Practicing good data preservation methods makes your data easier to share with others.

Why should you share your research data?

  • To fulfill funder and journal requirements. Increasingly, sharing research data is required by funding agencies and some journals.
  • To raise interest in publications. One study found a 69% increase in citations for articles whose associated data were available online.
  • To speed research. Data sharing can often accelerate discovery rates, especially with medical and epidemiology research.

Every data management plan requirement will expect information about how the data collected will be shared for public access, or to specify if the data should not be shared. Acceptable exceptions to sharing data generally apply to data that might compromise research subjects or be tied to intellectual property, such as patents.

Examples of data sharing concerns:

  • Data cannot be publicly shared because it contains potentially identifying information of human subjects
  • Data contains the locations of endangered/threatened species or valuable artifacts and will only be shared with trusted parties who will agree to reuse criteria
  • Data cannot be released until the patents related to this research are issued

When will the data be made available?

Different funding agencies have different requirements for when research data and articles should be made available. Some agencies require that data be made available at the time of publication, while others require that data be made available within 12 months or a “reasonable time” after publication. For information about specific funder requirements for data and article sharing, see our Federal Funding Requirements page.

How will others access the data?

In a DMP, simply stating that “data will be made available upon request” does not show a commitment to data sharing. Sharing data in a more formal manner effectively publishes it; sharing, or publishing, your data can have many benefits:

  • Improved discoverability: published datasets will have assigned metadata, making them easier to search for and find.
  • Citable: repositories that publish data often offer a citation for your data
  • Stable: repositories that publish data often provide DOIs (Digital Object Identifier) to the data that they curate. A DOI won’t change, even if a URL for accessing the data changes.

Will there be restrictions to the data?

When determining how and where to share your data, consider if there are any reasons to restrict access to your data. You should describe how the dataset will be licensed if rights exist (e.g., list any restrictions or delays on data sharing in order to protect intellectual property, copyright, or patentable data).

You should describe how the dataset will be licensed if rights exist. For example, list any restrictions or delays on data sharing in order to protect intellectual property, and explicitly list any selected licenses detailing reuse and sharing, or patentable data.

  • Example restriction: Data will be deposited into the ICPSR, but access will be restricted due to the sensitive nature of its contents. Anyone wishing to use the data must first submit an application to the ICPSR.

Potential Data Management Costs:

You should always check with the funding agency to determine where in the proposal to include costs related to data management

Include any costs for data management services during the course of the project and after the project is complete.

Tips:

  • Valuable data should be shared when possible
  • Examples of valuable data: data of one-time events, data that are expensive to collect, and data that validate research findings
  • Try to deposit your data in a repository that will handle both the data sharing and preservation
  • Try to share both the raw and analyzed data whenever possible, since analyzed data often contains computed values that cannot be reversed back into their individual variables

Writing Prompts:

  • Are there acceptable reasons for not sharing the data?
  • When will the data be made available?
  • How will others access the data?
  • Will there be any restrictions on the data?
  • Will the data have enough documentation to be useful?

This content was adapted from Iowa State University Library’s Data Management Plan Guide.