eLearning
We have an extensive eLearning environment which significantly speeds up the learning curve on FAIR. It provides a wide range of training from introductory to advanced modules for people using, managing or implementing FAIR.
Each training module consist of multiple short videos with supporting visuals and clear explanation from experienced tutors.
The content is provided by FAIR experts, in most cases co-authors of the seminal FAIR principles Nature paper.
Trainees can do the course in their own time and pause to resume later at any moment.
Each module ends with a detailed questionnaire which covering all the main points of the course. After each question the right answer is shown, providing a recap that helps trainees remember key learnings.
Introduction to FAIR
This module provides and introduction to FAIR data. It covers the vision of FAIR data, the impact of 'unFAIR' data, the FAIR principles and how these can be realised. This course is an essential precursor to any more in-depth courses on FAIR data.
FAIR Principles in Detail
In this course module we discuss in more detail each of the FAIR principles: their initial intentions, what aspects do they consider, how are they relevant to FAIR and how should we interpret them when we put them into action.
Semantic Interoperability
This course module covers the importance of semantic interoperability in the FAIR principles, emphasizing machine actionability and the role of ontologies in bridging human reasoning with machine processing to ensure meaningful information exchange.
Ontology Engineering
This course module covers how ontologies are used to create machine-readable metadata, based on semantic data models, thus enabling the core aspect of FAIR: machine actionability.
Linked Data and the Semantic Web
This course module provides and introduction to linked data, RDF (Resource Description Framework), RDF syntaxes (such as N-Triples, Turtle, RDF/XML, RDFa and JSON LD), RDFS (RDF Schema), SPARQL and OWL (Web Ontology Language).
The FAIRification Workflow
In this final course module of the Fundamental in FAIR we will bring all the previous learnings together in discussing the steps required to make data FAIR.