Manage Your Research Data: Why Share Data?

In December 2009, the Open Government Directive was issued by the White House, which required federal agencies to make their agency data open as well as public. This built upon earlier open government legislation like the Freedom of Information Act (1966) and OPEN Government Act of 2007.  In February 2013, the White House further issued a memorandum requiring federal agencies offering more than $100 million in research grants to make funded research data accessible to the public. This was further solidified into law with the passage of HR 4171 - Foundations for Evidence-Based Policymaking Act of 2017. As a result, nearly all federally funded research projects now carry a data sharing requirement.  As this practice becomes the standard, many non-governmental funding organizations, such as non-profits, journals, scholarly organizations, and scientific institutions, also require data sharing. 

More recently, the NIH issued the Data Management and Sharing (DMS) policy, effective January 25, 2023. This policy requires the sharing of research data (with some exceptions).  Researchers must:

• Plan and budget for the managing and sharing of data
• Submit a DMS plan for review when applying for funding
• Comply with the approved DMS plan

Data has a cyclical lifecycle, and its value does not end upon the conclusion of a project.
New analysis tools, new methodologies, and new disciplinary paradigms allow researchers to reexam, reuse, and build upon archived data.
This is the principle of "Data Reuse," defined by the National Library of Medicine as "using research data for a research activity or purpose other than that for which it was originally intended."  Even data dismissed as not useful by the original researcher may prove useful to future researchers.

Sharing data makes the originating study more visible.
When shared research data is reused by other scholars, the data and the original project/publication are cited. By sharing data, researchers can further improve the impact and longevity of their research projects.

Data Lifecycle
Research projects are often linear, beginning with a question followed by data collection, analysis, interpretation, and finally conclusion and publication. Data collected and created during a research project, however, may be reused by the original creator or other researchers in future projects. The cyclical life of data is reflected below (image from the University of Virginia Library's "Research Data Management" research guide)