In the third part of the workshop series Smart Policies for Data, we will focus on two central building blocks – interoperability and balanced data sharing. The presentations of the event: - Szymon Lewandowski, DG CONNECT, European Commission - Marko Turpeinen, CEO, 1001 Lakes - Lars Nagel, CEO, International Data Spaces Association

1. Smart Policies for
Data workshop
series
18 March 2021
Building blocks for
fair digital society

2. Elements for successful
European Data Markets
Szymon Lewandowski, European Commission
DG CONNECT, Data Policy and Innovation, 18.03.2021

3. Data Market vs Data Economy
• The Data Market is the marketplace where digital data is
exchanged as “products” or “services” as a result of the
elaboration of raw data. Its value is based on the
aggregate value of the demand of digital data without
measuring the direct, indirect and induced impacts of
data in the economy.
• The Data Economy measures the overall impacts of the
Data Market on the economy.
2
https://datalandscape.eu/

4.  The Supply and Demand
dimension -
measurement of data
supplier and data user
companies and the
revenues generated.
 The Business and
Economy dimension -
the size of the Data
Market and the value of
the Data Economy.
 The Workforce and Skills
dimension - data
professionals and their
potential skill gap.
EU Data Market – main indicators

5. European Strategy for Data
A common European data space, a single market for data
Data can flow within
the EU and across
sectors –
FFD Regulation
European rules and values
are fully respected
GDPR
Rules for access and use of data
are fair, practical and clear & clear
data governance mechanisms are
in place
Availability of high quality
data to create and innovate
Benefitting from the second wave of industrial data
4

6. European Strategy for Data - legislation
Public sector data of high value
Unleash the socio-economic potential
of data as a PUBLIC GOOD
Public sector data, private sector data and
personal data voluntarily made available by data
holders
Personal data and private sector data held by online
platforms and originating from the users (both
businesses and individuals)
Regulate MARKET POWER
based on data
Private sector data, personal data
and co-generated (IoT) data
Ensure FAIRNESS in the
allocation of data value among the
actors of the data economy
Ensure TRUST in data
transactions
Dec 2020
Q3 2021
Impl. Act.
High Value
Datasets
Data
Governance
Act
Digital
Market
Act
Data Act
Q1 2021
Nov 2020
4 key instruments
5

7. High impact
deployments
Digital
Innovation
Hubs
BUILDING
ESSENTIAL
DIGITAL
CAPACITIES High Performance Computing
Artificial Intelligence
Cybersecurity
Advanced Digital Skills
DIGITAL EUROPE PROGRAMME - ACCELERATING THE BEST USE OF DIGITAL TECHNOLOGIES
European Strategy for Data – funding support

8. Artificial intelligence, data and cloud
Data spaces
Green Deal
Manufacturing
Health
Agriculture
Mobility
Security (law
enforcement)
Cultural Heritage
Media
Horizontal
actions
in support to
data spaces
support centre
open data portal
high value data
sets
Cloud federation
Market place
Cloud to Edge
based services
Middleware
platforms, building
blocks, cross
cutting software…
AI on demand
platform
Central access
point to AI
resources
Testing &
Experimentation
Facilities
Manufacturing
Health
Agriculture
Smart
Communities
Edge AI HW
Actions will be managed directly by CNECT
Approx. 56% of the SO2 budget Approx. 36% of the budget

9. Enabling different types of data markets
• Direct trading (via API of data holder) or with the involvement of intermediary
• Individual "micro data" (data marketplace) or information products (data broker)
• Involving individual ("personal data market"/ PIMS) or industrial/IoT data
• Data stay in a an "industrial data space" or in an open environment
• The concept of Common EU Data Spaces in DEP as sectoral data markets
• Rules for ‘European style’ intermediaries in the Data Governance Act
• Access to the data generated in the use of the gatekeeper platform – Digital Markets Act
• Supply of data - HVDs (open data), and via sectoral legislation (electricity, mobility)

10. What are the remaining issues in data
markets?
Legal:
• Uncertainty on the right to use
the data
• Lack of control over the data
• Lack of standard licencing
solutions
Technical:
• Lack of standards
• Insufficient quality of the data
• Lack of interoperability between
sectors
• Data difficult to find
Structural:
• Imbalance in negotiating power
• Small players not having critical
mass of data and not sharing it
9

11. Thank you very much for your
attention
• https://ec.europa.eu/digital-single-
market/en/news/building-data-economy-
brochure
• CNECT-G1@ec.europa.eu

