Setting the Scene: Data Management 101

1. Setting the Scene:Data Management 101 Robin L. Dale Director of Digital & Preservation Services

2. Data Management 101 • What do we mean by data & “data management?” • How does it differ from digital preservation or digital curation? • Supporting the data lifecycle • Overview of requirements from NSF, NIH, IMLS

3. Data Management? • Driven by e-Science; research data • Not digital preservation in the narrow sense • Not “dark” archiving • More closely tied to digital and data curation • Focus on data sharing and archiving • Lacks a coordinated focus in most research areas • Huge opportunities for libraries to leverage existing digpres and dig curation work

4. What Do We Mean by Data? • Images, audio & video • Library-owned *and* astronomy, oceanographic, etc • Numerical • SPSS, STATA, Excel, Access, MySQL, complied databases • Code • Publications & text • “Raw” data • Sensor readings, telemetry, gene sequences • Supporting metadata

5. Supporting the Data Lifecycle Data Documentation Initiative. Data Documentation Initiative (DDI) Technical Specification , Part I, Overview. http://www.ddialliance.org/Specification/DDI-Lifecycle

6. Recent Mandates • National Institutes for Health (NIH) • National Science Foundation (NSF) • Institute for Museum & Library Services (IMLS)

7. NIH (2003) • The NIH requires a data sharing statement for those proposals requesting >$500,000 in direct costs in any year of project • Applies to final research data • not summary statistics or tables; must be “data on which summary statistics and tables are based” • “Timeliness” factor • NIH expects that plan to be enacted

8. NSF (2011) • Data Sharing • Investigators are expected to share with other researchers, at no more than incremental cost and within a reasonable time, the primary data, samples, physical collections and other supporting materials created or gathered in the course of work under NSF grants • encouraged to share software and inventions created under the grant or otherwise make them or their products widely available and usable • Data Management • MUST include a data management plan (2-pages)

9. NSF Data Management Plans • How will the proposal will conform to NSF policy? • the types of data, samples, physical collections, software, curriculum materials produced • the standards to be used for data and metadata format and content • policies for access and sharing including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements • policies and provisions for re-use, re-distribution, and the production of derivatives; and • plans for archiving data, samples, and other research products, and for preservation of access to them

10. IMLS (2011 or 2012?), 1/2 • Specifications for Projects that Develop Digital Products (OMB 3137-0071) • Part III Developing Data Management Plans for Research Projects • IMLS “encourages the sharing of research data”

11. IMLS, 2/2 • Intended purpose of the research, type of data to be collected or generated, approximate dates when the data will be generated or collected, & anticipated volume of data • Privacy and approval issues; consent data • IP rights, ownership • Technology used to create/collect data; formats for storage; metadata • Technical issues during project (access, storage, metadata) • Long-term plan (post-project), IR deposit?

12. Moving Forward • Implementation (beyond “the plan”) • Opportunities for libraries? • Who will pay? • Local plans? • Building “best practices”

13. References • NIH: NIH Data Sharing Policy and Implementation Guidance, http://grants.nih.gov/grants/policy/data_sharing/data_sharing_guidance.htm • NSF: Dissemination and Sharing of Research Results http://www.nsf.gov/bfa/dias/policy/dmp.jsp • IMLS: Specifications for Projects that Develop Digital Products www.imls.gov/applicants/forms/DigitalProducts.doc

14. Questions? Thank you! If you have any questions, please do contact me: Robin.Dale@lyrasis.org (404) 592-4816 (direct)