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Research Data Management Self-Assessment

A self-assessment and introductory guide to research data management for researchers

Sharing Data

Sharing Data

Sharing data is more involved simply uploading files somewhere for other researchers to find. The methods you use to share your data will depend on a number of factors including the size and content of your data, mandates from the entities that fund and publish your research, and assumptions and requirements related to future use. If you make your data and other materials available, you should make sure that other researchers can find and use them.

What does it mean to share data?

Sharing data means making your data available so that they can be accessed and used - by yourself or by others - in the future. Here are three factors to consider when sharing your data.

Format

Data should be shared in a usable format. This may mean sharing raw data instead of prepared data (or vice versa) or ensuring that data are saved in common or open file formats.

Completeness

Remember that notes, documentation, and other information about your data are part of your data. To ensure that your shared data is useful, make sure these elements are included.

Location

When choosing a method for sharing your data, consider how other researchers will find and use it. The storage options you use to save your data as you work on it will probably be different than the options you use to share it, especially over the longer term.

Requirements and How to Meet Them

Many research funders, publishers, institutions and research communities have formal expectations about how data should be shared. If you are unsure about what requirements apply to your data, contact the LRDS team at LRDS@chapman.edu.

The LRDS team maintains a list of funder Open Access and data sharing mandates. A list of journal sharing mandates in biomedical sciences can also be found at the bottom of the "NIH 2023" page on the same link.

Things to Think About

  • Though it is very likely that you’ll share your data only at the conclusion of a research project, data sharing should be incorporated into your data management practices from the beginning.
  • Data sharing is about showing your work. Though many current data sharing requirements focus on the data underlying journal articles and other scholarly works, you should be prepared to share all of your data. All of it has potential value.
  • There are be limits on how data containing sensitive or personally identifying information can be shared, but you should be prepared to share enough information about work so that others can evaluate, potentially replicate, and otherwise make use of what you’ve done.
  • Chapman's platform for preserving and sharing datasets is Chapman Figshare. Please see the Library's Digital Repositories at Chapman University guide for more information.