The Monitoring, Evaluation, and Learning Quality Assurance Processor (M-QAP) is a tool designed to extract publication metadata using Application Programming Interfaces (APIs) from various sources, including Web of Science, Scopus, Unpaywall, Crossref, ORCID, and Altmetrics. This tool was developed to support CGIAR institutions in reporting to its dashboard (https://www.cgiar.org/impact/results-dashboard/) and ensure that publications with a Digital Object Identifier (DOI) are validated against the above sources.

Over time, M-QAP has evolved to perform additional functions, such as:

• Retrieving metadata from CGSpace (https://cgspace.cgiar.org/home), CGIAR interim repository, to support reporting within the Performance and Results Management System (PRMS);

• Calculating the Findability, Accessibility, Interoperability, and Reuse (FAIR) score for CGIAR knowledge products;

• Matching institution names with CGIAR lists through an AI-powered text-matching feature. This AI suggests pairings when the similarity test is below 100%, allowing users to confirm them. It will only automatically pair institutions when they have been manually matched multiple times. However, users are encouraged to confirm matches, even at 100%, as the tool is still in its pilot phase.

Originally conceived as a proof of concept by the Monitoring, Evaluation, and Learning team (https://mel.cgiar.org/) at the International Center for Agricultural Research in the Dry Areas (ICARDA) (http://icarda.org/), M-QAP received financial backing from the System Management Office (SMO) (https://www.cgiar.org/how-we-work/governance/system-organization/system-management-office/). The tool has been developed by CodeObia (https://codeobia.com/), and the pilot version’s code is available on GitHub at https://github.com/icarda-git/M-QAP.

References

Feger S., De Col V., Al-Najdawi M., Cadavid J., Tobon H., Martinez G., Bonaiuti E. (2023). Introducing FAIR Scores in a Global Agricultural Science Reporting Service: An Analysis of the First Reporting Period. Beirut, Lebanon. https://hdl.handle.net/20.500.11766/68495

De Col V., Bonaiuti E. (2022). How the Web of Science enables innovation in agriculture. Clarivate blog. https://clarivate.com/blog/how-the-web-of-science-enables-innovation-in-agriculture/

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. https://hdl.handle.net/20.500.11766/13115

De Col V., Jani S., Rünzel M., Tobon H., Almanzar M., See D.S., Bonaiuti E. (2021). Case study on the Monitoring-Quality Assurance Processor-API - A tool to support CGIAR Quality Assurance process for peer-reviewed publications. https://hdl.handle.net/20.500.11766/66480