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Open Data and Open Science in Agriculture: Management

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Dr. Lusike Wasilwa (Kenya Agricultural & Livestock Research Organization) at the Forum on Open Data and Open Science in Agriculture on 15th June 2015

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Open Data and Open Science in Agriculture: Management

  1. 1. Kenya Agricultural & Livestock Research Organization Open Data and Open Science in Agriculture: Management Dr. Lusike Wasilwa
  2. 2. KALRO: 16 Institutes, 47 Centres & 4,000 staff capacity (600 scientists) 1. Food Crops Research Institute 2. Industrial Crops Res. Institute 3. Horticulture Research Institute 4. Tea Research Institute 5. Coffee Research Institute 6. Sugar Research Institute 7. Genetic Resources Res. Institute 8. Biotechnology Research Institute 9. Apiculture Research Institute 10. Dairy Research Institute 11. Beef Research Institute 12. Non-ruminant Research Institute 13. Sheep and Goat Research Institute 14. Veterinary Research Institute 15. Agriculture Mechanization Res. Inst. 16. Arid and Rangelands Research Inst.
  3. 3. Evolution of Research – Enhanced interaction with value chain actors Productivity challenges Market challenges Policy and institutional environmentInput Suppliers Technology Development Production Collection/ Processing Distribution Wholesaling Retailing Natural resources Physical environment
  4. 4. Channels of Communication Communication of Results Journals Books Technical notes Brochures Fact sheets Posters Annual reports Farmer Magazines Policy Briefs
  5. 5. Channels of communication Communication of Results Websites Blogs Twitter, Facebook E-Rails Newspapers Shows and Exhibitions TV and Radio Song and Poems – KALRO Choir
  6. 6. KALRO Website Hosts/Links KAINET Kenya Pollination Network Rice Knowledge Bank KALRO E-Mimi Repository KALRO Institutes Universities EAAFJ Conferences KALRO E- Marketplace???
  7. 7. Methods Used to Collect and Share Data
  8. 8. KARI E-Mimea (Plant) Clinic website launched in June 2013 that provides real-time information pest and disease management
  9. 9. SMS platform (Code 21336) Developed an SMS platform for answering farmers questions on pest and disease management System is currently being upgraded
  10. 10. E-RAILS http://www.erails.net E-RAILS question and answer service supported by FARA. Questions are regularly answered
  11. 11. Plantwise Example Pests and diseases cause considerable loss of crop yield Pests accounts for pre- harvest losses of 42% (15% attributable to insects; 13 % to weeds and 14 to plant pathogens)
  12. 12. Information flow Plant clinic register information flow to and from farmers Flow of other information e.g. market data from clinics Information from plant doctors and farmers and various stakeholders Information flow between stakeholders Input supply Research Farmers Regulation Extension Plant clinics Source: Plantwise, 2012
  13. 13. Paper form completed Scan paper form PDF image Keyboard paper form Excel spread sheet Intelligent Character Recognition software Access Controlled Knowledge Bank Database (with Excel exports) Raw data (standard format) HarmonisationValidation Verification for character accuracy Public Access Knowledge Bank Database Detailed analysis of crops, locations, pests, outreach, gender,... Quality analysis of clinic performance Basic analysis of clinics Country controlled filter Verification for character accuracy Plant Doctors Clerical Staff National Data Coordinators Data Transfer Managers Assistance from Knowledge Bank National Data Coordinators National Data Validators Assistance from Knowledge Bank Transfer Verification Harmon- isation Validat-ionSharing Recording ANALYSISANALYSI S ANALYSIS, PREDICTION AND MODELLING Source: Plantwise, 2012
  14. 14. Paper form completed Scan paper form PDF image Keyboard paper form Excel spread sheet Intelligent Character Recognition software Access Controlled Knowledge Bank Database (with Excel exports) Raw data (standard format) HarmonisationValidation Verification for character accuracy Public Access Knowledge Bank Database Detailed analysis of crops, locations, pests, outreach, gender,... Quality analysis of clinic performance Basic analysis of clinics Country controlled filter Verification for character accuracy Plant Doctors Clerical Staff National Data Coordinators Data Transfer Managers Assistance from Knowledge Bank National Data Coordinators National Data Validators Assistance from Knowledge Bank Recording Transfer
  15. 15. Data Collection, Standardization and Communication Capacity building of plant doctors on use of record and prescription sheets Standardized data collection in all plant clinics Digitization of collected data scanning in clinics Nominated County cluster coordinators Source: Plantwise, 2012
  16. 16. Knowledge Bank (KB) KB clinic support tools Clinics data collection Content/data CABI, KALRO, MoA and KEPHIS KB open access Reports, metrics, impact Improved diagnostic and management tools Improved data mapping, analysis and reporting tools Clinics admin tool Accesscontrol Source: Plantwise, 2012
  17. 17. Incidence of Maize Lethal Necrosis Disease (MLND) in Kenya (May 2013) Bomet, First report of MLND, Sept 2011 Areas MLND reported December 2012 Status of the disease not confirmed (May 2013) ? ? ? ? ? ? Source: KALRO MLND project, 2013
  18. 18. Advantages Increase visibility Increased chances for partnership and collaboration Avail relevant data for wide use Use to develop outputs for local use Form an organization repository
  19. 19. Challenges Cost Manpower for data collection and maintenance Means to prevent data loss Strategies for managing feedback Type and format of data, papers etc. Access of data from individuals Access of data from collaborators, consortia Ensure no plagiarism Increase use of data for generation of knowledge Continuous surveys/reports on data use
  20. 20. Reach all Actors in the Value Chain Input supply Technology generationand dissemination Production Processing Distribution Consumption 201520122009200620032000
  21. 21. THANK YOU

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