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Webinar@ASIRA: A Practitioners Approach to Open Data for Agricultural Research


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By Sander Janssen, Research Team Leader of Earth Observation and Environmental Informatics at Alterra, Wageningen UR,

12 April 2017- 14:00 CET

--The webinar was held as part of ASIRA (Access to Scientific Information Resources in Agriculture) Online Course for Low-Income Countries--

This presentation focus on the political context of open data publishing, methodological frameworks for estimating the impacts of open data and highlight the Open Data Journal for Agricultural Research as publication channel for open data sets. It will also build on personal reflections on publishing open data from Dr. Janssen’s own research career.

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Webinar@ASIRA: A Practitioners Approach to Open Data for Agricultural Research

  1. 1. A practitioners approach to open data for agricultural research 12 April 2017, Sander Janssen, team leader Earth Informatics
  2. 2. Outline § Political aspects of Open Data § Methodological framework perspective on Open Data § Personal experiences with Open Data § Publishing perspective on Open Data § Concluding remarks 2
  3. 3. Political perspective on Open Data 3 Courtesy of the
  4. 4. Political perspectives on Open Data (2) 4 (L-R) Labour MPs Elliot Morley, Jim Devine , David Chaytor, courtesy of
  5. 5. Relevance to governments § Government transparency and accountability ● Transparency with donor spending on development ● Data portals:, § Improved innovation and business development ● Stimulating the service sector ● Assisting start-ups: open data as a resource § Improved strategic assessment of decision making ● More data will lead to better decision making ● Different parties can be involved 5
  6. 6. Stakeholders benefit from improved and more effective use of open data for agriculture and nutrition by engaging with it in a practical and knowledgeable manner
  7. 7. Activities § Improved interoperability of data through providing improved standards and innovative services. § by providing examples of improved tools for impact assessment, as well as by analysing barriers that hinder the full potential of open data initiatives and investments § The development of tailored training courses will increase the capacity of stakeholders on how to use and handle open data
  8. 8. European Open Science Cloud 8
  9. 9. Methodological framework perspective on open data 9
  10. 10. Challenges for Data for Agriculture: 12/04/2017 Ministry of Economic Affairs / Wageningen 10 Innovation 1 2 3 4 Warning Stay away from challenge 4 until you have developed a proven capability for generating successes in 1-3 Further develop the innovation potential of Open Data (technological-, process-, and social innovations) and use this for developing (Ansoff matrix): 1. Improved data based products for existing markets (relatively easy) 2. Application of existing products in new markets 3. New products for existing markets 4. New products for new markets (very high risk of failure)
  11. 11. The Agri-Chain – fields of interest for data 12/04/2017 Ministry of Economic Affairs / Wageningen UR 11 Preparation Production Storage Processing Retail Consume Transportation Inputs Energy Water Packing Biomass GHG landscape Land usesmell
  12. 12. Data analysis and integration, Models, Artificial Intelligence, Linked Open Data, Semantic web technologies, ... Policy options, Products, Services, Costs, Benefits, Scenarios, Impact Assessments, Decision Support Systems, Integrated models, ..... Decision domain (policy/industry) Process of data based value creation and roles involved Policy makers/industry/societal stakeholders Wisdom Knowledge info + application Information data + added meaning (Big) Data raw material Knowledge domain (science / consultants) Interests (economic, social, environmental), values, preferences, trade-offs, risks, intangibles, ethics, .... Databases, Satellites, Sensor networks, Social media, Citizen Observatories, ... Open(data)Standards,(meta)datarepositories, Businessdevelopment,Visualizationtoolsand methods,Contextualization,KnowledgeBrokerage,...
