New technologies such as the Internet of Things and Cloud Computing are expected to leverage the current trend of Smart Farming, introducing more sensors, robots and artificial intelligence, encompassed by the phenomenon of Big Data. This presentation will give a quick insight into the state-of-the-art of Big Data applications in Smart Farming and identify the related challenges that have to be addressed. It shows that the scope of Big Data applications in Smart Farming goes beyond the farm; it is influencing the entire food supply chain. Big data are being used to provide predictive insights in farming operations, drive real-time operational decisions, and redesign business processes for game-changing business models. It is expected that Big Data will cause major shifts in roles and power relations among different players in current food supply chain networks. The landscape of stakeholders exhibits an interesting game between powerful tech companies, venture capitalists and often small startups and new entrants. At the same time there are several public institutions that publish open data, under the condition that the privacy of persons must be guaranteed. The future of Smart Farming may unravel in a continuum of two extreme scenarios: 1) closed, proprietary systems or 2) open, collaborative systems. The development of data and application infrastructures (platforms and standards) and their institutional embedment will play a crucial role in the battle between these scenarios. A major challenge is therefore to cope with governance issues and define suitable business models for data sharing in different supply chain scenarios.

1. Global developments of Big Data in Agri-Food
Sjaak Wolfert (Sr. Scientist, Wageningen Research)
European Big Data Value Forum, 22 Nov. 2017, Versailles, France

2. Wageningen University & Research: Two Partners
Wageningen University & Wageningen Research

3. Wageningen University & Research
 Academic research & education, and applied research
 5,800 employees (5,100 fte)
 >10,000 students (>125 countries)
 > 30 locations in NL, China, Chile, Ethiopia & Saudi Arabia
 Turnover about € 650 million
 Number 1 Agricultural University for the 4th year in a row
(National Taiwan Ranking)
To explore the potential of nature to improve the quality of life

4. BIG
DATA
Advancements in Farming
CONTROL
SENSING
& MONITORING
ANALYSIS
& PLANNING
SMART
SMART
SMART

5. Involving entire supply chain and beyond
Smart Farming
Smart Logistics
Domotics Health
Fitness/Well-being
Tracking & Tracing

6. The battlefield of Big Data in Farming & Food
Farming
Ag
Business
FoodVenture
Capitalists
Data
Start-up
Data
Start-up
Ag Tech
Tech
Companies
Tech
Start-up
Tech
Start-up
Retail
See: Wolfert et al., Agricultural Systems 153 (2017) 69–80
Processors

7. Ag Start-ups in the USA
7

8.  Governance
● privacy, security, stakeholders...
 Business models
● fair share, new opportunities
 Infrastructure
● open versus closed
 Ecosystems
● establishing critical mass
...which are often intertwined!
Current issues and challenges

9. Governance and business issues
9
Code of Conduct

10. Value Chain Integration: FieldScripts
PRESCRIPTIVE FARMING
based on PRECISION
AGRICTULTURE

11. Basic data sales
How does it work?
- A ‘box’ collects all data
- Data is stored in a cloud
- Data is being marketed/invested
- Farmer gets a share of profit
“Farmers think their trust is violated”
Their data goes to multinationals that promise
high future yields based on big data,
while farmers have to pay for everything

12. Creating a collaborative infrastructure
Scenario: get expert advice for spraying to
handle disease on tomatoes
State AuthorityFranz Farmer Ed Expert
Spraying
(follow advice)
Create
Advice
Approval
Request
Advice
CollaborativeBusinessProcess
1
2
3
FIspace App
‘Weather
Information’
FIspace App
‘Spraying
Expert Advice’
FIspace App
‘Spraying
Certification’
Back-EndSystems
Farm
Management
Systems
Sensor Network
in the Greenhouse
Agronomist
Expert System
Regulations &
Approval
System
product type, etc.
sensor data
(access details)
suggested
chemical
advice details
certification
details
12

13. Wrap-up and conclusions
 Agri-Food chains become more
technology/data-driven
 Probably causes major shifts in
roles and power relations among
different players in agri-food chain
networks
 Governance and Business Models
are key issues
 There is a need for a facilitating
open infrastructure
Two extreme scenarios:
1. Strong integrated supply chain
2. Open collaboration network
Reality somewhere in between!

14. IOF2020 ECOSYSTEM & COLLABORATION SPACE
WP1ProjectCoordination&
Management
IoF2020 Generic approach & structure
WP2 Trials/Use cases: Knowledge & App development
Lean multi-actor approach
3. EVALUATION
1. CO-DESIGN
2. IMPLEMENTATION
P1
P2
LARGE
SCALE
P3
WP3 IoT Integration WP4 Business Support
WP5 Ecosystem Development

15. Thank you for your
attention!
More information:
sjaak.wolfert@wur.nl
nl.linkedin.com/in/sjaakwolfert/
Twitter: @sjaakwolfert
http://www.slideshare.net/SjaakWolfert
15