Jan dirk Bulens explaining the challenges in data and ICT for research in working in country like Ethiopia and agriculture

1. Case study: Common Sense
a country in transition
E-Rosa 2nd workshop 27/28 November 2017, Wageningen
Jandirk bulens
e-infrastructure Roadmap for Open Science in Agriculture Funded under #H2020 Grant agreement no. 730988

3. In transition

4. CommonSense as a case study
• Ethiopia as an example in Africa where e-Infrastructure is still in its
infancy
• Research to transfer knowledge and experiences form Europe in a
developing infrastructure targeting open science in agriculture
• an outline is given and barriers are identified to indicate its specific
nature within this context
• It shows research is not only facing ‘research’ challenges, but also
societal, cultural and political aspects.
The project is still in progress.

5. Common Sense
• Dutch Program: Geodata for Agriculture and Water (G4AW)
• CommonSense is developing a platform of specialized information services
including a.o. dashboard and applications for crop monitoring, yield
forecasting for smallholder farmers and loan portfolio monitoring and risk
assessment for Micro Finance Institutions (MFIs)

6. CommonSense objectives
• CommonSense aims to improve the ability of 200,000 smallholder
farmers to sustain their livelihoods and food production
• By providing the associated value chain actors with timely and
relevant information services about agricultural production from
satellites and other data sources
• The services will be sustained by a business model, by our local
partner Apposit
• The project operates in the regions of Oromia, Amhara, SNNPR and
Tigray and will end in December 2018
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7. CommonSense user groups
• Micro Finance Institution (MFIs): information mitigating the risks of lending
and insuring farmers.
• Farmers: provision of actionable information to small holder farmers,
farmers groups /out-growers with to help them make more informed
decisions (e.g. on use of inputs, cultivation practices, market info).
• Unions and Cooperatives: e.g. support in aggregating and managing
agricultural inputs and outputs of member farmers.
• Agro-industry: e.g. support in managing farmer’s production for processing
• Government (MoA): support data collection and sharing for extension
workers (DA) and Woreda Agricultural Offices. Providing a broad view on
the performance of its agricultural sector at Woreda level.
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8. CommonSense Platform
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Customized Applications
Services
Crop suitability
Seasonal monitoring
Yield prediction
Localized weather forecasts
Farming risk analysis
Local data collection and sharing (e.g. prices), etc.
Farming input/output tracking

9. CHIRPS for Northern Amhara region
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120 mm in 5 days
Low rainfall 2015
CHIRPS: Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) is a 30+ year quasi-global rainfall dataset.

10. Common Sense Use Case
• Target group:
• small holders
• Impact:
• improved living conditions
• Proxy:
• Rate of return loans by Micro
Finance Institutes
• Sharing data is crucial (whatever
infrastructure is used)
Small holder
MFI
Agriscore
card
Loan
Rate of
return

11. Use case
Research focus
Processes and components
market
weather
crop
Farm
management
Small
holder
Impact
KPI
MFI
Agriscore
card
Loan
Rate of
return

12. Sesame pilot
• Collaboration: Sesame Business Network/AgriTerra/EIAR
• Services to: farmer’s unions, cooperatives.
• Localized weather forecasts
• Seasonal Monitoring
• Crop Yield Prediction
• Data collection and sharing within value chain
• Results: improved farm management by farmers and
planning/management of inputs and outputs by Unions, risk mitigation for
the farmer.
• Impact: more and more stable income.
• Upscaling potential: 100.000 sesame farmers via 5 unions and cooperatives
in Tigray and Amhara

13. Sesame case value chain

14. SWOT
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PositiveNegative
Internal External
Strengths:
 existing business networks like Sesame
 good telecom coverage
(but weak power supply continuity)
 To built up newly
Weaknesses:
- many changes of people in positions
- monopoly by Governmental organisations
- much time needed
- many language
- Illiteracy
- Poor data infrastructure
Opportunities:
 ambitious people
 donor acceptance (role of research)
 capacity building (role of research)
 business involvement
 Local business partners (to sustain)
Threats:
- Cultural differences
- Political instability
- information security barriers (INSA)
- satellite data for smallholder plots?