CGIAR Climate Change Synthesis Scripts
Code 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 ens...
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| Format: | Source Code |
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International Livestock Research Institute
2024
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| Online Access: | https://hdl.handle.net/10568/163212 |
| _version_ | 1855537203457818624 |
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| author | Orth, Alan S. |
| author_browse | Orth, Alan S. |
| author_facet | Orth, Alan S. |
| author_sort | Orth, Alan S. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Code 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. |
| format | Source Code |
| id | CGSpace163212 |
| institution | CGIAR Consortium |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | International Livestock Research Institute |
| publisherStr | International Livestock Research Institute |
| record_format | dspace |
| spelling | CGSpace1632122025-01-28T12:21:20Z CGIAR Climate Change Synthesis Scripts Orth, Alan S. python Code 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. 2024-12-09 2024-12-09T12:45:57Z 2024-12-09T12:45:57Z Source Code https://hdl.handle.net/10568/163212 Open Access International Livestock Research Institute Orth, A. 2024. CGIAR Climate Change Synthesis Scripts v1.0.0. Source Code. Nairobi, Kenya: ILRI. |
| spellingShingle | python Orth, Alan S. CGIAR Climate Change Synthesis Scripts |
| title | CGIAR Climate Change Synthesis Scripts |
| title_full | CGIAR Climate Change Synthesis Scripts |
| title_fullStr | CGIAR Climate Change Synthesis Scripts |
| title_full_unstemmed | CGIAR Climate Change Synthesis Scripts |
| title_short | CGIAR Climate Change Synthesis Scripts |
| title_sort | cgiar climate change synthesis scripts |
| topic | python |
| url | https://hdl.handle.net/10568/163212 |
| work_keys_str_mv | AT orthalans cgiarclimatechangesynthesisscripts |