Big Data inCGIAR

Elizabeth ArnaudBioversity International

22nd September, IGAD pre-meeting, INRA, Paris

CIAT: Big Data for Climate Smart Agriculture

CIAT analysis large, real-world data sets from annual survey on rice to produce recommendations much more quickly. 1. Harvest results of annual surveys and agronomic

experiments from National Private Companies2. Get Planting times for specific sites and seasonal forecasts3. pairing historical records with state-of-the-art seasonal

forecasts4. Analyses with advanced algorithms from biology, robotics

and neurosciences5. Searches for weather patterns in previous years and

checked which varieties did best in those years Result: Identify the most productive rice varieties

and planting times for specific sites and seasonal forecasts. Recommendations could potentially boost yields by 1 to 3 tons per hectare.

Crowdsourcing varieties

500 farmers per site will be given 3 blind varieties in small quantities to be tested under their own conditions (the crowdsourcing approach)

CGIAR Big Data Large amounts of data accumulated by

CGIAR Centers to be published as Open Data Highthrouput production of data: Highthrouput Genotyping Highthrouput Phenotyping Remote Sensing data Citizen Sciences ( Crowd Sourcing)

Open Data-Open Access Strategy for CGIAR

8 Agrifood System research programmes Big Data platform will support the 8 CRPs

1. Dryland Cereals and Legumes Agri-food System

2. Fish Agri-food Systems3. Forest and Agroforestry Landscapes4. Livestock Agri-food Systems5. Maize Agri-food Systems6. Rice Agri-food Systems7. Roots, Tubers and Bananas Agri-food Systems8. Wheat Agri-food Systems

5 Global Integrative Programmes

to ensure that research results deliver solutions at the national level that can be scaled up and out to other countries and regions.

1. Genebanks ++2. Nutrition and Health3. Water Land and Ecosystems (including

soils); 4. Climate Change5. Policies, Institutions and Markets research

Big Data and ICT: Call for Expressions of Interest A number of scientific organizations developed

high performance computing facilities and big data analytical capabilities.

A major opportunity exists for the CGIAR to leverage this investment in capability and infrastructure

Strong partnerships across the Consortium and beyond it,

work with existing and promising efforts to support the creation of a global-agri-informatics platform and network that ensures compliance with Linked Open Data and other standard interoperability protocols.

IFPRI-led EOI: Tools for Driving Interdisciplinary and Collaborative Big Data Analytics Implementation of CGIAR Survey Platform Data

for data collected through mobile phones from connected sensor network across trial sites Further development of agricultural ontologies

with research communities’ inputs Implementing Linked Open Data and APIs in data

repositories Enabling Data Discovery Use cases:

Scalable Satellite-based Crop Yield Mapper (SYCM): Crop Water Productivity (CWP) Remote Sensing for Agro-biodiversity Monitoring

Call for Pre-proposals for CGIAR Research Programmes http://www.cgiar.org/our-strategy/second

-call-for-cgiar-research-programs/crp-2nd-call-pre-proposal-submissions/