A practitioners approach to open datafor agricultural research

12 April 2017, Sander Janssen, team leader Earth Informatics

Outline

§ Political aspects of Open Data§ Methodological framework perspective on Open Data§ Personal experiences with Open Data§ Publishing perspective on Open Data§ Concluding remarks

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Political perspective on Open Data

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Courtesy of the Whitehouse.gov

Political perspectives on Open Data (2)

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(L-R) Labour MPs Elliot Morley, Jim Devine , David Chaytor, courtesy of Telegraph.co.uk

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

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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

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

European Open Science Cloud

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Methodological framework perspective on open data

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Challenges for Data for Agriculture:

12/04/2017MinistryofEconomicAffairs/WageningenUR

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Inno

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WarningStay away from challenge 4 until you have developed a proven capability for generating successes in 1-3

FurtherdeveloptheinnovationpotentialofOpenData(technological-,process-,andsocialinnovations)andusethisfordeveloping(Ansoff matrix):1.Improveddatabasedproductsforexistingmarkets(relativelyeasy)2.Applicationofexistingproductsinnewmarkets3.Newproductsforexistingmarkets4.Newproductsfornewmarkets(veryhighriskoffailure)

The Agri-Chain – fields of interest for data

12/04/2017

MinistryofEconomicAffairs/WageningenUR

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Preparation Production Storage Processing Retail Consume

Transportation

Inputs Energy Water Packing

Biomass GHG landscape Land usesmell

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

Knowledgeinfo +

application

Informationdata + added meaning

(Big) Dataraw material

Knowledge domain (science / consultants)

Interests (economic, social, environmental), values, preferences, trade-offs, risks, intangibles, ethics, ....

Databases, Satellites, Sensor networks, Social media, Citizen Observatories, ... O

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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

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Input Activity Output Outcome ImpactOpen 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 sectorIncreased innovation potential and international reputation of Dutch data related knowledge sector

Personal experiences with open data

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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;

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At the time of publishing:

§ Very few examples for references● Some in health research

§ Little idea of how to describe it, setting it up

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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

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Publishing perspective on open data

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The hockey stick curve debate:

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MichaelE.Mann,RaymondS.Bradley,MalcomK.Hughes,GeophysicalResearchLetters,Vol.26,No.6,p.759

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

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

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

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

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

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

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

Concluding remarks

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A vision for the future

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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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Thank you!

Sander.janssen@wur.nl@Wurcgi

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