Evaluating FAIR Digital Object and Linked Data as distributed object systems

TL;DR

This paper systematically evaluates FAIR Digital Object (FDO) and Linked Data as distributed object systems, comparing their interoperability, middleware, and adherence to FAIR principles, and provides recommendations for their integration and improvement.

Contribution

It offers a comprehensive evaluation of FDO and Linked Data using multiple frameworks, highlighting their similarities, differences, and pathways for better alignment and adoption.

Findings

FDO and Linked Data have complementary strengths and challenges.

Historical analysis explains adoption difficulties of Semantic Web technologies.

Recommendations aim to enhance interoperability and community alignment.

Abstract

FAIR Digital Object (FDO) is an emerging concept that is highlighted by European Open Science Cloud (EOSC) as a potential candidate for building a ecosystem of machine-actionable research outputs. In this work we systematically evaluate FDO and its implementations as a global distributed object system, by using five different conceptual frameworks that cover interoperability, middleware, FAIR principles, EOSC requirements and FDO guidelines themself. We compare the FDO approach with established Linked Data practices and the existing Web architecture, and provide a brief history of the Semantic Web while discussing why these technologies may have been difficult to adopt for FDO purposes. We conclude with recommendations for both Linked Data and FDO communities to further their adaptation and alignment.