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Open Data: Options for Researchers

This guide provides information about public access and open access to data and the options researchers have for sharing data or data privacy.

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Options by Openness: Sharing Data That...

Open data provides avenues for true reproducibility, citizen science, and improved decision making for individuals and entities across the globe (e.g., business owners, policy-makers, and individuals and their own health). To contribute your data openly, it is best practice to develop a data management plan before beginning your research to determine how best to be able to reuse and distribute your data upon completion and to publish data and supporting materials CC0 (or CC-BY) in a data repository. Here are some of the features of a data repository:

  • Provides an avenue for developing comprehensive metadata
  • Creates citations and assigns a DOI to your dataset(s)
  • Enables you to determine usage
  • Provides Long-term preservation and storage of your data

For assistance with choosing a repository and with meeting a repository's deposit requirements, please contact the Research Data Services department at

warning signRelying 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.



Not all research data can be made openly available. Here are some options for limiting availability or openness of your data in a way that still allows sharing.

  • Licensing - Publishing data with a copyright or with Creative Commons licensing allows you to share your data publicly without releasing your rights to the dataset. This is referred to as public access.
  • Embargo - one of the most common methods of ensuring first access to your data is through delaying open or public access to your data by a specified amount of time.
  • Partial dataset - data can be shared partially to allow others to understand what may be available and then they can contact you for the full dataset. Sampling in order to share partial datasets is also a way of protecting confidentiality of human subjects.

For help with exploring options for making your data public, please contact the Research Data Services department at

You can reach researchers interested in your data even if it is not shared openly or publicly. Some options include

  • Sharing interactive visualizations through resources like Tableau, CartoDB, or GitHub pages. While individuals can interact with your data, they do not have access to the raw data. (Here is an example.)
  • Publishing the metadata, or information about the data you have. Many data repositories also provide this as an option, and researchers who are interested can contact you directly for your data. When they contact you, you also have options:
    • Data use agreements can be used when sending a researcher data. These can outline expected conduct and hold individuals accountable related to the data and can also specify consequences of misuse.
    • Sending analysis - For data that absolutely cannot be shared, researchers can send you the analysis, you can run it on your data and return just the results to them.

For help with exploring options for potentially increasing awareness of your data, please contact the Research Data Services department at

Before sharing, consider the following:

  • 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 are the data sharing requirements of the journal in which you plan to publish an article?
  • What reuse policies do you wish for your data? Consider the Panton Principles carefully before you attach reuse restrictions.

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).