  13. 13. Road mapping is thinking backward along the chain (example: precision agriculture) 1) Start with the desired impacts (what do we want to accomplish?); 2) which outcomes are required?; 3) which outputs are needed?; 4) which activities should we undertake?; 5) Which inputs are needed 13 Input Activity Output Outcome Impact Open Data on: • Topography • Farms/parcellation • Land use • Crop rotation • Crop yield • Soils and fertility • Meteorological conditions • Etc. Standards Open remote sensing images Technical infrastructures and processing • Mapping, sensing, guidance, tracking • Stock taking • Data collection and linkage • (sensor) technology development, • Research • Dissemination • Education and training • Organising synergy within and between sectors of activity (including research and consultancy) • Increased crop yield • Decreased labour costs • Decreased inputs of fertilizer • Improved farmers’ skills • Improved public / private collaboration • Strengthening of professional skills knowledge workers in data/information sector • New / improved data and technologies • Scientific publications More efficient agricultural production Contribution to food security and sustainable development at national and global levels Less environmental pollution Increased innovation potential and international reputation of Dutch agricultural sector Increased innovation potential and international reputation of Dutch data related knowledge sector
  14. 14. Personal experiences with open data 14
  15. 15. A paper: Janssen, S., Andersen, E., Athanasiadis, I.N., Van Ittersum, M.K., 2009. A database for integrated assessment of European agricultural systems. Environmental Science & Policy 12, 573-587. 10.1016/j.envsci.2009.01.007 TC: 41; RF: Environment/Ecology; RI: 2.01; 15
  16. 16. At the time of publishing: § Very few examples for references ● Some in health research § Little idea of how to describe it, setting it up 16
  17. 17. Now, 6 years later... § Data has been used in: ● Soil carbon management across Europe ● Disease incidence and economic effects on farms ● Climate change adaptation, at EU scale, and at local scale ● Land use change modelling ● Now request on: farming systems in the Mediterranean region 17
  18. 18. Publishing perspective on open data 18
  19. 19. The hockey stick curve debate: 19 Michael E. Mann, Raymond S. Bradley , Malcom K. Hughes , Geophysical Research Letters, Vol. 26, No. 6, p.759
  20. 20. Background § More and more ‘demands’ from society for openness and transparency à tax payer money spend on research § Issue of reproducibility in research à Stapel affair in the Netherlands § Trendy topics as big data, data science, data revolution à more emphasis on the value of data as a common pool resource
  21. 21. 2015-02-25 21 Open Data Journal for Agricultural Research • Strong networking support • Strong institutional support: INRA, CGIAR and Wageningen UR • Three submissions, one accepted • More submissions coming up! •
  22. 22. What is a data journal? § Same as a ‘regular’ journal, where you publish your articles § Data is submitted with 4 page explanation of what it is. § Reviewed and ultimately published with citation and doi. § Data articles can be cited, once published, adding to your publication record (and scientific indexes) § Data is fully open access, with copyright on the author
  23. 23. Pro’s and con’s for researchers? § Benefit: Standard way of making data sets available § Benefit: Obtain a citation to their own data set, that could raise the scientific profile, including a digital object identifier § Benefit: Licensing issues and sharing conditions including liability solved at generic level, without requiring individual investigation § Drawback: need to provide a basic set of meta-data to describe the data set, for others to reliably use it. § Drawback: potentially, published data sets will be used without being appropriately cited in the derived research
  24. 24. Pro’s & Con’s for Research funders § Benefit: Research can easily fulfil requirements for Open Access, leading to a better availability of research data to the general public § Benefit: Re-use of data sets in projects other than in which it was produced lead to a higher impact of research projects § Drawback: funding will be used to make data sets available, leading to slightly less funding for carrying out research.
  25. 25. Pro’s & Con’s for IT and analytics developers § Benefit: data sets become available with meta-data § Benefit: data sets can be harvested with meta data and license to visualize and upload in other applications
  26. 26. Submission & Review § Submission (see Author Guidelines!) ● Data itself, preferably in non-propietary format ● 4 page description of the data ● Meta-data during the upload process § Review: ● Fit-for-use evaluation ● Not value by value ● Easy of understanding
  27. 27. Concluding remarks 27
  28. 28. A vision for the future 28
  29. 29. Concluding remarks / recommendations § Publish your data! § It is not about platforms, it is not about being perfect! § It is about a cultural change 29
  30. 30. Thank you! @Wurcgi 30