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. A study published on PLoS ONE 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 (New York Times article).
Before sharing, consider:
- Do your data contain confidential or private personal information? If you anonymize, can individuals in the dataset be reidentified (see SSRN article)?
- 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.
What are my data-sharing options?
Depending on your retention and sharing needs, there are several sharing options available.
|Sharing Method||Useful if…||Be aware…|
|Direct share via e-mail or pantherFILE||
|As supplementary materials in an appropriate journal||
|In a subject-specific data repository (see list maintained by Purdue University)||