak, and build upon your work long as it is passed along unchanged non-commercially, although their and in whole, with credit to you. new works must also acknowledge you and be non-commercial.For more info see http://creativecommons.org/licenses/
  17. 17. Preserve Share Planning for Long Term Preservation • Especially important for unique and non- replicable datasets • Use institutional and subject specialized repositories to preserve data for the long-term • LOCKSS: Lots of Copies Keep Stuff Safe • Talk to the library about your data
  18. 18. Preserve Share Locating Repositories • Institutional repositories at the UC ▫ Merritt https://merritt.cdlib.org/ ▫ eScholarship http://www.escholarship.org/uc/ucla • Finding subject specific repositories ▫ Databib http://databib.org/ ▫ Datacite repository list http://datacite.org/repolist ▫ Open Access Directory Data Repositories http://oad.simmons.edu/oadwiki/Data_repositories
  19. 19. Getting Additional Help• UCLA Library Data Management Guide http://guides.library.ucla.edu/data-management• University of California Curation Center (UC3) http://www.cdlib.org/services/uc3/• Contact a librarian ▫ Data help: data@library.ucla.edu ▫ Copyright/licensing: http://www.library.ucla.edu/copyright-publishing-contact-us ▫ Biomedical Library help: biomed-ref@library.ucla.edu ▫ Science and Engineering Library help: sel-ref@library.ucla.edu
  20. 20. Questions?Lisa FedererHealth and Life Sciences Librarianlmfederer@library.ucla.edu

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