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Spinning a Semantic Web for Agriculture
Medha Devare
Sr. . Research Fell llow, Big ig Data Module Lead
SWAT4LS (An (Antwerp), De Dec 4, 4, 20 2018 18
SLIDE 2 CGIAR – agricultural research for development
Research conducted by 15 non-profit research Centers with 10,000 scientists and support staff in over 70 countries. Close collaborations with national and regional research institutes, civil society
- rgs, academia, development orgs and private sector.
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Multidisciplinary (agronomy, breeding, socioeconomics, bioinformatics, data science) Multi-scale (genetic/genomic to landscape) Multi-stakeholder consultative, participatory processes (planning to implementing) Highly heterogeneous, climate-vulnerable, challenging environments
Ag R4D: Complex networks, systems, infrastructure…
SLIDE 4 Floods, cyclones, tidal surges, salinity Drought , overuse of groundwater, acid soils Temperature / drought stress, arsenic Limited-source surface irrigation Seasonal, flash flooding
Courtesy: A. McDonald, CIMMYT
Markets, credit, insurance…
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Hey Cigi, when should I plant my rice? How should I manage my crop?
Real-time decision support, risk mitigation for farmers Easy natural language as an interface Smart artificial intelligence trained by CGIAR and partners Leveraging multiple open, harmonized and interoperable databases
SLIDE 7 Geotagged, time-stamped pictures of insured sites, sowing to harvest. Timely ag advisories generated from the images + satellite imagery and localized data. Images can be used in claims settlements.
SLIDE 8 Scientifi fic in innovation via Big ig Data approaches
Find out what your soil says about your farm – and more!
- See how to best manage soil fertility
- Predict yield for different management and
weather scenarios
- Get locations for trusted agro dealers near you
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Support best practices in generating and managing FAIR data …to allow aggregation, combining, creation of Big Data pool
Opportunities
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Getting to FAIR…
Demo
GARDIAN (http://gardian.bigdata.cgiar.org)
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- 1. Search and filter semantic data described with ontologies.
What’s next?
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- 2. View groupings of plots across projects matching criteria. See what other
data or variables exist in each.
What’s next?
Common categories (all plots) Basal fertilizer quantity (kg/ha) Top dressing fertilizer N (kg/ha) Total N (kg/ha) Total P (kg/ha) Country Tillage Soil
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- 3. Select data to include in a
merged dataset. Download in tabular format
display.
What’s next?
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? ? ?
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AgroFIMS: Key features
Standardized data collection based on ontologies (e.g. AgrO), methodologies Built-in metadata (mapped to CGIAR repositories) = easy upload to repos Built-in R scripts for statistical analysis with graphs, reports generated Easier data integration = enhanced cross-regional, cross-disciplinary learning Plug-n-play with Big Data platform’s analytical, modeling, visualization tools Ease of use (paper or mobile-based digital data collection)
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SLIDE 34 What might th this lo look lik like?
Dataset
(weather)
Research entity (CIMMYT) plot 2 Planting ET Met Project (SIMLESA) Country
(Ethiopia)
has activity located in
Admin div 2
(Bako)
administered by has participant
Experimental site
(Bako)
Admin div 1
(Oromia)
is part of is part of
plot 1 plot 3 plot 4 Crop (maize) Land preparation Zero tillage Crop (bean)
has participant has process has process
Nutrient mgmt
has process
has participant
Etc.
has activity administered by
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Where do people fi fit t in in and how?
SLIDE 36 https://www.w3.org/2006/Talks/ 0718-aaai-tbl/Overview.html#(2)
Get on th the bus, Gus! Make a new pla lan, Stan – just listen to me…
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- T. Berners-Lee. https://www.w3.org/2006/Talks/0718-aaai-
tbl/Overview.html#(2)
SLIDE 38 What role do research organizations and research data play in harnessing AI and related technologies? Biomed as exemplar? Can disruptive tech address key limitations such as poor soil fertility, inadequate access to labor, markets, credit, and technology in Africa?
(Cilliers, Hughes, and Moyer, 2011; https://issafrica.org/research/monographs/african-futures-2050)
How might AI and ML best leverage SW to mitigate risk in heterogeneous agricultural environments?
SLIDE 39 Thank you!
bigdata.cgiar.org
