Open for^BusinessResearch Data Services & Data Management Planning

Ryan SchryverWendt Commonsschryver@engr.wisc.edu

is our

Research Data Servicesresearchdata.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

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.

Funder Requirements

NSF Data Management PlansMandatory for all Applications

NIH Data SharingMandatory for $500K+in direct costs in

any single year

NOAA/NASA/OMBVaries, but setting the precedent…

Soon OSTP

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.”

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

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.

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#IIC2j

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

Ryan Schryverschryver@engr.wisc.edu

Research Data Serviceshttp://researchdata.wisc.edu