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Creating a Data Management Plan for Your Grant Application

Creating a Data Management Plan for Your Grant Application. Liz Weinfurter Nursing Library Liaison eweinfur@umn.edu Lisa Johnston University Libraries Data Curation Lead ljohnsto@umn.edu. Image: http://www.sciencemag.org/content/331/6018.cover-expansion. Why is data management important.

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Creating a Data Management Plan for Your Grant Application

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  1. Creating a Data Management Plan for Your Grant Application Liz Weinfurter Nursing Library Liaison eweinfur@umn.edu Lisa Johnston University Libraries Data Curation Lead ljohnsto@umn.edu Image: http://www.sciencemag.org/content/331/6018.cover-expansion

  2. Why is data management important...

  3. NIH Data Sharing Policy In NIH's view, all data should be considered for data sharing. Data should be made as widely and freely available as possible while safeguarding the privacy of participants, and protecting confidential and proprietary data.  Investigators seeking $500,000 or more in direct costs in any year should include a description (primarily in the form of a brief paragraph immediately following the Research Plan Section) of how final research data will be shared, or explain why data sharing is not possible. 

  4. NIH Data Sharing Plan A brief paragraph describing: • expected schedule for data sharing • format of the final dataset, • documentation to be provided, • whether or not any analytic tools also will be provided, • any the criteria for deciding who can receive the data and conditions placed on their use (ie. Data sharing agreement), • and the mode of data sharing.

  5. NSF Data Sharing Policy "Share with other researchers, at no more than incremental cost and within a reasonable time, the data, samples, physical collections and other supporting materials created or gathered in the course of the work.”  -NSF PAPP Guide New (Jan 2011): “Grantees are expected to encourage and facilitate such sharing” and that NSF will implement these policies through: • the proposal review process; (ie. Data Management Plan) • award negotiations and conditions; and • appropriate support and incentives for data cleanup, documentation, dissemination, storage and the like.

  6. Agencies with $100M/Year funding must develop a strategy that "improves the public’s ability to locate and access digital data resulting from federally funded scientific research.... [the data] should be stored and publicly accessible to search, retrieve, and analyze." - OSTP Memo Feb 22, 2013 Image: http://www.retronaut.com/wp-content/uploads/2012/12/160.jpg

  7. Tool Box: Publisher Sharing Policies Many journals are requiring or strongly encouraging replication data/code to be made available.

  8. Today’s Agenda: Five Questions to Address in Your Data Management Plan 1. What type of data or files will be produced or used? 2. What standards will be used for documentation and metadata?   3. What steps will be taken to protect privacy, security,  confidentiality, intellectual property or other rights?  4. If you allow others to reuse your data, how will the data be accessed and shared? 5. How will the data be archived for preservation and long-term access?

  9. 1. What types of data or digital files will your research generate? How do you store them? Image Http://cdn.slashgear.com/wp-content/uploads/2012/10/google-datacenter-tech-13.jpg

  10. Tool Box: Data Storage Options LOCAL(LAB OR DEPT) CLOUD CENTRAL (OIT) Hard drive Dept/local server Personal Laptop Flash Drive Active Directory NetFiles Google Docs Amazon DropBox  Security Problems

  11. Tool Box: Storing Human Subjects Data SENSITIVE IDENTIFIABLE INFORMATION PROTECTED HEALTH INFORMATION (PHI) ✔ AHC Managed Servers ✔ OIT Block Storage ✔ NetFiles xShared/personal drive x Google docs x DropBox x Amazon x Email ✔ AHC Managed Servers ✔ OIT Block Storage ✔ NetFiles ✔ Shared/personal drive ✔ Google docs x DropBox x Amazon x Email

  12. 2. What standards will you use to document your research? Image: http://www.fujitsu.com/img/INTSTG/products/bpm/business-process-management-582x240.jpg

  13. Tool Box: What are Metadata Standards? Metadata: a standard set of elements used to describe a particular type of data set; used for data format & context. Why are standards important? Access Context Attribution Interoperability

  14. Tool Box: Metadata Schema

  15. 3. What steps will you take to protect privacy, security, confidentiality, intellectual property or other rights?  Image: http://www.businesscomputingworld.co.uk/wp-content/uploads/2012/01/Computer-Connections.jpg

  16. Tool Box: Storing Human Subjects Data “De-identified” data must not include these 19 identifiers: • Medical record number • Health plan number • Account numbers • License numbers • VIN/license plates • Device identification • Universal resource locators • IP address • Biometric identifiers • Full face photos • Any other unique identifying number or code • Name • Location < state • Dates (year only) • Ages over 89 • Phone number • Fax number • Email address • Social security number

  17. Tool Box: Securing Data University private data must be stored on University computers, not home computers or other personal electronic devices. - U of M Policy for Standard for Securing Private Data 2010 Links: See also, OIT Guide on Securing your Data (encryption methods) and Physical Server protection. 

  18. University Policy: Tool Box: Data and Intellectual Property The University shall be the sole owner of all rights, titles, and interests (including intellectual property rights) in and to technology: • created by University employees in the course of their employment; • created by students or post-doctoral or other fellows in the course of their academic duties or appointments; or • created by individuals, including employees, students, or post-doctoral or other fellows,using substantial University resources. U of M Board of Regents policy, Commercialization of Intellectual Property Rights

  19. 4. How will you share your data with others for reuse? Image: http://jivesna.com/images/dspace.png

  20. laboratory notebooks preliminary analyses drafts of scientific papers plans for future research peer review reports communications with colleagues, or physical objects, such as laboratory specimens. Also, Confidential materials Trade secrets, HIPAA, or FERPA information Tool Box:   What Not to Share

  21. Tool Box:   Publishing Data Post online Project web site Institutional web site FigShare Zenodo Publish in journal Cite data in your work PURL or DOI Deposit into data repository UMN Digital Conservancy

  22. Tool Box: Subject Data Repositories

  23. 5. How will you archive the data for preservation and long-term access? Image: http://www.spellboundblog.com/wp-content/uploads/2008/09/floppy_photo.jpg

  24. DBF PDF CSV TIFF Tool Box:   File Formats for Long-term Access MS Access MS Word MS Excel GIF or JPG

  25. Tool Box: Digital Conservancy Data Example

  26. To recap: There are resources on campus to help you create a DMP, comply with grant requirements, and implement research data management. Image: http://www.nsf.gov/news/mmg/media/images/memorandum_f.jpg

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