This lesson plan provides participants with a comprehensive overview of data accessibility, focusing on the distinctions between open and restricted access, the role of data licenses, and the ethical and legal considerations involved. Participants will engage with examples, participate in discussions, and apply their knowledge through interactive activities. The goal is to develop a clear understanding of how data accessibility impacts research and collaborations.
Data accessibility is the degree to which data can be easily accessed, understood, and used by authorized users when they need it. It ensures that people can obtain relevant data in a usable format to support reuse.
In the Life Sciences, data professionals often define it as the processes and ease with which data can be accessed, retrieved, and have a secondary use when authorized by its original participants and owners. This topic encompasses not only the technical access, but also the format, and documentation that allows for distinct levels of access. In the context of the FAIR principles: “Accessible” means that data should be retrievable by their identifier using a standard communications protocol. This protocol should be open, free, and universally implementable. While data access can be regulated (e.g., controlled or registered access), the protocol itself remains open and free.
Important or key definitions
Open Access:
Means data is publicly available without requiring registration, approval, or special permissions. Anyone can discover, access, download, and reuse the data, subject only to licence conditions such as attribution. Open access is appropriate when there are no privacy, confidentiality, ethical, or contractual concerns.
Controlled Access:
Refers to the mechanisms for sharing sensitive or personal data, when it has been properly pseudonymized or only after a formal application or approval process. This often involves legal agreements (e.g. Data Sharing Agreements, Data Processing Agreements)
Registered Access:
A less restrictive form of controlled access, where users register and agree to specific terms of use, often without individual project-by-project approval but still with a clear record of who is accessing example of this, is request access in a Public Repository like DataverseNL
Restricted access:
Often an umbrella term meaning “not open access”. Some organizations use it as a synonym for controlled access, while others use it more broadly for any access restrictions.
In this section aims to provide trainers with the foundational understandings of data accessibility, inspired by the FAIR principles and focusing on Life Sciences Data.
- Data discoverability as the ability for users to find and locate the data they need
- Data discoverability and its main components: rich and descriptive metadata, search, indexed and searchable repositories and centralized portals
- Data Usability the degree to which (machines and humans) can read and understand the data
- Data Quality: the quality of the data which should be clean consistent and free of errors, to be ready for immediate use.
- Federated data access (local sources)
- Relevant legislations, policies, and recommendations ( e.g. sensitive, personal data, contracts such as Data Transfer and Processing Agreements)
FAIR element(s)
- A - Accessible: working with the community of researchers who have sensitive data and wish to know how to enable FAIR for data that needs to have controlled access.
References
- Dyke, S.O.M., Linden, M., Lappalainen, I., Rambla De Argila, J., Carey, K., Lloyd, D., Spalding, J.D., Cabili, M.N., Kerry, G., Foreman, J., et al. (2018). Registered access: authorizing data access. European Journal of Human Genetics, 26, 1721-1731. Available at: https://www.nature.com/articles/s41431-018-0219-y
- Gierasch, L.M., Davidson, N.O., Rye, K.A., & Burlingame, A.L. (2020). The data must be accessible to all. Journal of Lipid Research, 61(4), 465. Available at: https://www.jlr.org/article/S0022-2275(20)43495-9/fulltext
- Research Data Management Support, Huijser, D., Moopen, N., Flores-Dourojeanni, J., Beltrán, M., de Bruijn, K., de Bruin, J., Capel, D., Dijkstra, F., Einarson, S., Folkers, J., et al. (2025). Data Privacy Handbook. Utrecht University. Available at: https://utrechtuniversity.github.io/dataprivacyhandbook/
Take home tasks/preparation
- Understanding what principles to consider in a context of sharing sensitive data