Bent Egberg Mikkelsen and Karin Zimmermann's presentation at the eROSA Workshop “Towards Open Science in Agriculture & Food”, a side event to High Level conference on FOOD 2030, Plovdiv, Bulgaria (13/6/2018)

1. Presenter: Bent Egberg Mikkelsen & Karin Zimmerman
Date: 13|06|18
Occasion: Plovdiv June 2018
Why the food sector needs
a research infrastructure on Food, Health
Behaviour & Lifestyle –
insights from the RICHFIELDS design study
Bent Egberg Mikkelsen, AAU – CPH
& Karin Zimmerman, WUR
eROSA Open PreFood2030 Summit, Plovdiv June 13, 2018
Consumer

3. Two important drivers
1. From Projects to Permenancy
2. From Research3.0 to Research4.0

4. Why a RI is a good idea 1
Results has an amazing ability to disappear when projects close
”So you want the original data set?”
”Well thing is that was on my Laptop that got
stolen and the backup did not work” 
Disclaimer: Quote is purely fictional. Any resemblance to actual
persons, living or dead, or actual events is purely coincidental

5. Business Generated Data Case Studies. Richfields D8.1 Bent Egberg Mikkelsen, Kwabena Titi Ofei,Haris Hondo, Erik Kaunisto (2017)
Why a RI is a good idea 2
stakeholder views on Big big food data analytic and “food & the digital”
”We have so many data we dont know what to do with them ”
Chief data analyst, Major Danish Retailer
”Something is rotten in the state of the retail sector. Its changing but
we dont know how. What we do know is that its digitally driven”
Major Danish Market Intelligence Bureau with inspiration from Shakespeare
Stakeholders workshop report (2017). Richfields D 8.3. Kwabena Titi Ofei, Bent Egberg Mikkelsen, Haris Hondo, Erik Kaunisto, Sophie Hieke

6. One thing is for certain
Recent policy papers says the same
The food sector compared to travel tech,
health tech and fintech are lacking behing in
terms of taking advantage of ”the digital”

7. What is a Infrastructure?
Its got 2 dimensions. Hard & Soft
Hard part: labs, devices, machines etc Soft part: multi source data
Lab
generated
Bizz
generated
Consumer
generated
Register
stored
6y
• Lab generated: experimental
behavioral data
• Bizz generated: shopping data
• Consumer generated: Instagram,
Facebook etc
• Register data: Socio demographics,
weather, health etc

8. What is smart food labs
3 cases of Laboratory generated data
Step 1
• Case studies on three facilities (Fake Food Buffet,
FoodScape Lab, Restaurant of the Future)
• Food choice, purchase and consumption
Step 2
• Mapping additional facilities across Europe (private and
public)
• Expert interviews in selected facilities (commercial and public-
private institutions)
Step 3
• Stakeholder workshops to discuss these insights
• Synthesis of findings and recommendations
N=3+2

9. Behavioural food labs
case of foodscape lab

10. Use case: Know now or in 5 years?
Get realtime answers on food intake
• 7 day food record
• High drop out rate
• Primarily ressource full
respondents
• Labor intensive data
cleaning
• Five years before reporting
• Costumer generated
• Card based (loyalty, credit etc)
• Directly interface to TradeSync
• Realtime sourced
• Based on
DonateYourData/sharing
economy
”Your idea of a digital data platform is the future but you needa’
come back in 2 years.”, Deputy director, DK Govennment Food Agency

11. Consumer4.0
always connected
•Uses many channels for communication
•Uses different shopping channels: web,
brick & mortar and mixed
•Has relations with many different
enterprises
•Would potentially like to share data

12. Use case 1: Get realtime answers on food intake

13. Consumers & Data
Why research infrastructures?
Some societal trends pushing us
Digitalisation
 Data platforms, linked open data, standards
 Apps, sensors, wearables
Personalisation
 Individual feed back structures
 Quantified self
Globalisation
 Global markets and global SDGs
 Internet
Integration
 Fragmentation in sectoral policies
and practices to be overcome
Citizen science
 Citizens become engaged
in research

14. Research infrastructure:
enabling response to scientific & societal challenges
Research
Infrastructures
centre of knowledge
triangle
 Unique research services,
facilities and resources and
related services
● ‘single-sited’
● ‘distributed’
● ‘virtual’
 Scientific discoveries &
technological development
 Help to shape scientific
communities
 Attract young people to science
& attract the best researchers
around the world
 Build bridges between national
research communities and
scientific disciplines via users
from different countries
Education
Research
Innovation

15. Research Infrastructures:
overcoming fragmentation
Transition to
Consumer centred
FNH-RI
Inter-disciplinary
Multilevel
Multisector
Fragmented
Disciplinary
Sectoral
Ineffective
Inefficient

16. to be an overarching, virtual, integrated
research environment to collate, validate,
harmonize and connect existing
and future research data & tools as well as
labs & experimental facilities.
Aim of FNH-RI

17. FNH-RI model
added value by scientific integration of fragmented
and locked data via services to stakeholders
supporting the interoperability of standardization
and quality management of data and tools
conditions for access, organizes centralized and distributed activities, and
enables flexibility regarding innovation within the RI
Data platform
ICT backbone
Governance structure

18. • EU, Research Infrastructure projects
• EuroDISH: Determinants – Intake – Status - Health
• RICHFIELDS: Focus on gap Determinants – Intake
• Food Nutrition Health RI roadmap (ESFRI)
• 2015, based on (premature) application, lessons learned
• Next round 2019/20
• EU Member States
• Preparing FNH-RI consortium for ESFRI-roadmap
• Political & fin support ESFRI roadmap applic (Ministries)
• National roadmaps (DK,NL,IT,UK,FR,SL). Coming up new node 2019
Three tracks to the FNH-RI

19. 2024
Fully operational
Food, Nutrition
& Health RI
Food, Nutrition and Health RI
Time line 2015-2025
2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025
RI building: Member State & EU level funding
Preparatory phase Implementation phase
Growth of Member States
and stakeholders involved
RI design & development : Member State & EU (H2020, JPI, etc.)
FNH-RI
Foundation
Design phase

20. The FNHRI in the making
Consortium building proces
Maturity
full-blown research infrastructure
Growth
Expansion of core interactions and
services
Launch
The core interaction
Building
consortium

21.  to ensure sustained advocacy
for food information in Europe
 develop, publish and exploit
food composition information
 promote international
cooperation and harmonisation
of standards to improve data
quality, storage and access.
metrology and
standards for food
labs on food safety,
food quality and food
data
 ethics check
 guidance on
ethical, legal,
and social issues
when exchanging
data
 centres for
nutrition in EU
 toolbox for trials
 standards for
data
 databases & tools
catalogue
 recommendations
for data
storage/transfer/
access
 cloud
provisioning
FNHRI interconnectivity
Services & tools in- & external to FNH-RI

22. FNH-RI Funding scheme
FNH-RI Member States
FNH-RI
National Public Funding National Public Funding National Public Funding
FNH-RI
National Nodes 1
FNH-RI
National Nodes 2
FNH-RI
National Nodes 3
FNH-RI ESFRI funding

23. Take home messages
• Project created data needs ”perpetuumisation”
• A new openness and sharing economy calls for RI’s
• Supported by high level research & RI policy
• The development is fuelled by digitization
• For Food & Nutrition the need is less obvious than for neutron
research
• Support for Food & nutrition RI’s is contamineted by slow digital
growth in the food sector
• BTW: Are your country ready for the FNHRI?

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