Lecture at the Intro Course "Big data in Agriculture" http://wiki.agroknow.gr/agroknow/index.php/Athens_Green_Hackathon_2013

1. Open Data for Agriculture
Intro to Big Data
29/11/2013
Athens, Greece
Joint offering by
Supported by EU projects

2. Data Products & Problems
in Agriculture
Charalampos Thanopoulos
Agro-Know Technologies

3. Intro
• This presentation aims to provide information about
the open data in agriculture, examples of agricultural
data problems and how these can be described with
the drivetrain approach
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4. Objectives
This presentation aims to provide basic information on
data-related issues in agriculture
• Provide an intro to agricultural sciences
• Describe the use of open data in agriculture
• Define the agricultural data formats
• Provide examples of agricultural data problems
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5. Structure
• The presentation consists of the following
sections:
– Intro to agriculture & agricultural sciences
– Intro to agricultural market & potential
– Intro to Open Data in agriculture
– Review of agricultural data problems
• 4 agricultural case studies
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6. Source: http://www.agricorner.com/shareholder-demands-to-shape-modern-agriculture/
INTRO TO AGRICULTURE &
AGRICULTURAL SCIENCES

7. About agriculture
Definition 1: “the science or practice of farming,
including cultivation of the soil for the growing of
crops and the rearing of animals to provide food,
wool, and other products”
Definition 2: “the set of activities that transform the
environment for the production of animals and
plants for human use. Agriculture concerns
techniques, including the application of agronomic
research”
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8. About agricultural sciences
• Agricultural science: a broad multidisciplinary
field encompassing the parts of exact, natural,
economic and social sciences that are used in
the practice and understanding of agriculture.
– Veterinary science, but not animal science, is
often excluded from the definition
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9. Source: http://www.archives.gov.on.ca/en/explore/online/agriculture/big/big_12_farmers_market.aspx
INTRO TO AGRICULTURAL MARKET
& POTENTIAL

10. a huge market, globally
Food & Agricultural commodities production, http://faostat.fao.org
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11. some figures
• Food - Gross Production Value globally in 2011:
$2,318,966,621
• Agriculture - Gross Production Value globally in
2011: $2,405,001,443
• Investment in agriculture - Gross Capital Stock
globally: $5,356,830,000
… they are big
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12. examples of EU production in 2010
Source: Eurostat
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13. how many businesses?
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14. INTRO TO OPEN DATA IN
AGRICULTURE

15. Definition of Open Data
“Open data is data that can be freely used,
reused and redistributed by anyone subject only, at most, to the requirement
to attribute and sharealike”
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16. why open data?
• Open data, especially open government data, is a
tremendous resource that is as yet largely
untapped
– individuals and organisations collect broad range of
different types of data to perform their tasks
• Government is particularly significant in this
respect
– quantity and centrality of data it collects
– most is public data by law, could be made open and
made available for others to use
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17. closed data
Examples:
…always bad?
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18. open data for businesses
“new businesses and new
business models are beginning
to emerge: Suppliers,
aggregators, developers,
enrichers and enablers”
“key link in the value chain for
open data is the
consumer…direct relevance to
the choices individuals make as
part of their day-to-day lives”
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19. Open Data in agriculture: a political priority
“How Open Data can be
harnessed to help meet the
challenge of sustainably
feeding nine billion people
by 2050”
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20. Agriculture is about to experience a “growth shock” in
order to cover the exponentially increasing food
needs of the global population
• Key facts about agricultural trends
• All demographic and food demand projections suggest
that, by 2050, the planet will face severe food crises due to
our inability to meet agricultural demand – by 2050:
– 9.3 billion global population, 34% higher than today
– 70% of the world’s population will be urban, compared to 49%
today
– food production (net of food used for biofuels) must increase by
70%
• According to these projections, and in order to achieve the
forecasted food levels by 2050, a total investment of USD
83 billion per annum will be required
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21. One of the most promising routes to agriculture
modernisation is the provision of Open Data to all
interested parties
Open data in agriculture
• In an era of Big Data, one of the most promising routes to
bootstrap innovation in agriculture is by the use of Open
Data:
– e.g. provisioning, maintaining, enriching with relevant metadata,
making openly available a vast amount of information
• The use and wide dissemination of these data sets is
strongly advocated by a number of global and national
policy makers such as:
–
–
–
–
The New Alliance for Food Security and Nutrition G-8 initiative
Food & Agriculture Organization of the UN
DEFRA & DFID in UK
USDA & USAID in the US
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22. examples of variety & diversity
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23. data sets
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24. maps
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25. photos
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26. databases
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27. Agricultural data formats
• publications, theses, reports, other grey literature
• educational material and content, courseware
• primary data, such as measurements & observations
– structured, e.g. datasets as tables
– digitized, e.g. images, videos
• secondary data, such as processed elaborations
– e.g. dendrograms, pie charts, models
• provenance information, incl. authors, their
organizations and projects
• experimental protocols & methods
• social data, tags, ratings, etc.
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28. .. examples of Big Data in agriculture
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29. REVIEW OF AGRICULTURAL DATA
PROBLEMS

