1. Open for ^ Business Research Data Services & Data Management Planning Ryan Schryver Wendt Commons schryver@engr.wisc.edu is our

2. Research Data Services researchdata.wisc.edu researchdata.wisc.edu  Our Goal: Aid UW-Madison researchers in their efforts to preserve, maintain, and share their data  Interdisciplinary  Data management is our day job  What we do:  Data management plans – help draft or review  Consultations – policies, development, best practices  Training and education  Referral – local/national/disciplinary resources

3. Why Manage Data?  Ensure research integrity and replication.  Ensure research data are accurate and reliable.  Increase efficiency.  Save time and resources in the long run.  Enhance data security and minimize the risk of data loss.  Prevent duplication of effort by enabling others to use your data.  Meet funding grant requirements.

4. Funder Requirements NSF Data Management Plans Mandatory for all Applications NIH Data Sharing Mandatory for $500K+in direct costs in any single year NOAA/NASA/OMB Varies, but setting the precedent… Soon OSTP

5. OSTP – What it says  Released February 2013.  All federal agencies with $100M+ in R&D to develop plans to increase public access to research results and data.  ROI: “maximize the impact and accountability of the Federal research investment.” -- “Innovation” and “Validity.”

6. Elements of a Public Access Plan for Scientific Data*  Maximize access  Protect confidentiality and privacy  Preserve intellectual property rights and commercial interests  Balance demands of long-term preservation and access  Use of data management plans  Include cost of data management in funding proposals  Evaluate DMPs  Ensure researcher compliance with DMPs  Promote public deposit of data  Private-sector cooperation to improve access  Mechanisms for identification & attribution of data  Data stewardship workforce development  Long-term support for repository development *Used with permission of ICPSR

7. What is a DMP?  Document that outlines how you will handle data (and description of that data) during AND after research is complete.  States what data will be created and how, and outlines the plans for sharing and preservation.  Justifies why access or sharing is limited.

8. Example: NSF Data Management Plan  Started January 2011 for NEW proposals.  Blueprint for data retention and sharing.  Not voluntary – “integral part” of NSF proposal and FastLane.  Factual material (physical or digital) necessary to validate findings Data is expected to “explain and defend results.”  Standards determined by “Community of Interest.” Source: Special Information and Supplementary Documentation, http://www.nsf.gov/pubs/policydocs/pappguide/nsf11001/gpg_2.jsp#IIC2jhttp://www.nsf.gov/pubs/policydocs/pappguide/nsf11001/gpg_2.jsp#IIC2j

9. NSF DMP Content 1.Expected Data: types, physical/electronic collections, materials to be produced 2.Standards to be used for data and metadata format and content 3.Policies for access and sharing including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements 4.Policies and provisions for re-use, re-distribution, and the production of derivatives 5.Plans for archiving data, samples, and other research products, and for preservation of access to them

10. Ryan Schryver schryver@engr.wisc.edu Research Data Services http://researchdata.wisc.edu