First and foremost, ask yourself what research you can openly share.
Making data open access is a fundamental step in advancing research and promoting not just domestic but global collaboration. The European Union’s Horizon 2020 programme gave us the tagline for research data: “as open as possible and as closed as necessary”. So before making data open access, it’s crucial to understand the principles that underpin the open access movement.
Open data involves removing barriers to accessing information, enabling anyone to freely use, share and build upon data. While it does aim to minimise restrictions, if any of your research involves proprietary, confidential or otherwise sensitive information, you may need to reconsider sharing, remove or anonymise sensitive data, obtain consent if people are involved or restrict access to parts of your research.
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This article provides a guide on how to contribute to the growing movement of transparent and accessible research, effectively accelerating the pace of discovery and innovation.
Be FAIR
After you have decided what you can share, the next step is to prepare your data. An acronym is useful to explain how best to do this: FAIR.
The “F” stands for “findable”. You want to make your research easily findable, so I recommend assigning persistent identifiers, such as digital object identifiers (DOIs), to your datasets. These identifiers ensure that your data remains easily discoverable and citable over time. Think of a persistent identifier like a link to a website; it works in a similar manner, except this link will not end up broken. Repositories often offer DOI assignment as part of their services, contributing to the long-term visibility and impact of your open access data.
The “A” in FAIR stands for accessible. For open data, this involves finding the most appropriate repository for your research. Deposit your data in a trusted repository to ensure its long-term accessibility. Research data repositories may be run by institutions or funding agencies or for research communities. If you’re having difficulty selecting a repository, consult with your colleagues or funders in your research sphere or turn to your institution’s library. Research libraries like Virginia Tech University Libraries, where I work, have a wealth of expertise on research data.
The “I” denotes interoperable. This means placing your data and documentation in formats that are useful to your community. If there are community standards for either data or documentation formats, use them. If not, default to sharing your data and documentation in open formats (for example, txt or csv) for ease of input into applications and in combining them with other data and documentation.
Finally, “R” stands for reusable. Make sure you include a data readme file and all necessary metadata (meaning data about the data) – how it was collected, analysed and interpreted. Without metadata, your research cannot be reused. Follow any community standards that exist in creating this documentation. Include relevant software or written code with your data that analyses, visualises or otherwise manipulates your data.
Additionally, have a clear and concise data access statement outlining the terms and conditions for accessing and using your data. Selecting the right licence is crucial for governing the use of your open access data. Imagine a dataset with 20 licences for different pieces – it would be almost impossible to use. A public domain dedication – CC0 – is the most open and flexible; I recommend using it whenever possible. Creative Commons licences, such as CC BY (Attribution) or CC BY-SA (Attribution-ShareAlike), offer flexibility in defining the terms of use while maintaining the spirit of openness.
Post-sharing
Once you’ve shared your research, consider promoting your open access data to maximise its impact. Share through social media and through academic networks, especially those in which you have previously shared your data. Your institution may also want to promote it through press releases or news feeds. I also recommend encouraging feedback and collaboration to enhance your research’s visibility. Many repositories provide metrics and analytics to help you understand how your data is being used. Monitoring impact allows you to assess the reach and influence of your contribution to the broader research community.
Making data open access is a transformative step towards improving collaboration, transparency and innovation in research. By following these guidelines and embracing the principles of openness, researchers can contribute to the collective advancement of global knowledge.
Jonathan Petters is associate director of data management and curation services at Virginia Tech University Libraries. He participates in Research Data Alliance groups and was recently on the executive board of the Research Data Access and Preservation Association.
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