After completing this course successfully, the students are capable of:
- Explaining the FAIR principles and their impact on digital objects.
- Assessing the FAIRness of digital objects.
- Applying the FAIR principles to improve findability, accessibility, interoperability, and reusability of digital objects.
- Critically evaluating and selecting technologies to realize the FAIR principles.
- Executing the FAIRification process to make metadata and data FAIR(er).
Since their publication in March 2016, the FAIR principles rapidly gained international momentum by introducing a set of guiding principles to improve findability, accessibility, interoperability, and reusability of data, metadata, and other types of digital objects. A key aspect of the principles is to better leverage the resources invested in generating digital objects by improving the machine actionability and, therefore, increasing automation in different activities that require findable, accessible, interoperable, and reusable data. The rapid acceptance of the FAIR principles as guidelines for proper data stewardship created a significant demand for expertise on how to apply them and, therefore, increase the FAIRness of digital objects.|
This course aims at introducing the required knowledge to understand and apply the FAIR principles on data and metadata. The course focuses on the understanding of the principles, their analysis, and on the process to make existing data FAIR. A significant part of FAIR relates to supporting the ability of artificial agents to interpret discovered information and act accordingly. This is achieved using semantic techniques such as ontologies, Linked Data, and Semantic Web, which are also addressed in the course. During the course, students will apply the acquired knowledge in a practical project of making selected data FAIR.
The main topics of the course are the following:
- Introduction to FAIR Data Stewardship;
- Detailed explanation of the FAIR principles;
- Introduction to the FAIRification process on metadata and data
- Introduction to semantic interoperability
- Introduction to Semantic Web and Linked Data technologies
- Introduction to the tools to be used in the FAIRification process (FAIR Data Point)
|Basic understanding of data structures;|
Understanding of data modeling.
|Master Business Information Technology||Verplicht materiaal|
|Selected papers, made available via Canvas.|
|Barend Mons, Data Stewardship for Open Science: Implementing FAIR Principles. 1st edition, Chapman and Hall/CRC, 2018, ISBN 9781315380711|
|Zelfstudie geen begeleiding|
|Report, Presentation, Exam|
OpmerkingProject report 50%, project presentation 10%, final exam 40%. Resit for the final exam.