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. For more on the topic: http://aims.fao.org/activity/blog/join-free-webinar-publishing-open-data-agricultural-research

1. A practitioners approach to open data
for agricultural research
12 April 2017, Sander Janssen, team leader Earth
Informatics

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. Political perspective on Open Data
3
Courtesy of the Whitehouse.gov

4. Political perspectives on Open Data (2)
4
(L-R) Labour MPs Elliot Morley, Jim Devine , David
Chaytor, courtesy of Telegraph.co.uk

5. Relevance to governments
§ Government transparency and accountability
● Transparency with donor spending on development
● Data portals: Data.gov, data.overheid.nl
§ 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. 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. 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. European
Open Science
Cloud
8

9. Methodological framework perspective on
open data
9

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. 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. 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. 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. Personal experiences with open data
14

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. 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. 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. Publishing perspective on open data
18

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. 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. 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!
• www.odjar.org

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
www.odjar.org

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
www.odjar.org

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.
www.odjar.org

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
www.odjar.org

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
www.odjar.org

27. Concluding remarks
27

28. A vision for the future
28

29. Concluding remarks / recommendations
§ Publish your data!
§ It is not about platforms, it is not about being perfect!
§ It is about a cultural change
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30. Thank you!
Sander.janssen@wur.nl
@Wurcgi
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