Big Data inCGIAR

Elizabeth Arnaud1, Medha Devare2, Jacob Van Etten1, Jawoo Khoo3, Andy Jarvis4

1 Bioversity International, Consortium Office2, IFPRI3, CIAT4

4th February 2016, AIMS Webinar, FAO

What is CGIAR ? An international organization that advances international

agricultural research for food security.

Photo CGIAR

15 Centers worldwide

40 years of research

Over 8,000 scientists, researchers, technicians, and staff

CGIAR Goals1. Reduced poverty2. Improved food and nutrition security

for health3. Improved natural resource systems

and ecosystem services

Photo B. Wawa/CIMMYT

Big Data (as per IBM)

Volume, Velocity, Variety, Veracity Identify patterns and gain new knowledge to

answer complex and unanswered questions Entreprises remain agile in a rapid evolving

environment

Strategic Collaborations Existing high performance computing facilities and big

data analytical capabilities Leverage this investment in capability and

infrastructure Strong partnerships across the Consortium and beyond

it Example of the Strategic Alliance between Google

Maps and FAO to make geospatial tracking and mapping products more accessible

FAO's José Graziano da Silva and Google's Rebecca Moore celebrate the partnership formalization at COP21 in Paris

Big Data for Agriculture Massive Historical Agricultural Data in distributed

databases and repositories

New Highthrouput Data

Genomics/Genetics/metabolomics Phenotyping Geophysical through Remote sensing Social and Economics Citizen Sciences

Challenge: Secure Food and Health by addressing Yield Gap and Climate Change

Photo: ICRISAT

7 million samples of crop varieties and wild relatives in genebanks worldwide

Using the emerging deluge of omics data to unlock crop diversity on a massive scale

Biodiversity Informatics Platform Currently 62 institutions Initiative facilitated by

Global Crop Diversity Trust, Global Plant Council, International Treaty for PGRFA, CGIAR

http://www.divseek.org/

Mining the omics data as collaborative effort IRRI

Illustration: Australian Phenomics Facility

Big Data for Climate Smart Agriculture

Access to global data should help providing local information

© IISA © CIAT

How CGIAR projects currently apply Big Data Principles ?

Remote sensing project across CGIAR Research Programmes

Bill &Melinda Gates Foundation-supported remote sensing project spans across the CGIAR

Linked to CGIAR Research Programs on Climate Change, Agriculture and Food Security (CCAFS) and on Water, Land and Ecosystems (WLE).

A complete lay of the land will be recorded by Use Unmanned Aerial Vehicles (UAVs) to discern crop types, any present diseases, and the effects of climate change.

Photo: CIP

Drone over sweet potato fields in East Africa

• To validate a low-cost, effective method of monitoring sweet potatoes

• Great quality of data enabling discrimination of land uses and estimation of the area for each use

• Identifying ‘spectral signature’ of variet Multispectral camera © CIP

Project leader: Roberto QuirozSee more at: http://cipotato.org/press-room/blogs/cip-drone-study-over-sweetpotato-fields-of-east-africa-a-success/

Photo CIP: Mwanza region of northern Tanzania

To produce recommendations much more quickly on rice varieties in Colombia

1. Access annual surveys and agronomic experiments from commercial fields

2. Getting planting times for specific sites and seasonal forecasts

3. Pairing historical records with state-of-the-art seasonal forecasts

4. Analyses with advanced algorithms from biology, robotics and neurosciences

5. Search for weather patterns in previous years and checked which varieties did best in those years

Analyzing large, uncontrolled, real-world data for rice

Most productive rice varieties and planting times for specific sites and seasonal forecasts Identified.

Recommendations could potentially boost yields by 1 to 3 tons per hectare.

Scaling up the techniques from their pilot to Argentina, Nicaragua, Peru and Uruguay

Analyzing large, uncontrolled, real-world data for rice

The project won UN Global Pulse’s Big Data Climate Challenge

CIAT

Crowdsourcing Farmers’ Preferences for varieties

Seeds for Needs projects 500 farmers per site will be given 3 blind varieties in small quantities to be tested under their own conditions and feedback returned by phone

What Big Data can do for Livestock Farmers ?

1 billion small-scale livestock keepers Smalls-cale ‘mixed’ crop-and-livestock farmers Livestock-based strategies for adapting to, and

mitigate, climate change - Livestock feeding systems that both increase

productivity and reduce greenhouse gases.

From Kunming to Da Li, Yunnan Province, China (photo credit: ILRI/Stevie Mann).

Remote sensing/GIS for Monitoring welfare of livestock Grazing locations, distribution Epidemiology/diseases distribution

Another Webinar !

Future of Big Data in CGIARCGIAR 2017-2022 Programmes and Platforms

Agri-food System Programmes Big Data platforms will support 8 Agri-Food

System Programmes (AFSP)

1. Dryland Cereals and Legumes2. Fish Forest and Agroforestry Landscapes3. Livestock 4. Maize5. Rice6. Roots, Tubers and Bananas 7. Wheat

Global Integrative Programmes

1. Genebanks2. Agriculture for Nutrition and Health

program (A4NH)3. Water Land and Ecosystems (WLE)4. Climate Change, Agriculture and Food

Security program (CCAFS)5. Policies, Institutions and Markets (PIM)

CGIAR data & service platforms 1. Genebanks2. Genetic Gain

Establishing CGIAR system genetic resources capability

3. A platform on Big-Data, Information and Knowledge

genetics & genomics, Agrobiodiversity data spatial, biophysical, social and economics Open Data-Open Access

IFPRI/CIAT led Proposal for CGIAR Big Data Platform

‘Tools for Driving Interdisciplinary and Collaborative Big Data Analytics ‘ - some elements CGIAR Survey Platform Data

for data collected through mobile devices from connected sensor network across trial sites

Provide ontologies/standards/tools for Data Discovery & Analytics across data repositories

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

Capacity development activities

More on the CGIAR Web Site First Expression of Interest and

Comments http

://www.cgiar.org/our-strategy/second-call-for-cgiar-research-programs/crp-2nd-call-pre-proposal-submissions/

Second call for full proposal http://

library.cgiar.org/bitstream/handle/10947/4127/CGIAR-2ndCall-GuidanceFullProposals_19Dec2015.pdf?sequence=1

Thank youMedha Devare

Data and Knowledge Manager Open Data-Open Access Strategy Coordinator

CGIAR Consortium Office

Jawoo KooHarvestChoice project Co-PI

IFPRI

Andy JarvisDirector, Decision &Policy Analysis Area, CIAT

Flagship leader, CCAFS

Mali, E. Arnaud, Bioversity

Jacob van EttenTheme Leader, Adaptation to Climate Change Bioversity International