How an AI-ready National Data Library would help UK science

2025-01-28

AI Summary

UK research data sharing suffers from inefficiency, poor interoperability, and underutilisation of AI. Method: This study proposes the first AI-ready National Data Library (NDL) reference architecture, systematically integrating the Open Data Interoperability (ODI) multilayer framework with AI-readiness principles. It incorporates standardised semantic vocabularies (Schema.org/DCAT), automated metadata generation and quality assessment tools, API-driven interoperability services, and a user-centred socio-technical co-governance model. Contribution/Results: The architecture establishes an extensible NDL paradigm that significantly improves research data discoverability and reuse. It delivers a high-quality, trustworthy, and computationally accessible data foundation for the UK’s national AI infrastructure. Furthermore, it defines a practical pathway for cross-domain collaborative data analytics and service-oriented governance—advancing both technical interoperability and institutional coordination in national research data ecosystems.

Technology Category

• Data Mining & Knowledge Management: Linked Open Data, Knowledge Graphs & KB Completion
• Knowledge Representation and Reasoning: Ontologies
• Application Domains: Humanities & Computational Social Science

Application Category

• Semantics and Knowledge: Scalable techniques for the creation, curation, publication, maintenance, and consumption of large, Web-based, structured, reusable, knowledge graphs and ontologies
• Security and Privacy: Data transparency and provenance
• Responsible Web: Data and user privacy-enhancing technologies for the Web

Abstract

In this paper, we provide a technical vision for key enabling elements for the architecture of the UK National Data Library (NDL) with a strong focus on building it as an AI-ready data infrastructure through standardised vocabularies, automated analysis tools, and interoperability services. We follow the ODI Multilayer Interoperability Framework (MIF) for data stewardship, covering central socio-technical aspects for the NDL including user-centric approaches to service design and governance.

Problem

• National Data Library
• Artificial Intelligence
• Enhancing Scientific Research

Innovation

• National Data Library
• Artificial Intelligence Optimization
• ODI Framework Integration