1. Using collective intelligence methods to improve government data infrastructures and promote the use of complex data: The example of the Northern Ireland Longitudinal Study.
- Author
-
Lowry, Estelle, Hogan, Michael, Moriarty, John, Harney, Owen, Ruijer, Erna, Pilch, Monika, Groarke, Jenny, Hanlon, Michelle, and Shuttleworth, Ian
- Subjects
Collective intelligence ,Data ,Data infrastructure ,Open access ,Humans ,Government ,Longitudinal Studies ,Northern Ireland ,Policy ,Research Design - Abstract
BACKGROUND: This paper discusses how collective intelligence (CI) methods can be implemented to improve government data infrastructures, not only to support understanding and primary use of complex national data but also to increase the dissemination and secondary impact of research based on these data. The case study uses the Northern Ireland Longitudinal Study (NILS), a member of the UK family of census/administrative data longitudinal studies (UKLS). METHODS: A stakeholder-engaged CI approach was applied to inform the transformation of the NILS Research Support Unit (RSU) infrastructure to support researchers in their use of government data, including collaborative decision-making and better dissemination of research outputs. RESULTS: We provide an overview of NILS RSU infrastructure design changes that have been implemented to date, focusing on a website redesign to meet user information requirements and the formation of better working partnerships between data users and providers within the Northern Ireland data landscape. We also discuss the key challenges faced by the design team during this project of transformation. CONCLUSION: Our primary objective to improve government data infrastructure and to increase dissemination and the impact of research based on data was a complex and multifaceted challenge due to the number of stakeholders involved and their often conflicting perspectives. Results from this CI approach have been pivotal in highlighting how NILS RSU can work collaboratively with users to maximize the potential of this data, in terms of forming multidisciplinary networks to ensure the research is utilized in policy and in the literature and providing academic support and resources to attract new researchers.
- Published
- 2023