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Managing Research Data: Data Sharing

Why Share Your Research Data?

There are benefits for the researcher, research sponsor, scientific community and public:

  • Openness in science
  • Promotes rigor and transparency
  • Enhanced researcher reputation through increased citations
  • Expansion of the scientific community, increased discussion and participation
  • Increased opportunities for cross disciplinary research
  • A better informed public increases trust in science and better decision making
  • Allows optimized spend by research funders
  • Increased opportunities for meta-analyses through combining datasets across laboratories

Concerns about data sharing

Researchers may be reluctant to share data because of concerns about:

  • Inappropriate use due to poor understanding of research parameters and strategies
  • Maintaining security and confidentiality of sensitive data
  • Not getting credit or acknowledgement
  • Loss of advantage when competing for research dollars

Data Sharing Done Right

Some measures that can address researcher concerns:

  • Include a data accessibility statement with each publication.
  • Develop thorough metadata to describe all parameters and methods of collection and include them on the landing page for the date repository
  • Archive and curate data with a reputable, carefully selected repository
  • Provide recommended citation to ensure appropriate attribution
  • Increase citations by making datasets discoverable and increasing secondary use of datasets
  • Publish data papers that describe raw data, data processing and failed data for additional citations.

How to share data

Steps for sharing data include:

  • Create robust metadata to describe methodology, improving reproducibility and provide provenance
  • Specify appropriate geography and time periods
  • Use discipline specific thesauri and ontologies
  • Include links to appropriate data catalogs, downloads
  • Include archival and reference information such as properly formatted citations and universally unique identifiers
  • Ask data contributors to review metadata for correctness and completeness
    • Correct methods and techniques described
    • All contributions acknowledged
    • All appropriate management reviews
    • Funding organization recognized
  • Publish metadata and data in:
    • Federal data catalogs such as Data.gov
  • Disciplinary data repositories i.e. Knowledge Network for Biocomplexity (KNB), Long Term Ecological Research (LTER) Network Data Portal
  • NSF Public Access Repository (PAR)