Semantic Artefacts Governance and Management

FAIR-IMPACT recognises the critical importance of governance in the development and maintenance of semantic artefacts. To address this, the project has dedicated a specific task aimed at defining and expanding on the concept of "Semantic Artefact Governance". Through the FAIR-IMPACT Semantic Artefact Governance workshop, we explored a variety of governance strategies and practices across diverse EOSC-related communities. This effort enabled us to generate recommendations for initiatives and communities seeking to implement governance and management methods throughout their semantic artefact lifecycle.

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Semantic Artefact Governance Definition

Governance of development and maintenance practices is essential for establishing a network of interoperable semantic artefacts within an organization or community, ensuring that these efforts do not result in siloed data. Several initiatives have set high-level operational rules to measure the interoperability of created semantic artefacts through dedicated tests or assessment metrics. These initiatives aim to integrate the rules into a structured methodology necessary for the management of semantic artefacts. At the same time, recognizing clear accountabilities for these assets and responsibilities for related processes has a significant impact on effective governance.

Some initiatives prioritize adapting existing principles and practices to maintain broad aspects of interoperability. However, adopting these strategies is not always straightforward, as their implementation can vary widely depending on the technologies in use, organizational structures, or specific goals. As a first step to address this issue, we aim to provide a generic definition that is broadly applicable across different contexts. This definition builds on existing works, including insights from communities of practice and data governance definitions derived from a structured literature review presented by René Abraham et al. 2019. We formalised the semantic artefact governance and management as: 

  • A principled approach for regulating various aspects of semantic artefact lifecycle, from acquisition through usage to deprecation. Semantic artefact governance establishes policies, standards, procedures, and monitors compliance. It defines decision-making, accountabilities, roles, and responsibilities about these assets.

Semantic Artefact Governance Component

Governance Framework

Governance Framework defines a set of high-level principles and agreed-upon specifications to provide management mechanisms, supports the development, maintenance, and use of standard tools, and facilitates the application of best practices. By reusing the pattern established by the BASF Governance Operational Model for Ontologies (GOMO), which is the result of a collaborative effort between industry and academia in the semantic web field, we provide a unified governance structure aimed at enhancing interoperability across initiatives adopting the framework.

 

Principles in semantic artefact governance can take the form of simple statements or concrete policies that address specific aspects of the semantic artefact lifecycle, such as metadata, versioning, information model, etc. Each principle should be supported by Recommendations, offering guidance on implementing the principle while providing necessary background knowledge for carrying out related activities. Recommendations lead to Standards, derived from best practices, which set norms or requirements to ensure consistent and effective governance. These standards enable human- or software-based evaluations through a Quality Control process to verify correct implementation. Lastly, training programs emphasise the importance of educating stakeholders on using these recommendations and standards effectively, ensuring the principles are applied consistently.

In the following, we provide an example of how the framework can be applied in practice. We take one of the FAIR Principles, specifically I1: '(Meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation,' and demonstrate its implementation within the framework in the following graph.

 


 

Engineering Methodology

Engineering Methodology comprises processes, methods, and tools for building semantic artefacts. The Methodology structures activities, tasks, and operations into systematic and formal phases necessary for developing semantic artefacts such as conceptualization, encoding, publication and maintenance. Initiatives could either develop their own methodology, workflows and related tools, customise all steps of SA lifecycle based on their requirements and objectives, or adapt existing methodology and utilise available tools and services to adhere to best practices and increase interoperability with others initiatives. Further details are referenced in FAIR-IMPACT’s T4.2.1, which produced a revised Linked Open Terms methodology (FAIR by design methodology). 

In the following, we highlight several key aspects of the semantic artefact lifecycle that should be addressed during the development, publication, maintenance, and consumption phases of a semantic artefact. These aspects represent primary topics that should be formalised through the Governance Framework introduced in the previous section.

