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?

Relying on your own, your lab’s, your department’s, or even some campus-wide IT resources or services can be risky. Unless the service offers an explicit commitment to long-term preservation of content, your data are liable to disappear if you change institutions or retire, funding stops, or technology policies or platforms change.

What help is available?

These people and services can help you make data-sharing decisions:

Further Reading

Tenopir C, Allard S, Douglass K, Aydinoglu AU, Wu L, et al. (2011) Data Sharing by Scientists: Practices and Perceptions. PLoS ONE 6(6).