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2017 11 cascd


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CAS Chengdu November 2017

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2017 11 cascd

  1. 1. Towards an Infrastructure for FAIR data in Agriculture and Nutrition Chengdu, 2017-11-09Johannes Keizer, GODAN Secretariat
  2. 2. • GODAN Secretariat • Before: Team Leader at FAO for open Access and open Science • Background: Research, Pesticide Chemistry Johannes Keizer, PhDTHE PRESENTER
  3. 3. Daunting challenges - impressive opportunities: • The life science revolution is changing our understanding of the fundamental biology of plants, animals and people. It is transforming agriculture. • Information revolution approaches are critically transforming the retail end of food value chains- radical transparency.
  4. 4. “… research suggests that seven sectors alone could generate more than $3 trillion a year in additional value as a result of open data, which is already giving rise to hundreds of entrepreneurial businesses and helping established companies to segment markets …” Source: McKinsey Global Institute "Making these data public will allow people to make their own assessments of the progress of our Good Growth Plan. It is also blurring the traditional roles of business, government and NGOs by highlighting our collective responsibility to address acute global challenges. Above all, the data will be of value to farmers, enabling them to increase productivity sustainably and to enhance their livelihoods." "Open data has the power to solve our most challenging sustainability problems. … Agri- tech businesses have a big role to play in finding novel solutions to these problems. … Syngenta is taking a step that puts them at the forefront of the open data movement in their sector. We look forward to working with them to unlock benefits for farmers and consumers worldwide." Mike Mack, CEO of Syngenta (2015, for 1st GGP data release) Jeni Tennison, Deputy CEO and CTO of the Open Data Institute There is Hype
  5. 5. Digital recombination
  6. 6. Data against death • Discovering patterns of gene expression during aging • Craig Venter and others sift through genomic data on a vast scale • Matching genetic expression with physiologica patterns
  7. 7. EXAMPLE VITICULTURE AGRICULTURAL Technology Courtesy prof. Scienza, Universita’ di Milano
  8. 8. Taste profiles from two different soils
  9. 9. Development of Genetic Research Relation between Phenotypes and Physiology and Genetics through Data Analysis Monitoring in the field the results of breed modifications
  11. 11. Paradigm Shift for research • In the past – 80% data production, 20% data evaluatio • In the future – 20% data production, 80% data evaluation
  12. 12. Communities of Practice Technical Standards Shared Semantic Business Models Research Facilities Connectivity Computing Power Quite a Lot! And to see in Detail Region-Country-City Laws and Regulations/ Taxes/Fees Streets/Railways/Elec tricity/Water Factories/ Transport /Shops/Services Set of Services Technical Backbone Governance Business Model Community Infrastructure
  13. 13. How can we integrate various data? Our proposal is … Tomokazu Yoshida
  14. 14. 24 Conceptual sketch of “CLOP” in 2013APAN44th in Dalian
  15. 15. Structure of API mashup : 4 Layers Term, Code Layer Data Content Layer Data Format (Container) Layer API Layer agroXML, Sensor ML, GML/KML, GPX, … FarmXML(FIX-pms), BIX-pp, GPXX, … Data structure? Data meaning? Data relation? V V V RDF, UML, … SOS, WMTS, WMS, WFS, … MetXML, PDS, … Content list in certain region of interest among certain stakeholders, … Terminology, ontology, … Code system definition, …(Language / Localization)
  16. 16. APAN 44, Dalian August 2017 EXAMPLES FROM EUROPE Iron and Wires Data interoperability http://gacs/ Common s! Shared semantics Data, discovery services DCAN Sustainable and trusted storage CCAN DataVerse Call it FAIR data , Virtual research environments Data/Information Portals Data publication, acess, processing and analysis e BioLink Galaxy
  17. 17. A complementary bottom-up approach: Information from commercial fields - Taking advantage of modern information technologies !!! Climate Soil Crop management Productivity /Quality Site-specific information  Yield and quality limiting factors  favorable/unfavorable Climatic patterns  Optimal site-specific management practices Massively exciting, transformational science “The most magical aspect of big data is Smart Data: the application of statistical analytics and machine learning to data sets to find interesting connections and signals in all the noise.” ”. Philip Brittan. Courtesy Andy Jarvis, CGIAR
  19. 19. THE FAIR PRINCIPLE resources need to be Findable Accessible Interoperable Reusable = FAIR FAIR principle by Barend Mons, EC, EOSC
  20. 20. The 6 levels of “FAIRness”
  21. 21. GODAN addresses Issues through working groups • i.e. data rights and responsibilities • i.e. data infrastructure • i.e. better technical, semantic and legal interoperability • i.e data gaps in nutrition
  22. 22. We want more Chinese Partners
  23. 23. Also in China GODAN is growing But we want more partners, you!
  24. 24. Join GODAN! ● Sign up means you agree to our principles in our Statement of Purpose purpose/ ● Easy to complete forms online godan-partner/ ● Talk to us about how you can get involved in our events, publications and working groups
  25. 25.