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Reflections on making EFSA an open science organisation

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Reflections on making EFSA an open science organisation

  1. 1. Reflections on making EFSA an open science organisation Nikos Manouselis, CEO Agro-Know
  2. 2. background
  3. 3. An extraordinary company that captures, organizes and adds value to the rich information available in agricultural and biodiversity sciences, in order to make it universally accessible, useful and meaningful.
  4. 4. Unorganized Content in local and remote sites Widgets Authoring services Data Discovery Services Analytics services Data Platform Ingestion Translation Publication Harvesting BlossomCultivation Organized and structured Content in local and remote DBs Educational Bibliographic Other Enrichment Aggregate data from diverse sources Works with different type of data Prepare data for meaningful services Educational Bibliographic data aggregation & sharing solutions
  5. 5. indicative partners & clients • Food and Agriculture Organization (FAO) • Global Forum on Agricultural Research (GFAR) • International Fund for Agricultural Development (IFAD) • World Bank Group • UK’s Dept for International Development (DFID) • Michigan State University (MSU) • Wageningen University & Research (WUR) • French Institute of Agricultural Research (INRA) • International Centre for Research in Organic Food Systems (ICROFS)
  6. 6. advocates of open • a global movement dedicated to open agricultural knowledge • Global Open Data for Agriculture and Nutrition (GODAN): make agricultural and nutritionally relevant data available, accessible, and usable for unrestricted use worldwide
  7. 7. making different systems work together • Agricultural Interoperability Interest Group (IG), Research Data Alliance (RDA) • Knowledge & Learning Systems WG, Global Food Safety Partnership (GFSP)
  8. 8. large scale data-related projects • agINFRA: a data infrastructure to support agricultural scientific communities (2011 - 2015) – 12 partners (incl. FAO); tech coordinator, evaluation, sustainability – in G8 Open Data in Agriculture Action Plan for Europe • SemaGrow: Data intensive techniques to boost the real-time performance of global agricultural data infrastructures (2012 - 2015) – 8 partners (incl. FAO, WUR); tech, evaluation, sustainability – in G8 Open Data in Agriculture Action Plan for Europe • OpenMinTeD: Open Mining INfrastructure for TExt and Data (2015- 2018) – 15 partners (incl. UoA, EBI, INRA); tech+data, requirements & evaluation • Big Data Europe: Integrating Big Data, Software and Communities for Addressing Europe’s Societal Challenges (2015-2018) – 12 partners (incl. FAO); agri-food community & use cases
  9. 9. (my) understanding of the context • vision: “Society engages in EFSA’s scientific work and gains trust in the EU food safety system” –increase openness & transparency –openness to meaningful contributions
  10. 10. levels of reflection a) on a data e-infrastructure for EFSA operations b) on positioning EFSA within a food safety data ecosystem c) on “data need”-oriented innovation services for EFSA stakeholders
  11. 11. a data e-infrastructure for EFSA operations
  12. 12. example:
  13. 13. open & federated architecture agINFRA automated metadata aggregation workflows Publications CIARD RING registry Federated information providers Data sets CIARD RING registry Educational CIARD RING registry …etc
  14. 14. catalogue of data sources/sets
  15. 15. published & linked vocabularies
  16. 16. complex, automated data ingestion Metadata harvester Filtering component Stores File system (DC, IEEE LOM, MODS XML) File system (DC, IEEE LOM, MODS XML) Stores Identification and de-duplication component MySQL Dupli cates Stores Transformation component ( to AKIF) Store metadata in JSON (Internal Format) Link checking component PostProcessing/ Enrichment component File system (XMLs) Get unique ID Records with Broken Links Indexing mechanism API
  17. 17. big data technologies
  18. 18. data customer service
  19. 19. how could this look like for EFSA? EFSA’s data & information hub Toxicity testing methods Registry Various data providers, of various scientific data sources/formats Pesticide outputs Registry Foodborne disease outbreaks Registry …etc
  20. 20. positioning EFSA within a food safety data ecosystem
  21. 21. example: AGRIS (
  22. 22. the AGRIS ecosystem looks simple…
  23. 23. …but it is a bit more complex
  24. 24. How does the EFSA data ecosystem look like?
  25. 25. need-oriented innovation services for EFSA stakeholders
  26. 26. example: CSPI • the organized voice of the American public on nutrition, food safety, health and other issues – “improve food safety laws and reduce the incidence of foodborne illness” • has tracked foodborne illness outbreaks since 1997 – events where two or more people become ill from eating the same food – outbreaks where both the food and pathogen can be identified
  27. 27. US Outbreak Alert Database (until 2011)
  28. 28. US Outbreak Report (after 2011)
  29. 29. stakeholder with very specific challenges a) time-consuming & laborious primary data identification and documentation (by hand) b) not complete coverage: incomplete & problematic data collection and sharing c) multiple & outdated databases for secondary/processed data storage and curation d) time-consuming & expensive processed data visualization & publication
  30. 30. advanced data organisation & classification
  31. 31. auto extract structured data from text
  32. 32. include & link to food recall data
  33. 33. add more (relevant) data sources
  34. 34. allow users to customize data reports
  35. 35. provide multi-channel access to data
  36. 36. Challenges of EFSA stakeholders? • each decision maker has own data needs –Which information is critical for their work? –What is the main challenge in finding, managing or disseminating this information?
  37. 37. and what’s next?
  38. 38. Separate Independent (variably linked) actions Collective and Cohesive Approach (More Collaboration, Coordination, Communication, Connection) harmonising & linking scientific outputs?
  39. 39. EFSA’s Data & Information Hub Context-specific Data & Information Hubs Source diagram from Open Models concept paper: can openness be addictive?
  40. 40. thank you!