Slides of my talk at the University of Guelph (Canada) on September 22nd, 2016. Followed by an agri-food data meetup. (http://bulletin.ovc.uoguelph.ca/post/150653601025/lecture-and-meetup-on-open-agri-food-data)

1. Towards a Global Data
Ecosystem for Agriculture
and Food

2.  A story
 Who we are
 Open data in agri-food
 Cases from our work
 A common data ecosystem?

3. 6
A story
1

7. Κρήτη (Crete)
• Largest & most populous of Greek islands
• Significant part of economy & cultural heritage of
Greece while retaining own local cultural traits
(poetry, music, dialect)
• Once center of Minoan civilization (circa 2700–
1420 BC)
…the earliest recorded civilization in Europe

8. Minoan civilisation
• Named
after King
Minos
• A king of
Crete, son
of Zeus and
Europa

10. Minoans: enemies with Athens
• Every nine years, King Minos
of Crete made King Aegeus of
Athens to pick seven young
boys and seven young girls to
be sent to his palace, the
labyrinth, to be eaten by the
monster Minotaur (half man,
half bull)

12. Theseus prince of Athens

13. princess Ariadne, daughter of Minos

15. so the myth is
about
navigating
through a
labyrinth

16. our story: helping people
navigate through information

17. 6
Who we are
2

19. We find, connect and deliver
agriculture & food information
worldwide
(for the past 8 years)

20. So yes, we consider ourselves pioneers

21. We help organizations build a
better future for all, using
open agriculture and food
data

22. We work with major institutions and initiatives

23. We are a flexible, intuitional team of experts
that delivers
Expert in strategy
design
Designs the most
efficient solutions
Expert in customer needs
identification and analysis
The Strategist
The Architect
The Perfectionist
Nikos Manouselis
Giannis Stoitsis
Babis Thanopoulos
Expert in data and
technology solutions
Kostas Kastrantas
The Doer

24. Blending domain experts, computer engineers and information
scientists

25. We Lead We MakeWe Support
The elements

26. Big Data Indexing
Sentiment Analysis &
Opinion Mining
Big Data Processing
Information
Extraction
Information Retrieval
Summarization
Social Network
Analysis
Large-scale Schema
Matching
Hessian-Free Non-
Linear Optimization
Argumentative
Ontology Alignment
Semantic Annotation
Ontology Evolution
Ontology Population
Deep Kernelized
Multi-task Learning
Convolutional
Networks
Cascade Learning
Machines
Data-intensive R&D linking basic with
applied research in real-life settings

27. open stack of software for big data
analytics & text/data mining

28. 6
Open Data in Agri-Food
2

41. 6
Cases from our work
3

42. AGRIS

43. 8 million
bibliographic records
350.000
visitors per month
Serving >200 data providers
20% of the total FAO visits

44. We aggregate and serve agricultural scientific
information to maximise the impact of AGRIS

45. TAPipedia
A G20 initiative

47. GWPPGlobal Water Pathogen Project

48. Global Scientific Knowledge Hub
for Water Pathogens
UNESCO, Procter & Gamble, Gates
Foundation

49. VitisAll science about Greek
viticulture

50. MachineLearning
Toolbox
High-Throughput
Genotyping
VITIS
Open Linked Portal
DATASETS
2016 2017 2018 2019 2020
Image Recognition / Convolutional Networks
BIBLIOGRAPHIC
Big Data
Indexing
Information
Retrieval
+ PHENOTYPIC + GEOLOCATIONAL + GENETIC + SATELLITE IMAGING
High-Throughput
Phenotyping
Identification
Quantification
Feature Extraction / Image Analysis
Prediction
Sequence Alignment / HMMs
Data
Toolbox
Classification
Information
Extraction
Summarization
Modelling
Toolbox
Large-scale Schema
Matching
Semantic
Annotation
Ontology
Population

52.  Notifications: SMS, email based
on company’s food profile
 Analytics: provide Food Safety
analytics per product, ingredient
and per region
 Supplier check: check if the
current or a new supplier has
been involved in a food incident in
the past
 Regulations: access regulations
and standards for the product and
ingredients per region
 Decision support: take decisions
about new ingredients that a
company would like to use in a
product

53. 6
Towards a common
data ecosystem?
4

55. Doing business with open data
“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”

57. “For a data revolution to happen, agriculture and
food need a fabric of interoperable and interplaying
infrastructure layers that will make data sharing
and exchange as natural to us as it is to use the
road or rail infrastructure to move from one
country to another.”
Agroknow’s response to A global data ecosystem for agriculture &
food, September 2016

58. The right people together
• Open Harvest’16 & Chania Declaration: public and private
sector want to work more closely together on data sharing
• GODAN Data Ecosystem for Agri-food WG to bring senior
data infrastructure people together (co-led by Agroknow &
Syngenta)
• Engage people developing data infrastructure pieces
– CTO meeting is planned
– follow up paper on Technology Principles for Enhanced
Data Interoperability & Discoverability (?)

59. Sharing scientific knowledge
• Agri-food industry investing into Linked R&D Data
platforms
• EU and CGIAR build platforms based on Linked
Open Data and Big Data Analytics for their scientific
data and outputs
• Agroknow, INRA, WUR & FAO to coordinate the
development of a 10y roadmap for a scientific data
infrastructure in agriculture and food

60. How to get involved?
• If you are building data platforms or infrastructures
– join the GODAN WG (talk to me)
• If you are producing, managing or using scientific
data
– follow GODAN for an announcement on roadmap
development events (and talk to me)
• If you are funding such work
– share with us your priorities, interests and planned
interventions to (at least) avoid overlaps and double-
funding (you can also talk to me)

61. 4
Thank you