CGIAR Climate Change Synthesis Scripts

cg.creator.identifierAlan S. Orth: 0000-0002-1735-7458en_US
cg.identifier.dataurlhttps://hdl.handle.net/20.500.11766.1/FK2/Z98CZOen_US
cg.identifier.doihttps://doi.org/10.5281/zenodo.14329329en_US
cg.subject.ilriDATAen_US
cg.subject.ilriKNOWLEDGE AND INFORMATIONen_US
cg.subject.impactPlatformClimate Changeen_US
dc.contributor.authorOrth, Alan S.en_US
dc.date.accessioned2024-12-09T12:45:57Zen_US
dc.date.available2024-12-09T12:45:57Zen_US
dc.identifier.urihttps://hdl.handle.net/10568/163212en_US
dc.titleCGIAR Climate Change Synthesis Scriptsen_US
dcterms.abstractCode used to generate datasets for the 2024 synthesis of CGIAR work on climate change. Items matching the inclusion criteria were retrieved from eight CGIAR institutional repositories. This Python-based extract, transform, and load (ETL) pipeline filtered, merged, and normalized the metadata to ensure consistent use of date formats, multi-value separators, and identifiers. Naive deduplication was performed using titles and DOIs. Items identified to have been included erroneously due to incorrect repository metadata (mislabeled preprints, non-English, etc) were excluded. We used Crossref and Unpaywall to fill in gaps for missing metadata such as usage (license) and access rights because this information can be valuable to researchers. All other metadata was used as-is from the respective repositories. Bibliographic metadata in the CSV output is oriented towards use with the Rayyan platform for systematic literature review.en_US
dcterms.accessRightsOpen Accessen_US
dcterms.bibliographicCitationOrth, A. 2024. CGIAR Climate Change Synthesis Scripts v1.0.0. Source Code. Nairobi, Kenya: ILRI.en_US
dcterms.issued2024-12-09en_US
dcterms.licenseGPL-3.0-onlyen_US
dcterms.publisherInternational Livestock Research Instituteen_US
dcterms.subjectpythonen_US
dcterms.typeSource Codeen_US

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