Presentation by Sander Muilerman, International Institute of Tropical Agriculture
Session: TechTalk for Agriculture
on 7 Nov 2013
ICT4Ag, Kigali, Rwanda
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
Data out, knowledge in: - dumb and smart phones for research and extension delivery in smallholder farming systems
1. Data out, knowledge in
- dumb and smart phones for research and
extension delivery in smallholder farming systems
TechTalk for Agriculture
Sander Muilerman
International Institute of Tropical Agriculture
2. IITA
An international non-profit R4D
organization (1967) for the
development of agriculture.
Mission to reduce producer and
consumer risks, enhance crop
quality and productivity, and
generate wealth from agriculture.
R4D activities reach ~85% of
national systems in Africa.
Partners include national and
international institutes, NGOs,
academia, and the private sector.
A member of CGIAR consortium
www.iita.org
3. Part of the CGIAR consortium
Global research partnership unites 15 organizations
engaged in research for sustainable development
A member of CGIAR consortium
www.iita.org
4. Agricultural researchers like paper questionnaires
Proven low-tech technology
Accepted and appropriate technology
Clear scientific conventions on good practice
Fail-safe even in the most remote areas
Paper trail
However, several drawbacks:
Complex logistics, no corrections once printed, managing
unexpected outcomes, data latency, minimal economies of scale,
cost and HR for data entry, field management and data quality
management…
A member of CGIAR consortium
www.iita.org
6. Digital data collection tools enhance research process
Skipping, conditionality, branching and live updates/corrections
Use previous answers in new questions (or for calculations)
Innovative mixed methods research (audio, photo, video…)
No catastrophic data loss, no data latency, high reliability
Easier field staff management, even with multiple surveys, and more
quality checks with data range & type enforcement
Mobile phones today are accepted technology in rural areas, works on
any phone/tablet and is completely offline
Instantly make data available also to stakeholders/Apps
Anyone with a phone can collect data, ‘citizen enumerators’
Smart phones have more sensors (GPS, QR, barcodes, …)
Often more cost efficient (less logistics and no data entry)
Real-time and online (distant) management
A member of CGIAR consortium
www.iita.org
7. Examples of mobile data collection systems in IITA
General survey research: Mobenzi Researcher
Control the research process via a Web Console
Very simple to deploy
Powerful set of tools
Used for several
mixed-methods surveys
in the most rural
areas of Ghana
8. Examples of mobile data collection systems in IITA
Sustainable Tree Crops Programme – Côte d’Ivoire
SMS training session reports
SMS seed brokerage system
SMS mass alert message
A member of CGIAR consortium
www.iita.org
9. Examples of mobile data collection systems in IITA
Development of Commercial Farmer Information System
Use of mobile data collection system
Designed for traceability and certification of cocoa
Management info for OLAM (large agrodealer)
Sustainability info for cocoa certifiers and clients
Research data on cocoa farming for IITA researchers
Unique data, large sample
Mutually beneficial
10. Examples of mobile data collection systems in IITA
Complex household surveys:
Computer Assisted Personal Interviewing with
Total control by researcher on a laptop computer
Use of ruggedized tablets for data collection by enumerators
Successfully used for several surveys in Nigeria
A member of CGIAR consortium
www.iita.org
11. Examples: making data/knowledge work for farmers
Community Knowledge Worker – Grameen Foundation
Development of banana and cocoa farming content for ‘last-mile
extension delivery’ in Uganda and Ghana (and beyond).
An additional layer of extension delivery at the community level,
makes basic extension information available 24/7 through smart
phones. Designed to support national extension, it can be
operated by local entrepreneurs as a ‘business-out-of-a-box’.
A member of CGIAR consortium
www.iita.org
12. Examples: making data/
knowledge work for farmers
DEWN (Tanzania) ‘Digital Early
Warning Network’
Farmer groups compiled and sent in
monthly disease reports on cassava
mosaic disease and cassava brown
streak disease using text messages
on basic GSM phones.
DEWN has provided an innovative,
informative, and relatively cheap
means for involving communities in
monitoring the health of their own
crops.
A member of CGIAR consortium
www.iita.org
13. Examples: making data/knowledge work for farmers
Combining data collection and extension delivery:
CKW on banana diseases, with direct expert follow-up
Mobile phones provide information on how to recognize and
control banana diseases (using CKW system)
In exchange data was collected on demographics, awareness,
disease presence and GPS coordinates.
If suspicious diseases reported a visit by research and extension
staff would follow (IITA/NARO)
Highly efficient in terms of cost, HR and impact.
2991 surveys in 2 months
38 Community Knowledge Workers trained
Awareness raised with 3000+ farmers
A member of CGIAR consortium
www.iita.org
14. Examples: making data/knowledge work for farmers
Scientific Animations Without Borders
Creates and deploys educational animations on cell phones for
those who can’t read. On ‘SusdeViki’ site: 300+ educational
materials related to agriculture and life sciences, marketplace
literacy and women’s empowerment. Most of these materials are
animated videos.
15. How can we enhance the collaboration between
Research for Development (R4D) and ICT4Ag?
Combining data collection efforts?
Development of content?
Development of applications?
How to partner?
…
Lessons learned?
Understand the need of the researcher and of the farmer
Plan it well
It is all about the quality of the intervention
& the appropriateness of the technology
Mobile phone extension delivery has to be an add-on to other
farmer training and support.