30. CASE STUDY 1A: PRODUCING HIGHLY
NUTRITIOUS GREEN VEGETABLES

31. Radiki.com
• food scouter collecting edible
plants like of wild Taraxacum
officinale W.
http://en.wikipedia.org/wiki/Ta
raxacumbusiness
• opportunity: gourmet
restaurants are looking for such
highly nutritious & appreciated
greens
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32. data problems
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33. data problems
Dried export in US
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34. Issues identified
1. finding right & relevant only legislation
2. finding right, natural drying techniques for
these plants
3. finding scientific info on proper packaging
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35. 1: finding right &
relevant only legislation
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36. Slide 36 of 63

37. Slide 37 of 63

38. 2: finding right, natural drying
techniques for these plants
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40. Slide 40 of 63

41. 3: finding scientific info
on proper packaging
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43. Slide 43 of 63

44. The Drivetrain approach
• Enrich existing bibliographic information
• Link bibliographic information with related Web resources
• Allow users to access the full-text of a publication and all the information the Web
knows about a specific research area in the agricultural domain
• Users’ requirements
• Linked data infrastructure
• Selection of available data sources
• Existing bibliographic information
• Available additional data sources
• Develop algorithms for linking data from various data sources (i.e.
DBPedia, World Bank etc) using a linked-data approach involving
AGROVOC
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45. CASE STUDY 1B: AGRO-FOOD
COOPERATIVE

46. Stevia Hellas
• Christos Stamatis
– (CEO of the Stevia Coop)
• Crowd funding model
– 250 growers
– first Greek Stevia
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47. Slide 47 of 63

48. Issues identified
1. Strengthen the knowledge about food safety
2. Where to set up the adding value processing
unit
3. Organic portion of the coops cultivation
4. Define product price
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49. Problem 1: Strengthen the knowledge
about food safety
• The coop needs to strengthen the knowledge in
Food Safety and to follow the standards
• Needs to have access to a portal that provides
access to such information
• It could be extended to cover also other food
products and domains
• What kind of open data are needed
– OER from Educational Institutions
– Open courses
– Data from the ministry on which are the food
standards
– Data from FAO e.g. FAO codex
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50. How such service can help
• Benefits for a stakeholder
– personnel that you need to ensure that you will
follow the food safety standards
– find the food safety standards that should be
followed
– define relevant training for your employees
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51. Problem 2: Where to set up the adding
value processing unit
• The cooperative would like to have a product
on the shelf
• Valuable information
– available energy resources
– shipping roots
– availability of land
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52. Problem 3: Organic portion of the coops
cultivation
• A cooperative would like to invest more in
organic cultivation
• Valuable information
– market needs in organic products and stevia
specifically
– prices of the last years for conventional products
– climate conditions
– soil quality maps
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53. Problem 4: Define product price
• Estimate the price for coops’ product
• Valuable information
– sugar prices
– international prices of stevia
– meteo data
– import prices in Greece
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54. CASE STUDY 2A: PRODUCE TRAINING
MATERIAL FOR NATURAL PRODUCTS

55. APIVITA
• creating natural effective and holistic products
since 1979 to promote health & beauty
– Lately involved in the agricultural education and
training
– Producing training material, creating courses etc.
related to the ingredients of APIVITA natural products
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56. APIVITA
finding OER material
for natural products
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57. The Drivetrain approach
Creating additional services for APIVITA web site
• Existing (generic) user requirements
• Existing appropriate functionalities
• Data models available to support the functionalities of the new web site
• APIVITA-owned content
• External Open Educational Resources with related content
• Requirements from the expected users of the APIVITA micro-site
• Feedback (rating/reviews) of available resources from the APIVITA users
Develop algorithms for
• Filtering results from the linked data stes,
• Fine-tuning content based on the feedback received
• Revising user interface/facets based on new requirements
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58. CASE STUDY 2B: ORGANIZE TRAINING
MATERIAL FOR ORGANIC PRODUCTS

59. Association of organic products
• SEAE: Sociedad Española de Agricultura
Ecologica
• A non-profit organization promoting organic
agriculture in Spain
• Organizes training events and
Conferences/Workshops
– Produces training material and collects
publications from Conference submissions
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60. Issues identified
• Issue:
– Material produced not described with metadata
– Only available (partially) in SEAE website
– All information only available in Spanish
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61. Slide 61 of 63

62. The Drivetrain approach
Create a collection of multilingual metadata for describing
resources and publish metadata in other websites
• Multilingual metadata authoring tool (e.g. AgLR)
• Automatic translation tools
• Agricultural educational portals
• Training material produced by SEAE
• Conference submissions, publications & proceedings
• Develop algorithms for the selection of content for the SEAE collection
• Publication of multilingual metadata in other OER web portals
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63. Thank you!
Charalampos Thanopoulos
Agro-Know Technologies
cthanopoulos@agroknow.gr