Big Data Coordination Platform: Full Proposal 2017-2022

This proposal for a Big Data and ICT Platform therefore focuses on enhancing CGIAR and partner capacity to deliver big data management, analytics and ICT-focused solutions to CGIAR target geographies and communities. The ultimate goal of the platform is to harness the capabilities of Big Data to accelerate and enhance the impact of international agricultural research. It will support CGIAR’s mission by creating an enabling environment where data are expertly managed and used effectively to strengthen delivery on CGIAR SRF’s System Level Outcome (SLO) targets. Critical gaps were identified during the extensive scoping consultations with CGIAR researchers and partners (provided in Annex 8). The Platform will achieve this through ambitious partnerships with initiatives and organizations outside CGIAR, both upstream and downstream, public and private. It will focus on promoting CGIAR-wide collaboration across CRPs and Centers, in addition to developing new partnership models with big data leaders at the global level. As a result, CGIAR and partner capacity will be enhanced, external partnerships will be leveraged, and an institutional culture of collaborative data management and analytics will be established. Important international public goods such as new global and regional datasets will be developed, alongside new methods that support CGIAR to use the data revolution as an additional means of delivering on SLOs

Alliance for a Data Revolution: CGIAR Platform for Big Data in Agriculture 2017 Convention Report

On September 19-22, 2017 the Consultative Group for International Agricultural Research1 (CGIAR) gathered over 300 local and international researchers, non-profits, public and private sector actors for the first CGIAR Platform for Big Data in Agriculture Convention, hosted by the International Center for Tropical Agriculture (CIAT) in Palmira, Colombia. The Convention marked the programmatic launch of the Platform, which aims to enable the development sector to embrace data and other digital technology approaches to solve agricultural development problems faster, better and at greater scale. The Platform works across the CGIAR network and CGIAR Research Programs (CRPs) and with the gamut of stakeholders in the agriculture sector as they grapple with creation, curation, and sharing data to enable new approaches to complex development challenges. The Platform is designed around three strategic pillars: Organize, Convene, and Inspire. The first aims to organize data so datasets are findable, accessible, and interoperable so they can be used increasingly in big data analytics. In addition, this pillar will develop open digital infrastructures for the sector that support the CGIAR’s work and enable new partnerships and innovations. The aim to convene analysts, researchers and public, private and non-profit actors in the agriculture sector will build new partnerships that both shape and fully leverage digital technologies in support of global agricultural development. The final pillar is to inspire these actors to push the limits of research and innovation to generate new data-driven approaches that solve real world development problems faster, cheaper, and more efficiently

CGIAR Platform for Big Data in Agriculture - Plan of Work and Budget 2021

The CGIAR Platform for Big Data in Agriculture is a cross-cutting program of the global CGIAR consortium of non-profit research institutes looking into virtually every aspect of food security spanning: genomics, breeding, agroecology, climate science, and the socioeconomic drivers and context of food systems change. The Platform tends to data standards and data sharing, digital innovation strategy and technology transfer, and research into the intersection of digital technologies and agricultural development in emerging regions

Extension of SDG Interface Ontology with the indicators of the CGIAR Strategic Research Framework

SDG Interface Ontology integrates the concepts used by the CGIAR Research Framework and the processus described by the SR

Inspire Challenge Award: Real-time diagnostics for devastating wheat rust

Demonstrated that a small gene sequencing device could be used in the field to identify a strain of wheat rust within 48 hours, dramatically reducing the response cycle time. The pilot demonstrated the first-ever accurate identification of individual yellow rust strains just as the disease emerged in the field

Agronomy Field Information Management System (AgroFIMS)

AgroFIMS has been tested by potential users from several CGIAR Centers and partners through two user workshops. Feedback has been very positive, and work is ongoing with KDDart Technologies to enable digital data collection using AgroFIMS templates. A field testing version of AgroFIMS-KDSmart will be available in summer 2019

TALIA, the first agricultural virtual extension agent operated entirely by AI

We created a small prototype that we tested among partners using Telegram. We feel that Watson has true potential to build a complete agricultural assistant to support farmers, however it is a complex endeavor where in-depth experience with Watson is required

Predicting yields using biophysical crop simulations, machine learning and remote sensing in India

We tested the innovation and piloted it using ground truth yield data collected by means of crop cutting experiments in Odisha. Before starting to finalize the tool for adoption by insurance providers, the tool will be fine-tuned in the course of 2021

GARDIAN Labs, an open-access service to enable researchers to collaborate and share data and analytic approaches and tools

Successful use of the analytic environment for cross-cutting research for climate adaptation and crop nutrition