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Sharing and Access
Data Sharing refers to the practice of making research data available to others for validation and replication of results.
The NSF requires that all requests for funding contain a data management plan (DMP) addressing how the proposed project will comply with the agency's Data Sharing Policy.
Some subject areas, such as engineering or mathematical and physical sciences, may have specific guidelines addressing unique data management issues for their respective communities. Existing disciplinary requirements are posted at the Data Sharing and Dissemination of Results page, which also includes the general NSF data policy. Be sure to look at proposal details and main directorate or division website for additional guidelines.
NSF also provides an FAQ on data sharing which will answer some questions about the requirements and process.
Things to Think About
When establishing data sharing and access policies and provisions, consider who you will share your data with, how it will be shared, and when in the research process you will share it. For example:
- Is the data shared with other researchers or the general public?
- Who will you share it with? Who may be interested in your data in the future and what might it be used for?
- Are there ethical issues or privacy concerns? Do any regulations apply to the data (for example HIPAA)?
- Do you have the right to share the data if it is not produced by you?
- Will you make the data available before or after you formally publish your results?
- Is your data understandable by other researchers?
- Should the data be restricted or embargoed for intellectual property reasons?
- Will the data be licensed? Will there be any conditions on its re-use?
Options for Sharing Research Data
There are several ways to share research data; the appropriate method will depend on the nature of your research and the content of the data.
||provide access to research data upon request
||provide research data data in support of published articles
||deposit research data in local repository, ie: ScholarWorks
|Disciplinary data repository
||deposit research data in an appropriate community-based repository
- NIH data sharing example from the University of Michigan:
Data products from this study will be made available without cost to researchers and analysts through the University of Michigan HRS Data Download System. User registration is required in order to access or download files. As part of the registration process, users must agree to the conditions of use governing access to the public release data. The information provided to users will not be used for commercial purposes, and will not be redistributed to third parties.
- NSF example from the University of California, San Diego:
All data, metadata, and analyses collected under the proposed experiments will be made publicly available as per NSF guidelines within 2 years of collection via published manuscripts, publicly available final reports to NSF, and/or from data archives at UCSD’s Department of Cognitive Science. The PI will take guidance from NSF concerning the right to use the data prior to opening it up to wider use. There are no ethical or privacy issues involved in sharing of this type of data and it is unlikely that sharing will incur more than modest cost.
- Local Storage for UMass Amherst:
The data will be stored at the University of Massachusetts Amherst
institutional repository ScholarWorks@UMass Amherst upon completion of the grant. Data will be made freely available under a Creative Commons Attribution-No Derivatives-Non Commercial Use 3.0 License. ScholarWorks@UMassAmherst is built on the Digital Commons platform, using Qualified Dublin Core for descriptive metadata. The PI and subject librarians will be responsible for providing the descriptive metadata, so as to make the data discoverable in search engines such as Google.
Last Edited: 4 December 2012