12. Design principles for data spaces
18.3.2021
Marko Turpeinen
CEO, 1001 Lakes

13. Organization-centric view on data
Organization
Proprietary
data
Open data
Confidential data
Distributed
data

14. Network-centric view on data
Trusted Data
Space
Member
Member
Member
Untrusted
Intermediaries

15. Human-centric view on data

16. Source: WalDigiFarm
Farmer’s view on data (example)

17. Design principle #1 for data spaces
Data sovereignty
The capability of a natural person or organisation
for exclusive self-determination with regard to its
economic data goods. This is the innovative and
transformative concept underlying data spaces.
Source:
”Design principles
for data spaces”.
Position paper to
be published by

18. Design principle #2 for data spaces
Data level playing field
New entrants face no insurmountable barriers to
entry because of monopolistic situations. When a data
level playing exists, players compete on quality of
service, and not on the amount of data they control. A
data level playing field is a pivotal condition to create
a fair data sharing economy.
Source:
”Design principles
for data spaces”.
Position paper to
be published by

19. Design principle #3 for data spaces
Decentralised soft infrastructure
The data sharing infrastructure is not a monolithic
centralised IT infrastructure. It is a collection of
interoperable implementations of data spaces which
comply to a unified set of agreements in all dimensions:
functional, technical, operational, legal and economic.
Out of the principle of data sovereignty follows
functional and non-functional requirements of
interoperability, portability, findability, security, privacy
and trustworthiness.
Source:
”Design principles
for data spaces”.
Position paper to
be published by

20. Design principle #4 for data spaces
Public-private governance
For the design, creation and maintenance of the
data level playing field a sound governance is
essential. All stakeholders need to feel represented
and engaged. These include users (persons,
organisations) or provider of data services as well as
their technology partners and professionals.
Source:
”Design principles
for data spaces”.
Position paper to
be published by

21. Source: ”Design
principles for data
spaces”. Position paper
to be published by

22. Trust Building Blocks
Decentralised Identity System
(for organizations, people, things)
1. Allow the usage of the data
2. Inhibit the usage of the data
3. Restrict the data usage for a group of users or systems
4. Restrict the data usage for specific purposes
5. Restrict the data usage when a specific event has occurred
6. Use or do not use the data in a specific time interval
7. Use the data not more than N times
8. Use data and delete it after
9. Modify data (in transit)
10. Modify data (in rest)
11. Log the data usage information
12. Notify a party or a specific group of users when the data is used
13. Share the data under specific circumstances
Data Usage Policies
(specification and enforcement)

23. 12

24. Fair Data Economy Rulebook
13

25. Source:
”Design principles
for data spaces”.
Position paper to
be published by

26. Embryonic AGRI data spaces (examples)
AgriFood Data Space Finland
Agdatahub

27. Fair data economy rules needed for data spaces
• Combination of business, legal, technical and societal viewpoints is required in
defining fair data rules.
Common design principles for data spaces can be applied
• Apply common building blocks, while leaving room for domain specific solutions.
Common soft infrastructure makes cross-sectorial data sharing easier.
Embryonic data spaces are seeds for common European data
spaces
• National and regional initiatives are important intermediary milestones when
moving towards the vision of common European data spaces, as long as they
adhere to the data space principles and infrastructure reference models, such
as IDS and GAIA-X.
Key messages

28. Thank You!
Marko Turpeinen
marko.turpeinen@1001lakes.com

29. Implementing the European Data Strategy
Building blocks for fair digital society
Online Event
March 18, 2021 at 10:00 pm - 12:30 pm
Lars Nagel
CEO International Data Spaces Association

30. EUROPEAN STRATEGY FOR DATA
www.internationaldataspaces.org
Manufacturing
Health
Agriculture
Green
Finance
Public
Administration
Mobility
Energy
Skills
9Data spaces in key sectors
European Data Space
• Availabilty of large
pools of data
• Infrastructure to use
and exchange data
• Appropriate
governance
mechanisms
How to
realize?

31. It is about vital ecosystems…

32. … and their resilient structures to
establish trust.

33. DATA SPACES
A CONCEPT FOR CONNECTING
ALL KINDS OF DATA ENDPOINTS
When broadening the perspective from an individual
use case scenario to a platform landscape view, the
INTERNATIONAL DATA SPACES positions itself as an
architecture to link different cloud platforms through
secure exchange and trusted sharing of data, short:
through data sovereignty.
By proposing a specific software component, the INTERNATIONAL DATA SPACES Connector, industrial data clouds can be
connected, as well as individual enterprise clouds and on premise applications and individual connected devices.
THIS IS A
DATA SPACE –
JUST ONE SPECIES
OUT OF
THOUSANDS

34. A EUROPEAN STRATEGY FOR DATA
www.internationaldataspaces.org
Manufacturing
Health
Agriculture
Green
Finance
Public
Administration
Mobility
Energy
Skills
9Data spaces in key sectors
European Data Space
• Availabilty of large
pools of data
• Infrastructure to use
and exchange data
• Appropriate
governance
mechanisms
• No silos!
• Enlarge the data pool!
• Cross-sectoral
benefits!

