Data Sharing Essentials
Why share data?
- To fulfill funder and journal requirements. Grant funders and (in some disciplines) journals may require data sharing.
- To raise interest in publications. One study found a 69% increase in citations for articles whose associated data were available online.
- To establish priority. Data posted online can be timestamped to establish the date they were produced, blocking “scooping” tactics.
- To speed research. Particularly in complex fields, data sharing can accelerate discovery rates, as researchers into Alzheimer’s disease discovered.
Before sharing, consider:
- Do your data contain confidential or private personal information? If you anonymize, can individuals in the dataset be reidentified?
- Are your datasets understandable to those who wish to use them? Have you included all the metadata, methodology descriptions, codebooks, data dictionaries, and other descriptive material that someone looking at the dataset for the first time would need?
- Do your datasets comply with description, format, metadata, and sharing standards in your field?
- What reuse policies do you wish for your data? Consider the Panton Principles carefully before you attach reuse restrictions.
Where should you put your data?
- As supplementary materials or a “data publication” in an appropriate journal. Check with journals about their data policies.
- A disciplinary data repository, if one exists in your field. Examples include ICPSR, Dryad, and the National Snow and Ice Data Center.
- A campus digital archive with a commitment to storing digital materials for the long term. Examples include MINDS@UW and the Data and Information Services Center’s Online Data Archive.
What help is available?
These people and services can help you make data-sharing decisions: