Leveraging CrossRef Application Programming Interface to identify policy-relevant research conducted in South Africa: a bibliometric analysis
1
Health Information, Epidemiology, Research, Monitoring and Evaluation Cluster, National Department of Health, Pretoria, South Africa
2
Research and Implementation Science Unit, Health Systems Trust, Pretoria, South Africa
Popul. Med. 2026;8(Supplement Supplement 1):A879
ABSTRACT
BACKGROUND:
Large scale Artificial Intelligent (AI) models could transform the contribution of research towards achievement of Sustainable Development Goals (SDGs). Countries need to monitor and report progress on SDGs using data collected from multiple resources to support evidence-based decision-making. Research that supports efforts towards achievement of SDGs needs to be captured and reported at a country level. Since 2015, South Africa has developed a National Health Research Database (NHRD) which serves as a repository of health-related research conducted in public health facilities. We conducted a bibliometric analysis using CrossRef Application Programming Interface (API) and mapping of SDG relevant research from NHRD records between 2015 and 2023.
METHODS:
A bibliometric analysis of 5,270 registered and approved study records from the NHRD was conducted using titles in proposal format. The workflow to extract publication metadata included data extraction and cleaning, country identification and verification. The publication metadata retrieved via the CrossRef API included the digital object identifiers (DOIs), author names, title, publication year and study country. Further classification of SDG relevant research was conducted on Dimensions Research GPT AI tool.
RESULTS:
Among the 5,270 records, 397 (7.5%) publication titles were indexed on CrossRef API tool based on fuzzy matching with a threshold of >70%. The generated DOIs were further validated using online libraries with a total of 172/397 (43.3%) publications correctly identified. The SDG mapping demonstrated dominant contributions to SDG 3 (targets 3.8, 3.3 and 3.4). Significant cross-cutting contributions evident for SDGs 4, 5, 9, 10, and 17 were observed.
CONCLUSIONS:
The use AI tools provide an attractive methodology to map SDG related publications derived from national datasets. However, a more accurate estimate of the publication rate of registered and approved NHRD studies, ongoing follow-up with researchers is recommended to capture study updates for knowledge translation and dissemination.
Large scale Artificial Intelligent (AI) models could transform the contribution of research towards achievement of Sustainable Development Goals (SDGs). Countries need to monitor and report progress on SDGs using data collected from multiple resources to support evidence-based decision-making. Research that supports efforts towards achievement of SDGs needs to be captured and reported at a country level. Since 2015, South Africa has developed a National Health Research Database (NHRD) which serves as a repository of health-related research conducted in public health facilities. We conducted a bibliometric analysis using CrossRef Application Programming Interface (API) and mapping of SDG relevant research from NHRD records between 2015 and 2023.
METHODS:
A bibliometric analysis of 5,270 registered and approved study records from the NHRD was conducted using titles in proposal format. The workflow to extract publication metadata included data extraction and cleaning, country identification and verification. The publication metadata retrieved via the CrossRef API included the digital object identifiers (DOIs), author names, title, publication year and study country. Further classification of SDG relevant research was conducted on Dimensions Research GPT AI tool.
RESULTS:
Among the 5,270 records, 397 (7.5%) publication titles were indexed on CrossRef API tool based on fuzzy matching with a threshold of >70%. The generated DOIs were further validated using online libraries with a total of 172/397 (43.3%) publications correctly identified. The SDG mapping demonstrated dominant contributions to SDG 3 (targets 3.8, 3.3 and 3.4). Significant cross-cutting contributions evident for SDGs 4, 5, 9, 10, and 17 were observed.
CONCLUSIONS:
The use AI tools provide an attractive methodology to map SDG related publications derived from national datasets. However, a more accurate estimate of the publication rate of registered and approved NHRD studies, ongoing follow-up with researchers is recommended to capture study updates for knowledge translation and dissemination.
| eISSN: | 2654-1459 |
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