  1. Availability (licencing)
  2. Access rights and security policy
  3. Documentation
  4. Relevant attributes, metadata and provenance
  5. Unique identification for (meta)data
  6. Versioning
  7. Deprecation
  8. information model
  9. (Meta)data reuse
  10. Visualisation
  11. Mapping
  12. Modularity and extensibility 
  13. (Meta)data access and semantic repository
  14. Naming Conventions
  15. Scope
  16. Language
  17. Commitment to collaboration
  18. Channels for communications and contribution

Organisational Structure

Organisational Structure outlines how specific activities are allocated and directed to achieve the organisation’s goals. It defines decision-making, accountabilities, roles, responsibilities, and the engagement of stakeholders. Operational mechanisms, such as Standard Operating Procedures (SOPs), can be employed to disseminate tasks among actors. Through examining communities of practice, we identified key domains of activity essential for initiatives to recognize. These domains should be addressed according to the initiative’s level of maturity in semantic artefact management and its available human resources.

 

 

Editorial: Focuses on developing, maintaining, and updating the principles and standards of the initiative. This includes creating, implementing, and overseeing review processes for these standards, as well as establishing policies that ensure editorial consistency.

Technical: Responsible for the upkeep and administration of the technical infrastructure. This includes managing websites, repositories, APIs, SPARQL endpoints, and other related services and workflows, ensuring they are up-to-date, secure, and accessible.

Outreach: Manages the organisation’s public relations and external communications. This includes monitoring communication channels, producing documentation and educational resources, and representing the organisation at events and other external venues to enhance engagement and awareness.

Coordination: Oversees the consistency and alignment of governance policies with organisational standards, ensuring technical compliance. This area supports best practices and coordinates training for curators, fostering collaborative interactions between teams to reinforce policy coherence.

SA Development: Encompasses the full lifecycle of developing and releasing semantic artefacts, from initial conception to final deployment. This includes iterative development processes, version management, and ensuring that artefacts are released with documentation and clear functionality for end users.

SA Curation: Ensures that semantic artefacts are current and aligned with ongoing requirements. This includes managing lifecycle aspects like versioning, deprecation, and identification, while also engaging with the community, expert networks, and external entities to maintain relevance and foster collaboration.

Expertise: An advisory group of subject-matter experts providing specialised knowledge to support ontology validation and curation. This team promotes and guides the use of semantic artefacts, offering recommendations for content evolution, reuse, and adaptation while validating changes and improvements.

Community: Foster an inclusive, collaborative network of stakeholders involved in the development, use, and governance of semantic artefacts. This involves engaging users, curators, and contributors, feedback loops, and communication channels that facilitate active participation and knowledge sharing.


Semantic Artefact Governance Recommendations

Following the structured methodology, we analysed practices, principles, and resources for semantic artefact governance and management to create tailored recommendations that cater to the specific requirements of distinct target groups.

  1. Project-based initiatives managing single-core semantic artefact, such as application ontologies (e.g., EFO and SAREF) or Linked Open Data sets (e.g., AGROVOC). Within this category, semantic artefact is developed to address the need for standard vocabulary in a target domain. These semantic artefacts enable semantic interoperability and support the creation of knowledge graphs by providing domain-specific concepts and properties, enhancing data integration between systems that deploy them.
  2. Support-based initiatives direct communities in developing and maintaining semantic artefacts. Individuals or groups of researchers independently build and maintain artefacts in a decentralised manner. Organisations such as INRAE Voc and NFDI4Biodiv operate within this category.
  3. Harmonisation initiatives that provide principles and guidelines, along with infrastructure, to harmonise the management of semantic artefact across communities or organisations. Developers can use the upper-level ontologies, modularisation methods, and other standard workflows and practices established by these initiatives to ensure they develop interoperable semantic artefact. The OBO Foundry is an example of this category, serving as a pivotal point in using semantic web technologies in biological and biomedical sciences. BASF also falls into this category but restricts its developed ontologies to internal organisational use.

Here you can find the document: https://docs.google.com/document/d/1BZjUcvsZArGANLkrGkHP9Wrmx1EFiuje-YkaNJwZ1Hs/edit?usp=sharing