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Research . 2023
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Detecting Dark Matter Data:data gaps for innovation and R&D activity in the creative industries

Authors: McDonald; Jordan;

Detecting Dark Matter Data:data gaps for innovation and R&D activity in the creative industries

Abstract

How can we make data collection, processing & analysis more useful for data consumers (like policymakers and funders) and for data producers (like businesses and individual creatives)? Through our research we found that though there are a wide variety of quantitative and qualitative data sources on the creative industries available, policymakers and creative practitioners alike still struggle to use data effectively as a decision support tool in their strategic thinking and planning. In particular, there is tacit knowledge that sector activity occurs which is not well-captured through traditional economic analysis mechanisms like Companies House data or the Office for National Statistics’ Annual Business Survey, a data gap that one research participant referred to as the “dark matter” of the sector. Our research focused especially on data gaps for innovation and R&D activity in the creative industries. To support better decision-making for innovation in the creative industries, we need to shine a light on this “dark matter,”: improve existing data sources with richer and more frequently updated information; streamline data collection processes to make them less onerous particularly for small businesses; and encourage greater transparency about how and where data is used and shared after it is collected. In this paper we outline our findings on how different groups of stakeholders think about innovation and data with respect to the creative industries. We look at where different viewpoints on these concepts create challenges for devising appropriate data capture, sharing and analysis mechanisms for the creative industries. We provide four core recommendations to key stakeholder groups working in and around the creative industries: policymakers and policy advisors; membership organisations and trade bodies; individual creatives and creative companies; and data platform providers. We close with a series of provocation questions to spark reflection and open opportunities for change from each of these perspectives.

This project is a collaboration between Creative Informatics, CRAIC: The Creative Research And Innovation Centre at Loughborough London University, and industry partner, The Data City. Creative Informatics is a partnership between The University of Edinburgh, Edinburgh Napier University, Creative Edinburgh and Codebase. Creative Informatics is funded by: the Creative Industries Clusters Programme managed by the Arts & Humanities Research Council as part of the Industrial Strategy; the Scottish Funding Council; and the Edinburgh and South East Scotland City Region Deal Data Driven Innovation Initiative. The Creative Research And Innovation 'centre' provides a forum for the range of research and policy programmes being developed by Andrew Chitty and Graham Hitchen, in their roles as Professor and Senior Enterprise Fellow – respectively – at the Institute for Media and Creative Industries at Loughborough London. The Data City is a data as a service company providing unique, real-time industrial data on the most dynamic emerging economic sectors.

Country
United Kingdom
Related Organizations
Keywords

creative industries, policymaking, creative industries data

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green