FAIR Research Objects and computational workflows A Linked Data approach

This PhD thesis explores the topics of RO-Crate, FAIR Digital Objects (FDOs), and computational workflows, in order to examine research questions on how these can be implemented and integrated using Linked Data approaches – forming “FAIR Research Objects”.
The background covers the evolution of the Semantic Web, Linked Data, and FAIR Digital Objects, which are evaluated against the FAIR principles and several frameworks, to consider these technologies as potential middleware for a global distributed object system that enable machine-actionable research outputs.
This work introduces the community-developed method RO-Crate for packaging research artefacts with their contextual information, relationships and metadata – utilising Linked Data standards that are simplified and documented for pragmatic use by software developers. The tension between flexibility for implementations and rigidity of semantic constraints is explored, and demonstrated by profiles of RO-Crate across research domains such as bioinformatics, regulatory sciences, biodiversity and digital humanities.
Computational workflows, for reproducible data analysis across execution platforms, are examined as potential FAIR Digital Objects, considering them both as shareable research outputs as well as a part of provenance of computational results, captured in a Workflow Run Crate.
This thesis explores the emerging ecosystem of FAIR Digital Objects and how it can learn from the community development of RO-Crate to carefully adapt "just enough" of Linked Data technologies, balancing flexibility and predictability. The main findings of this thesis emphasise community-driven pragmatic solutions over strict semantic correctness, supporting advancement of the FAIR principles through practical and interoperable implementations of Web standards.