Detecting Dark Matter Data: data gaps for innovation and R&D activity in the creative industries
Description
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.
Notes
Files
Detecting Dark Matter Data (1).pdf
Files
(5.0 MB)
Name | Size | Download all |
---|---|---|
md5:baa5465610d9f3b1a48763fa700a4a37
|
5.0 MB | Preview Download |
Additional details
Funding
- UK Research and Innovation
- Creative Informatics: Data Driven Innovation for the Creative Industries AH/S002782/1