CGIAR data harmonization guidelines: Core variables for FAIR and AI-Ready data

Files

https://hdl.handle.net/10883/36872 (905.52 KB, pdf)

Authors

Gardeazabal, Andrea

Laporte, Marie-Angélique

Poole, Elizabeth

Longobardi, Lorenzo

Nagaraji, Satish

Date Issued

Metadata

Citation

Gardeazabal Monsalve, A., Devare, M., Dreher, K. A., Laporte, M. A., Aubert, C. Sonder, K., Poole, E., Longobardi, L., Azzarri, C., & Nagaraji, S. (2025). CGIAR data harmonization guidelines: Core variables for FAIR and AI-Ready data. CIMMYT. https://hdl.handle.net/10883/36872

Permanent link to cite or share this item

https://hdl.handle.net/10568/181246

External link to download this item

https://hdl.handle.net/10883/36872

Author ORCID identifiers

Andrea Gardeazábal-Monsalve https://orcid.org/0000-0003-1529-4200
Medha Devare https://orcid.org/0000-0003-0041-4812
Kate Dreher https://orcid.org/0000-0003-4652-4398
Marie-Angélique Laporte https://orcid.org/0000-0002-8461-9745
Kai Sonder https://orcid.org/0000-0001-9672-5361
Carlo Azzarri https://orcid.org/0000-0002-0345-1304

Organizations Affiliated to the Authors

International Maize and Wheat Improvement Center

Investors/sponsors

CGIAR Trust Fund

CGIAR Programs and Accelerators

Digital Transformation

Collections

CGIAR Accelerator on Digital Transformation

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Type

Review Status

Internal Review

Language

en

AGROVOC Keywords

data collection; information processing; datasets; agronomy; breeding; socioeconomics; gender; livestock; climate; environment

Access Rights

Open Access

Usage Rights

Attention