Everything you need to know about making research data open and FAIR


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Everything you need to know about making research data open and FAIR

Unless if they have been hibernating since the 1990s, every researcher knows about the Open Access movement and what a monumental shift it has represented in how scholars publish and read up on the latest research. Likewise, the Open Source movement has affected everybody’s lives by enabling huge technological developments, particularly on the internet. Open Data is another closely linked concept that has attracted less attention. However, it also shares the potential to greatly transform how researchers interact with data and foster deeper collaborations in the future. 

What is Open Data? 

If you are a researcher, you probably collect, analyze, and use all sorts of data to support your findings. But what happens to your data after you publish your paper? Do you keep hold of them? Do you share them with anyone who might be interested in or benefit from them? Do you make sure they are well-documented, organized, and accessible? 

If you answered no to any of these questions, you might want to consider reading up on open data and its best practices. 

Open Data is information released either under an open license or in the public domain that can be used by anybody. Open Data can come in any form, including as photographs, raw sensor data, databases, audio recordings, and nucleic acid sequences. Today, researchers, governmental organizations, and even citizen scientists are contributing huge quantitites of open data to public repositories. 

The advantages of opening your data 

Increased visibility and impact of your research 

By making your data open, you can increase the chances of other researchers finding and citing your work, which can boost your reputation and career prospects. Other researchers may even approach you for future collaborations. 

Better credibility and reproducibility 

If your data are open, you can enable other researchers to verify, replicate, or build upon your results, which can enhance the credibility and validity of your research. Even the simple act of providing your dataset publicly shows that you value transparency and have confidence in your findings. 

Contributing to the advancement of science and society 

Open Data can facilitate collaboration, innovation, and knowledge creation both within your discipline and between other disciplines and sectors, which can lead to new discoveries and solutions for global challenges. It also has positive economic and social effects

Keep it FAIR 

When sharing open data, the FAIR (Findable, Accessible, Interoperable, and Reusable) principles should be followed at all times. Making your research data open and FAIR is not only a good practice, but also a requirement for many journals and funding agencies nowadays. How these terms are implemented are explained in brief below. 

Findable 

Accessible 

  • Provide a globally unique and persistent identifier (e.g., DOI) 

  • Give useful metadata 

  • Metadata should refer to the identifier 

  • Register data in a searchable repository 

  • Make data retrievable by their identifier using a standardized communications protocol 

  • Keep metadata accessible, even when data are no longer available 

Interoperable 

Reusable 

  • Data and their metadata should follow strictly defined language and vocabularies that facilitate interpretation and processing 

  • Data and metadata make qualified references to other data/metadata (e.g, explain the nature of the link between A and B) 

  • Data are released with a clear and accessible data usage license. 

  • Data are associated with detailed provenance 

  • Data meet domain-relevant community standards 

The GO FAIR website offers great resources that can be used as effective checklists to ensure that your data are being shared in a way that is ethical and useful for other researchers. 

How to manage your open data 

Making your data open is not as simple as uploading them to a website or sending them to a colleague. You need to follow some good data-management practices to ensure that your data follow the FAIR principles and help other researchers. 

Make your data interoperable with other sources and formats 

You should use common standards and formats for your data to make them compatible with different software and platforms. For example, if other researchers studying the same topic are using the RDF format for data, it might be wise to do the same. Avoid any proprietary formats. Likewise, metadata should follow interoperable formats, like the Dublin Core specifications

Provide raw data 

Annotated or edited data can often be harder to use than raw data. Provide images, videos, and audio files in their unedited form and use lossless formats over lossy ones.  

Store your data securely and reliably 

For works-in-progress, you should back up your data regularly. Data preservation tools can facilitate this. Use encryption or password protection if they contain sensitive information.  

Make your data available through a reputable repository 

You should choose a trusted and well-used data repository like Figshare or Zenodo. The repository should have a clear and transparent data policy and provide a persistent identifier (such as a DOI) for your data Ideally, you should host the data in repositories that are relevant to your field or discipline; for example, transcriptomic data should be deposited in databases like the Gene Expression Omnibus

Provide sufficient metadata and documentation for reproducibility 

You should provide information about the origin, context, content, quality, and structure of your data, as well as the methods, tools, and standards used to collect and process them. You should also use common vocabularies and formats for your metadata and provide documentation where available to make them understandable by humans. A data reuse plan is useful for ensuring this is carried out properly. 

Apply an open license 

You should choose a license or waiver that specifies how others can use, modify, and share your data, such as Creative Commons or GPL. You should also make sure that the license is compatible with the policies of journals and funding agencies that support your research. 

Points of caution 

Before you open your data to the world, it is vital to ensure that your data are being shared ethically and legally. 

First, are the data yours to share? If they contain proprietary information, you must have explicit permission from license holders before declaring them open. Likewise, data should respect the ethical norms of different cultures or communities. If you have received help in obtaining data, you should acknowledge the sources and contributors of your data and give credit where credit is due. 

Second, ensure the quality and integrity of your data over time. You should update or correct your data if there are any errors or changes and leave records of any changes made. You should also monitor the usage and feedback of your data and respond to any questions or requests from other users. 

Finally, when dealing with any data containing confidential information, such as medical records, it is imperative to ensure that the data have been fully anonymized or that informed consent to disclose has been obtained from all participants. 

Conclusion 

Open Data is not just a practical source of information for researchers, it may transform the future of our societies by improving social and technological problems and fostering greater transparency. While there are many considerations in managing Open Data, the wealth of publicly available resources enable any researcher to be a responsible steward of their data, thereby maximizing the impact of their work. 

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Published on: Oct 10, 2023

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