Data sharing promotes many goals of the NIH research endeavor. It is particularly important for unique data that cannot be readily replicated. Data sharing allows scientists to expedite the translation of research results into knowledge, products, and procedures to improve human health. Do you know what a data sharing plan should include? Are you aware of common practices and standards for data sharing? Do you know what services are available to help share your data responsibly? This workshop will begin to address these questions. Q&A will follow the presentation. Anyone interested in or planning to apply for NIH funding should attend. Note: The NIH data-sharing policy applies to applicants seeking $500,000 or more in direct costs in any year of the proposed research.

1. Options for Sharing Your Data
Key Questions
IUPUI DataWorks is a data repository managed by the IUPUI University Library Center for Digital
Scholarship. It provides digital preservation, access, and registration enabling researchers to retain,
manage, and share research data in a secure, stable environment for citation, access, and re-use.
When you deposit data into IUPUI DataWorks, you will:
• Receive a stable link (DOI) to your deposit that will not change over time.
• Be able to control when your data is made public and how others may use your data.
• Make it easy for others to find your data using common search engines.
• Rest easy knowing your data are preserved in a secure environment for the future.
In your proposal data management plan, you can include standard language indicating that your
data will be preserved in IUPUI DataWorks.
IUPUI DataWorks
• Open or Publicly Available Data
◊ nucleotide sequences in GenBank
• Limited Data Set or Summary Data
◊ CMS Health Outcome Survey LDS
◊ American Community Survey
◊ Consumer Expenditure Survey Series
• Restricted Use Data
◊ National Longitudinal Study of
Adolescent Health: HIV Data
• Dark data
◊ That which is only available to the
research team generating it.
◊ Most research data currently!
Data Sharing in Practice
What
• Data supporting published findings
• De-identified data
• Processed & cleaned data
• Raw data
With Whom
• Upon Request
• Research Group or other colleagues
• Community of Practice
• Anyone
Where/How
• Secure system (e.g., REDCap)
• Subject repository (e.g., GenBank)
• Institutional repository (e.g., DataWorks)
• Other community resource (e.g.,
When
• Embargoed (e.g., delay of 6, 12, 18 months)
• Upon publication
• Immediately
IUPUI University Library Center for Digital Scholarship

2. Data Sharing in Health Sciences
Genetics
Overview
• No consensus at this point, particularly about how sharing/disclosure requirements apply in
particular situations.
• Context is highly variable depending on how the data was created, potential reuse, and particular
issues related to sensitivity of the data.
• There are multiple issues in academic research, industry and commercial applications, litigiation,
agency and federal policies that are driving this conversation.
• Discussion has just begun in a coordinated way, particularly how data sharing is affected by use
of evidence for creating federal agency policy and rules. See the Workshop on Principles and Best
Practices for Sharing Data from Environmental Health Research:
http://www.iom.edu/Activities/Environment/EnvironmentalHealthRT/2014-MAR-19.aspx
Nationally funded environmental public health data: http://www.cdc.gov/nceh/data.htm
United Nations Environment Programme (UNEP): Environmental Data Explorer
WorldBank Data: http://data.worldbank.org/topic/environment
California Environmental Data Exchange Network (CEDEN): http://www.ceden.org/
Environmental Health
Overview:
• Discussion began in 1990s with the Human Genome Project.
• Preceeded the legislative and executive branch policies driving conversations in other disciplines.
• Data sharing practices (e.g., de-identified human genome data and consent requirements),
mechanisms (e.g., tiered system for dissemination), and standards are well developed.
• Data is shared using various models ranging from controlled access to open access.
NIH Genome Wide Association Studies Policy:
http://grants.nih.gov/grants/guide/notice-files/NOT-OD-07-088.html
Genome Wide Association Studies Central: http://www.gwascentral.org/
NIH Genomic Data Sharing: http://gds.nih.gov/
NIH list of repositories: http://gds.nih.gov/02dr2.html
International Code of Conduct for Genomic and Health-Related Data Sharing (draft April 24, 2014)
Ready to share your data?
• Identify obligations to funders, publishers, research community, and institution.
• Begin to consider your answers to the questions on the opposite side of this page (What, With
Whom, How/Where, When). Write down your initial thoughts, including questions and concerns.
• Review the data and associated project documentation to gauge readiness for sharing.
• Contact Heather Coates for a consultation to identify the next steps and get support.