Novel network analysis of all research requests in Scotland

ObjectivesResearch Data Scotland (RDS) launched the Researcher Access Service (RAS) in 2024. The service was codesigned to meet researcher and data controller needs and maximise the value of and scale administrative linked data in Scotland. Analysis was carried out on all research requests in Scotland since 2015 to identify datasets most commonly asked for in combination to scale the service efficiently. MethodA dataset that included all research requests in Scotland since 2015 was analysed to identify all unique datasets requested for research in Scotland. Network analysis was then used to understand the relationships and connections between datasets. The networks were visualised, and different parameters were used to better understand connections. Community detection was used to identify the datasets which needed to be provided together to maximise the number of projects which could use the Researcher Access Service pathway. ResultsThe work identified that there have been 123 unique datasets requested for research in Scotland since 2015. Of these 123, 114 were not already available through the Researcher Access Service. The top five most requested datasets that were requested in combination with RAS datasets, alongside the number of times requested are as follows: SBR (Scottish Birth Record) – 131 SICSAG (Scottish Intensive Care Society Audit Group) – 84 ECOSS (Electronic Communication of Surveillance in Scotland) – 75 SCI Diabetes (Diabetes Register) – 70 NRS Stillbirths – 64 A number of communities of datasets were identified, for example Education datasets, health datasets, and imaging datasets. Identifying these communities of dataset requests, the need for groups of datasets to be provided together through the RAS became evident. ConclusionThe work has informed decisions on how best to scale the service. Only when we consider the combinations of datasets being requested and the connections between datasets, are we able to design a modern, scalable and sustainable service.

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Publication Details

Journal
International Journal for Population Data Science
Published
2025-08-28
DOI
https://doi.org/10.23889/ijpds.v10i4.3181
Primary Topic
Healthcare Systems and Technology
Type
article
Field-Weighted Citation Impact
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article

Novel network analysis of all research requests in Scotland

Stella Telford, Rosie Seaman, Jennifer Muir
International Journal for Population Data Science
Healthcare Systems and Technology
article

Novel network analysis of all research requests in Scotland

Stella Telford, Rosie Seaman, Jennifer Muir
article en

Abstract

ObjectivesResearch Data Scotland (RDS) launched the Researcher Access Service (RAS) in 2024. The service was codesigned to meet researcher and data controller needs and maximise the value of and scale administrative linked data in Scotland. Analysis was carried out on all research requests in Scotland since 2015 to identify datasets most commonly asked for in combination to scale the service efficiently. MethodA dataset that included all research requests in Scotland since 2015 was analysed to identify all unique datasets requested for research in Scotland. Network analysis was then used to understand the relationships and connections between datasets. The networks were visualised, and different parameters were used to better understand connections. Community detection was used to identify the datasets which needed to be provided together to maximise the number of projects which could use the Researcher Access Service pathway. ResultsThe work identified that there have been 123 unique datasets requested for research in Scotland since 2015. Of these 123, 114 were not already available through the Researcher Access Service. The top five most requested datasets that were requested in combination with RAS datasets, alongside the number of times requested are as follows: SBR (Scottish Birth Record) – 131 SICSAG (Scottish Intensive Care Society Audit Group) – 84 ECOSS (Electronic Communication of Surveillance in Scotland) – 75 SCI Diabetes (Diabetes Register) – 70 NRS Stillbirths – 64 A number of communities of datasets were identified, for example Education datasets, health datasets, and imaging datasets. Identifying these communities of dataset requests, the need for groups of datasets to be provided together through the RAS became evident. ConclusionThe work has informed decisions on how best to scale the service. Only when we consider the combinations of datasets being requested and the connections between datasets, are we able to design a modern, scalable and sustainable service.

International Journal for Population Data ScienceVol. 10(4)
Openalex Percentile: Top 73%
Healthcare Systems and Technology
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