A Comprehensive Database of CGIAR Climate-Related Journal Articles (2012–2023)

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cg.contributor.affiliationInternational Livestock Research Instituteen_US
cg.contributor.affiliationCGIAR System Organizationen_US
cg.contributor.affiliationGroningen Universityen_US
cg.contributor.affiliationIndependent Consultanten_US
cg.contributor.donorCGIAR Trust Funden_US
cg.creator.identifierAlan S. Orth: 0000-0002-1735-7458en_US
cg.creator.identifierAditi Mukherji: 0000-0002-8061-4349en_US
cg.identifier.urlhttps://hdl.handle.net/20.500.11766.1/FK2/Z98CZOen_US
cg.subject.impactAreaClimate adaptation and mitigationen_US
cg.subject.impactPlatformClimate Changeen_US
cg.subject.sdgSDG 13 - Climate actionen_US
dc.contributor.authorOrth, Alan S.en_US
dc.contributor.authorBosire, Caroline K.en_US
dc.contributor.authorRabago, Lauraen_US
dc.contributor.authorVaidya, Shrijanaen_US
dc.contributor.authorRajbhandari, Sitashmaen_US
dc.contributor.authorPradhan, Prajalen_US
dc.contributor.authorMukherji, Aditien_US
dc.date.accessioned2024-12-06T11:45:29Zen_US
dc.date.available2024-12-06T11:45:29Zen_US
dc.identifier.urihttps://hdl.handle.net/10568/163158en_US
dc.titleA Comprehensive Database of CGIAR Climate-Related Journal Articles (2012–2023)en_US
dcterms.abstractThis dataset contains bibliographic metadata for 3,466 peer-reviewed journal articles used in the 2024 synthesis of CGIAR work on climate change. The metadata was retrieved from eight CGIAR institutional repositories, processed using a Python-based extract, transform, and load (ETL) pipeline, and screened for climate change relevance in Rayyan. Through harvesting we identified 5,487 journal articles matching the inclusion criteria in CGIAR repositories: - Issue date between 2012 and 2023 - The words "climate change" in the title, abstract, or keywords - English language - DOI assigned The bibliographic metadata was merged and normalized to ensure consistent use of date formats, multi-value separators, and identifiers. The ETL pipeline used titles and DOIs to identify and remove duplicates, as well as exclude any others that had been erroneously included due to incorrect repository metadata we could identify (mislabeled preprints, non-English, etc.). We used Crossref, Unpaywall, and OpenAlex to fill in gaps for missing metadata such as usage (license) and access rights, affiliations, and publishers because this information can be valuable to researchers. Minor normalization was performed on affiliations, countries, and publishers, but all other metadata was used as-is from the respective repositories. 4,495 journal articles were uploaded to the Rayyan platform for a blinded screening of climate change relevance by a team trained in systematic literature review methodology. Reviewers excluded journal articles not deemed to be climate change related or identified as further duplicates. This dataset is useful for understanding CGIAR’s research on climate change. Potential areas of work could be to use machine learning to classify thematic areas. The Python code used to perform the harvesting and processing of this dataset can be found on GitHub: https://github.com/ilri/cgiar-climate-change-synthesisen_US
dcterms.accessRightsOpen Accessen_US
dcterms.bibliographicCitationAlan Orth, Caroline K. Bosire, Laura Rabago, Shrijana Vaidya, Sitashma Rajbhandari, Prajal Pradhan, Aditi Mukherji. (5/12/2024). A Comprehensive Database of CGIAR Climate-Related Journal Articles (2012–2023) [Bibliographic metadata].en_US
dcterms.issued2024-12-05en_US
dcterms.languageenen_US
dcterms.licenseCC-BY-4.0en_US
dcterms.publisherInternational Livestock Research Instituteen_US
dcterms.relationhttps://github.com/ilri/cgiar-climate-change-synthesisen_US
dcterms.relationhttps://hdl.handle.net/10568/172611en_US
dcterms.subjectclimate changeen_US
dcterms.typeDataseten_US

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