The development of FAIR Digital Objects (FDOs) holds immense promise for advancing scientific research, yet one critical challenge persists: Despite efforts to create FDOs, achieving true machine-actionability remains elusive.
We will address this pressing issue by focusing on the integration of Annotated Research Contexts (ARCs) within the scientific community. Recognizing the substantial efforts in annotating research and packaging it as RO-Crate FDOs, it is imperative to incentivize and leverage these endeavors to yield benefits transcending mere data management. ARCs as FDOs excel in meticulous record-keeping, rendering them indispensable in the realm of research data management.
However, dissemination and practical actionability of ARCs across diverse services, tools and repositories is pivotal in engendering user benefits. These platforms require the capacity to comprehend and interpret RO-Crates, enabling seamless interaction with FDOs. Drawing from ARC FDO consumption, search, and indexing platforms must provide users with comprehensive search results, while the service infrastructure can offer customised services tailored to the data described in the FDO.
Therefore, we will build a robust content-based recommendation framework. This approach promises to furnish users with enriched representations of ARC RO-Crate content, facilitating content-based filtering tailored to individual user needs.
To substantiate the efficacy of this framework, Galaxy will serve as the representative workflow engine in a proof-of-concept endeavor aimed at suggesting workflows based on data annotated and encapsulated within ARC RO-Crates. Leveraging collaborative efforts uniting domain experts, developers, and stakeholders across diverse backgrounds, our objective is to engineer practical solutions that render ARC-ISA RO-Crates actionable across pivotal platforms.
Angela Kranz, Eli Chadwick