دورية أكاديمية
Using collective intelligence methods to improve government data infrastructures and promote the use of complex data: The example of the Northern Ireland Longitudinal Study.
| العنوان: | Using collective intelligence methods to improve government data infrastructures and promote the use of complex data: The example of the Northern Ireland Longitudinal Study. |
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| المؤلفون: | Lowry E; School of Natural and Built Environment, Queen's University Belfast, University Street, BT7 1NN, Belfast, Northern Ireland. e.lowry@qub.ac.uk., Hogan MJ; School of Psychology, University of Galway, Galway, Ireland. michael.hogan@nuigalway.ie., Moriarty J; School of Social Sciences, Education and Social Work, Queen's University Belfast, BT7 1NN, Belfast, Northern Ireland., Harney OM; School of Psychology, University of Galway, Galway, Ireland., Ruijer E, Pilch M; School of Medicine, Trinity College Dublin, Dublin, Ireland., Groarke JM; School of Psychology, University of Galway, Galway, Ireland., Hanlon M; School of Psychology, University of Galway, Galway, Ireland., Shuttleworth I; School of Natural and Built Environment, Queen's University Belfast, University Street, BT7 1NN, Belfast, Northern Ireland. |
| المصدر: | Health research policy and systems [Health Res Policy Syst] 2023 Dec 18; Vol. 21 (1), pp. 134. Date of Electronic Publication: 2023 Dec 18. |
| نوع المنشور: | Journal Article; Review |
| اللغة: | English |
| بيانات الدورية: | Publisher: BioMed Central Country of Publication: England NLM ID: 101170481 Publication Model: Electronic Cited Medium: Internet ISSN: 1478-4505 (Electronic) Linking ISSN: 14784505 NLM ISO Abbreviation: Health Res Policy Syst Subsets: MEDLINE |
| أسماء مطبوعة: | Original Publication: [London] : BioMed Central, 2003- |
| مواضيع طبية MeSH: | Government* , Research Design*, Humans ; Longitudinal Studies ; Northern Ireland ; Policy |
| مستخلص: | 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. (© 2023. The Author(s).) |
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| فهرسة مساهمة: | Keywords: Collective intelligence; Data; Data infrastructure; Open access |
| تواريخ الأحداث: | Date Created: 20231219 Date Completed: 20231221 Latest Revision: 20231221 |
| رمز التحديث: | 20231221 |
| مُعرف محوري في PubMed: | PMC10726592 |
| DOI: | 10.1186/s12961-023-01070-x |
| PMID: | 38111046 |
| قاعدة البيانات: | MEDLINE |
Find this article in full text from Springer Verlag. 
Full Text Finder | تدمد: | 1478-4505 |
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| DOI: | 10.1186/s12961-023-01070-x |