Abstract
Semantic artefacts (SAs - terminologies, taxonomies, thesauri, vocabularies, metadata schemas and standards) are essential for standardising data representation and annotation, encapsulating the highest level of meaningful knowledge within interoperability frameworks. These artefacts are fundamental to sustainable, quality-verified data practices, aligning with the FAIR Data Principles, particularly Principle I.2. Although experts, including those in the EOSC Interoperability Framework, emphasise the need for governance policies for SA, no universal governance model exists that fits all scientific communities or projects. This deliverable presents various governance models to guide and inspire stakeholders in addressing the governance of semantic artefacts. It is the final and primary deliverable (D4.1) of FAIR-IMPACT’s T4.1 on “Semantic artefact disciplinary governance,” which reviews and analyses community practices to propose strategies tailored to SAs’ characteristics. This document sets out the baseline modality of semantic artefact governance derived from surveyed community-based practices. It provides actionable models for communities or institutions looking to establish or update their semantic artefact governance frameworks. The report is structured into four main sections. The first section introduces the overarching context and the inherent challenges of SA governance, setting the stage for understanding the complexities involved. The second section delves into the three primary components derived from community-based practices: engineering methodologies, organisational structure, and governance framework. Engineering methodologies cover the technical processes and lifecycle management of SAs. The organisational structure addresses the roles and responsibilities within institutions that support effective governance, and the governance framework outlines the high-level principles and standards guiding SA governance. The third section outlines the methodology used to develop the governance models, detailing the steps taken to synthesise community practices into structured, applicable models. The final section presents the baseline governance models, aligning them with specific use cases to demonstrate practical applications. These models address the diverse needs of different scientific communities and projects. As a result of this comprehensive analysis, FAIR-IMPACT T4.1 has formulated initial requirements and developed three distinct models of semantic artefact governance based on community-based stewardship practices. These models facilitate synchronicity, promoting coordinated efforts across scientific communities and ensuring consistent application of best practices. They aim to ensure long-term sustainability by supporting the enduring use and maintenance of semantic artefacts and aiding EOSC communities in seamlessly integrating semantic artefacts within the European Open Science Cloud, thus advancing the FAIR data agenda. This deliverable empowers stakeholders with the tools and frameworks to establish robust governance structures for semantic artefacts, fostering a more interconnected and sustainable data ecosystem.