sc2 workshop 1: big data in cgiar
TRANSCRIPT
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/