Improving the Interoperability of Biomedical Research Data
Author | : Philip van Damme |
Publisher | : |
Total Pages | : 0 |
Release | : 2023 |
ISBN-10 | : 9464832584 |
ISBN-13 | : 9789464832587 |
Rating | : 4/5 (84 Downloads) |
Book excerpt: "The research community widely acknowledges the importance of sharing research data for purposes like replicating previous research, answering new research questions, and increasing sample sizes or the number of variables. However, ensuring that shared data are also reusable by others (both humans and machines) is an ongoing challenge. A recent development in the research community has been the adoption of the FAIR Guiding Principles for research data management. The FAIR principles provide a set of guidelines on how to make (meta)data more Findable, Accessible, Interoperable, and Reusable. Data exchange should also be based on meaning, which is one aspect of interoperability, the main focus of this thesis. While humans can infer implicit information from natural language, machines need explicit meaning (semantics) for interpreting data. Terminology systems structure meanings in the real world in a way that is understandable for machines. They contain content in natural language for humans and logical statements that are understandable for machines. This thesis aims to contribute to more interoperable biomedical research data, particularly in the domain of rare diseases. To do so, we focus on (1) what role the FAIR principles play in guiding and harmonizing data management practices for biomedical research and (2) what impact challenges around using, creating, and maintaining terminology systems have on interoperable data."--