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Kevin Page

Dr

Kevin Page PhD BEng

Senior Researcher

Associate Member of Faculty

Dr Kevin Page studies cultural and societal informatics through interdisciplinary collaborations in the digital humanities. His work on the semantic annotation and distribution of data using web architectures has, through participation in numerous UK, EU, and international projects, been applied across a wide variety of domains including sensor networks, music information retrieval, scholarly texts, clinical healthcare, and remote collaboration for space exploration.

Interdisciplinary collaboration with colleagues across academic disciplines and cultural heritage institutions are characteristic of Kevin’s research. The ‘Linked Art’ initiative, working to create a standard data profile for linking and exchanging information about art, is a collaboration of over 25 institutions. As part of this wider effort, Dr Page led the US-UK funded ‘Linked Art II’ project and before that the AHRC-funded ‘Linked Art Research Network’. He is currently co-investigator of the ‘Enriching Exhibition Scholarship’ project which combines structured data, in the form of Linked Art, with computational analysis of full text sources about art exhibitions, from historical records through to social media. He has served on W3C working groups (LDP, SSN) and advisory committees seeking to harmonise the technical standards and approaches to information sharing. 

For many years Dr Page has investigated computational methods for the organisation and analysis of music and musical information, with a particular interest in their use for digital musicology. Much of his recent research includes the ‘Music Encoding and Linked Data’ framework - MELD - developed by Dr Page and colleagues during the EPSRC FAST project, and since deployed and developed through his AHRC ‘Unlocking Musicology’ and ‘Digital Delius’ projects. He is currently principal investigator of ‘Beethoven in the House’, an international collaboration funded by the UK AHRC and Germany's DFG, which will expand MELD into the new areas of musicological information gathering. As co-investigator of the ‘Digital Elgar’ project he worked alongside colleagues in the Faculty of Music and the National Trust to explore how information narratives can affect a connective context between physical and digital cultural resources. 

In 2014 Dr Page co-founded the international Digital Libraries for Musicology conference (DLfM), serving in chairing roles for several years, and has edited special issues on this and related topics (International Journal of Digital Libraries; Journal of Web Semantics). He has led the Digital Musicology course at the Digital Humanities at Oxford Summer School, the first of its kind, since he instigated it in 2015; for the preceding 4 years he coordinated Linked Data provision.

Underlying many of these applications is the development of information seeking strategies for digital libraries, primarily through the use of knowledge graphs to provide contextual assistance to users. Dr Page was Oxford investigator for the Mellon funded ‘Workset Creation for Scholarly Analysis and Data Capsules’ (WCSA+DC) where, alongside colleagues at the University of Illinois, he explored how these models can be applied to nearly 16 million volumes held in the HathiTrust Digital Library. Large-scale linking of complex and nuanced datasets also motivated Dr Page’s role as in the ‘Mapping Manuscript Migrations’ project, one of the most recent international ‘Digging into Data’ awards.

Dr. Page teaches the third year project group ‘Designing Intelligent Music Technology’ for the MSc in Engineering Science; and for Humanities Division options papers on ‘Digital Musicology’ and ‘Linked Data’ for the MSc in Digital Scholarship. He co-supervises a DPhil student, alongside colleagues from Oxford and the Victoria & Albert Museum, as part of the AHRC Collaborative Doctoral Partnerships programme.

Most Recent Publications

A model for annotating musical versions and arrangements across multiple documents and media

A model for annotating musical versions and arrangements across multiple documents and media

Narratives and exploration in a musicology app: Supporting scholarly argument with the Lohengrin TimeMachine

Narratives and exploration in a musicology app: Supporting scholarly argument with the Lohengrin TimeMachine

Harmonizing and publishing heterogeneous premodern manuscript metadata as Linked Open Data

Harmonizing and publishing heterogeneous premodern manuscript metadata as Linked Open Data

Design of a dynamic and self-adapting system, supported with artificial intelligence, machine learning and real-time intelligence for predictive cyber risk analytics in extreme environments – cyber risk in the colonisation of Mars

Design of a dynamic and self-adapting system, supported with artificial intelligence, machine learning and real-time intelligence for predictive cyber risk analytics in extreme environments – cyber risk in the colonisation of Mars

A New Model for Manuscript Provenance Research: The Mapping Manuscript Migrations Project

A New Model for Manuscript Provenance Research: The Mapping Manuscript Migrations Project

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Research Interests

  • Linked Data, Semantic Web, and Knowledge Graphs
  • Cultural and societal applications of informatics
  • Digital Musicology
  • Digital Humanities
  • Music Information Retrieval (applied, metadata, symbolic, multimodal)
  • Digital Libraries - theory and practice, Information-seeking behaviours, serendipitous discovery
  • Web architecture and standards
  • Ontology engineering
  • Metadata and web annotation
  • Hypertext and hypermedia
  • REST and API design

Current Projects

Past Projects

Research Groups

Related Academics

Most Recent Publications

A model for annotating musical versions and arrangements across multiple documents and media

A model for annotating musical versions and arrangements across multiple documents and media

Narratives and exploration in a musicology app: Supporting scholarly argument with the Lohengrin TimeMachine

Narratives and exploration in a musicology app: Supporting scholarly argument with the Lohengrin TimeMachine

Harmonizing and publishing heterogeneous premodern manuscript metadata as Linked Open Data

Harmonizing and publishing heterogeneous premodern manuscript metadata as Linked Open Data

Design of a dynamic and self-adapting system, supported with artificial intelligence, machine learning and real-time intelligence for predictive cyber risk analytics in extreme environments – cyber risk in the colonisation of Mars

Design of a dynamic and self-adapting system, supported with artificial intelligence, machine learning and real-time intelligence for predictive cyber risk analytics in extreme environments – cyber risk in the colonisation of Mars

A New Model for Manuscript Provenance Research: The Mapping Manuscript Migrations Project

A New Model for Manuscript Provenance Research: The Mapping Manuscript Migrations Project

View all