CGIAR is committed to the widespread dissemination of the results of its research and activities. CGIAR has made a strong commitment to open access and open data (OA-OD), and all Centers have signed CGIAR’s 2013 Open Access and Data Management Policy. The rationale behind OA-OD is to achieve the maximum impact to advantage the poor, especially smallholder farmers in developing countries.
OA-AD and initiatives of the Big Data Platform
BIG DATA 2018 annual report
In 2018, BIG DATA launched the Global Agricultural Research Data Innovation Acceleration Network (GARDIAN), a pan-CGIAR data search and discoverability portal. For the first time, datasets, publications and crop traits became discoverable and easily accessible in one portal, regardless of where they were archived across CGIAR’s 15 Research Centers and 11 genebanks.
A number of data ontologies were developed that enable the cross-domain data querying and exploration necessary to form and address complex research questions across CGIAR.
- An agronomy ontology developed by Bioversity International and IFPRI, which was incorporated into the Agronomy Field Information Management System (AgroFIMS).
- A mature crop ontology with new species and trait classes, which was released through a collaboration led by Bioversity International.
Source: BIG DATA, AR 2018.
OA-OD enhances the visibility, accessibility and impact of research and development activities, and improves the speed, efficiency and efficacy of research. It enables interdisciplinary research; assists novel computation of the research literature; and allows the global public to benefit from CGIAR research.
It also ensures that the results of research and activities can more easily and collectively build the infrastructure necessary for CGIAR to be at the forefront of the OA-OD for agriculture movement.
To further support CGIAR’s open access objectives, BIG DATA was launched May 2017. It aims to mobilize CGIAR data to accelerate research and spur new data-driven innovations, build data collaboration internally and externally, and leverage CGIAR expertise while claiming a unique leadership voice in digital agriculture. It also supports and promotes open data.
In 2018, BIG DATA created new data-driven capabilities, built new digital partnerships and alliances, and developed digital innovations.
Making data more efficient and accessible
GLDC 2018 annual report
For GLDC, implementation of strong data management and analytical research support tools has greatly benefited crop breeding activities.
GLDC data management systems and tools include the Breeding Management System, the genomic data management system Genomic Open-Source Breeding Informatics Initiative and public data sharing portals such as Dataverse and the Comprehensive Knowledge Archive Network.
Such databases render crop breeding highly efficient through access to pedigrees, electronic field books and in-field auto data validation. In addition, automated workflows to generate barcodes, tools for auto-generation of field books with updated records of pedigree data and quick exploratory statistical analysis aid efficiency and the timely flow of communication.
As an example, electronic field books have eliminated the need to key in data and enabled the data in the database to be available immediately after recording. This reduces the time for breeding decisions and incorporates greater rigor by integrating high quality statistical data analysis. As each plot – or plant in some cases – is barcoded, researchers can perform genomic selection in routine breeding by linking barcodes from phenotypic databases to genomic databases.
Source: GLDC, AR 2018.