Using mixed-methods, a data model and a computational ontology in film audience research

Bridgette Wessels*, David Forrest, Matthew Hanchard, Andrew Higson, Peter Merrington, Michael Pidd, Katherine Rogers, Roderik Smits, Nathaniel Townsend, Simeon Yates

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


This paper discusses a methodology that seeks to address one of the challenges in working with a range of data in mixed-methods audience research, which is how to sort, order and categorise different data so that they can be systematically combined and interrogated. The methodology was developed as part of the “Beyond the Multiplex: audiences for specialised films in English regions” (BtM) project. This project required a mixed methods approach using surveys, interviews, focus groups and document analysis to explore the richness of audience experiences and trends in the context of regional film policy. This required a mixed methods approach using surveys, interviews, focus groups and document analysis. The project utilised a data model approach that uses the principles of a computational ontology in order to sort, order and categorise data for systematic interrogation. The paper discusses methods, data, coding, and the use of a data model to support data analysis. We argue that this approach enables the cross referencing of data that provides a rich, multi-layered and relational understanding of film audiences but requires time and attention to data management and coding. Although, additionally it also forms the basis of an open access data resource for future research.

Original languageEnglish
Pages (from-to)118-131
Number of pages14
JournalCultural Trends
Issue number2-3
Early online date20 Jun 2019
Publication statusPublished - 2019


  • audiences
  • computational ontologies
  • data model
  • Film
  • mixed-methods

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