CGIAR, the world’s largest global agricultural innovation network, used our Web of Science™ API to significantly reduce their manual workload. In this article, Valentina De Col and Enrico Bonaiuti share their story about what this involved and how it led to efficient and reliable data assessment.
CGIAR, the world’s largest global agricultural innovation network dedicated to reducing poverty, enhancing food and nutrition security, and improving natural resources and ecosystem services, has recently introduced a new tool, the M-QAP (Monitoring, Evaluation, and Learning Quality Assurance Processor), to help assess the quality of its scientific publications. The tool uses APIs (Application Programming Interfaces) and, among them, the Web of Science API to make sure publications are peer-reviewed and indexed in the Web of Science Core Collection™.
The Web of Science API has recently processed more than 2,500 articles during quality assurance of the CGIAR Annual Performance Report. By automatically validating, articles were indexed in the Web of Science Core Collection, our API helped CGIAR reduce their manual workload and guarantee efficient and reliable data validation.
Publications are a key indicator
Scientific publications are one of the outputs of research efforts and investments produced by CGIAR. CGIAR reports annually on the number of peer-reviewed publications as well as each peer-reviewed publication’s Web of Science Core Collection and open access status.
How CGIAR saved time and resources
During the quality assurance of the 2020 CGIAR Annual Performance Report, the Web of Science API processed more than 2,500 articles with a Digital Object Identifier (DOI) and automatically validated around 90% as covered in Web of Science Core Collection. This had a significant impact in reducing manual quality assessment work, saving both time and resources, and improving the overall performance of the process within the organisation when assessing the quality of scientific publications.
“This had a significant impact in reducing manual quality assessment work, saving both time and resources. It also improved the overall performance of the process within the organization when assessing the quality of scientific publications.”
Reducing the workload of data entry and curation
Since 2020, the Web of Science API has been added in the M-QAP, a new tool integrated into the centralised CGIAR web service CLARISA (CGIAR Level Agricultural Results Interoperable System Architecture) and in two Management Information System platforms MEL (Monitoring, Evaluation, and Learning) and MARLO (Managing Agricultural Research for Learning and Outcomes).
The tool has been developed and implemented by the MEL team at the International Center for Agricultural Research in Dry Areas (ICARDA) in collaboration with the Innovations and Business Development Team at the Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT).
The Web of Science API helped CGIAR to:
- validate scientific publications in real-time, ensuring they are peer-reviewed and indexed in the Web of Science Core Collection
- support their annual quality assurance process
- save time and resources by removing the need for manual processes
- increase efficiency and accuracy by reducing human errors and having a reproducible, standardised, and reliable source of information through the API
- support decision-making and assist in the monitoring, evaluation, and oversight of scientific outputs.
A challenge for the future: Using the full potential the Web of Science API
Further integrations of the M-QAP tool within CLARISA, MEL and MARLO could expand data retrieval and collection by making use of a larger dataset available from the Web of Science API. This could enhance CGIAR’s analysis and assessment capabilities and support the evaluation of the quality of science, for instance through bibliometrics.
The use of a benchmark academic database such as the Web of Science™ has allowed a consistent, reliable, and replicable retrieval of data. This brings value to the overall CGIAR quality assessment process and supports its efforts towards the promotion of scientific quality and, ultimately, the effectiveness of the research for development.
Interested in learning more about our Web of Science API? Contact us today.
About the authors
Valentina De Col is the Agricultural Information System Officer, Monitoring Evaluation and Learning at the International Center for Agricultural Research in the Dry Areas (ICARDA).
Enrico Bonaiuti is the Research Team Leader, Monitoring Evaluation and Learning at the International Center for Agricultural Research in the Dry Areas (ICARDA) and Program Management Officer at the International Potato Center (CIP).
- De Col, V., Jani, S., Bonaiuti, E. (2021). Monitoring-Quality Assurance Processor-API – A tool to support CGIAR Quality Assurance process for peer-reviewed publications. International Center for Agriculture Research in the Dry Areas (ICARDA). https://hdl.handle.net/20.500.11766/66480
- De Col, V., Jani, S., Rünzel, M., Tobón, H., Almanzar, M.R., Bonaiuti, E. (2021). Case study on the Monitoring-Quality Assurance Processor-API – A tool to support CGIAR Quality Assurance process for peer-reviewed publications. International Center for Agriculture Research in the Dry Areas (ICARDA). https://hdl.handle.net/20.500.11766/66480