35. Design Principles
For data spaces to be built on
1. Data sovereignty
2. A level playing field for data sharing and exchange
3. A distributed soft infrastructure
4. Public-private governance

36. Decentralised soft infrastructure
The cornerstone for data ecosystems
▪ The infrastructure for European data spaces will not be a
monolithic, centralised IT infrastructure.
▪ Instead, it will be made of the totality of interoperable
implementations of data spaces complying with a set of
agreements in terms of functional, technical, operational
and legal aspects.
▪ Such a ‘soft infrastructure’ will be invisible to data space
participants.
▪ It will entail functional and non-functional requirements
regarding interoperability, portability, findability, security,
privacy, and trustworthiness.

37. Implementing Europe‘s Data Strategy
How to make DGA happen
The Commission has not been explicit yet on
how the general authorisation framework is to
be created and how the totality of data-sharing
applications will have to converge into the de-
facto ‘soft infrastructure’.
The big question now is: How do we get to this
general European authorisation framework
that will determine how data sharing and
exchange in Europe takes place in
practice?

38. Governance for data spaces
Proposal for making DGA happen
Shouldn‘t we have a
Data Exchange Board
to support the DIB?

39. Key steps to achieve data sovereignty
Actions to take in the coming digital decade
1. Digital ‘soft’ infrastructure for data sharing: Develop functional, legal, technical
and operational requirements that support the most pressing use cases of people,
businesses and governments in the various data spaces.
2. Based on existing best practices: Much of the groundwork on digital soft
infrastructure for data sharing has already been done in the past decade by
researchers and business practitioners around the world. The initial version of the
requirements for data sharing services should include these best practices.
3. Living form of standardisation: The digital soft infrastructures are a living form of
standardisation and should be allowed to evolve over time; the common way of
dealing with data must continuously respond to market needs and applications.
4. Operational governance: To include the best practices from the practitioners and
enable the continuous evolution of the standardisation, a sound governance model
should be set up which represents public-sector, private-sector and people’s
interests.
5. Initial implementation: The organisations that have created the requirements
should roll out and implement the first version of the digital soft infrastructure. This
will provide referenceable integrations and, importantly, validate market adoption,
6. Roll-out and adoption: The digital soft infrastructure should then be extended
across all sectors over the coming decade.
Source: BDVA
11

40. Teaming up
…with all their members which are
data spaces natives since years.
The big initiatives in the data realm:
Let’s increase awareness for Data Sovereignty: www.DataSovereigntyNow.org

41. WE NEED COMMON
DESIGN PRINCIPLES FOR DATA SPACES
www.internationaldataspaces.org
IDS Association provides
▪ Open Reference architecture setting the framework conditions – based on standards
▪ Trust framework and scheme for data sharing (rulebook)
▪ Coordinating operations for essential data sovereignty services
This enables
▪ open, distributed data eco systems and marketplaces,
▪ ensuring data sovereignty for the creator of the data,
▪ and proven data-provenance for the user of data,
▪ all above audit-proof, if requested
▪ based on European values.
2
1
3
2
1
3

42. DESIGN PRINCIPLES FOR DATA SPACES
ENSURING DATA SOVEREIGNTY
Unlimited
Interoperability
Enabled by semantic data
descriptions
Trust between different
security domains
Certified, comprehensive security
functions providing a maximum
level of trust
Governance for the
data economy
usage control and enforcement
for data flows
Information Model
Certified, trusted com-
ponents and environments Concept of usage control

43. 4Security profiles
satisfying all needs from quick
data sharing to comprehensive
security requirements
Formal certification states
coherence to reference
architecture, interoperability
and software quality
Defined in DIN Spec 27070 on “security
gateway for sharing data and services”
and reference architecture model 3.0
IDS CONNECTOR
ENABLES ACCESS TO SOVEREIGN,
TRUSTED DATA SHARING ECOSYSTEMS
Implementation in different scenarios (embedded
systems, mobile devices, client server solutions)
Specifications for
implementing a connector
based on container
management technologies
provided on Gitlab
27070 +

44. LET‘S BUILD
DATA SPACES.
// 16
But please: make life easy by
using common design principles.
IDS is a very good starting point – let‘s discuss and learn.
www.internationaldataspaces.org

45. // 17
LARS NAGEL
CEO
INTERNATIONAL DATA SPACES ASSOCIATION
WWW.LINKEDIN.COM/IN/LARS-NAGEL-704411B8/
JOSEPH-VON-FRAUNHOFER-STR. 2-4
44227 DORTMUND | GERMANY
+49 231 9743 619
INFO@INTERNATIONALDATASPACES.ORG
@ids_association
#internationaldataspaces
www.internationaldataspaces.org
International Data Spaces Association
JOIN US!
@LARSMNAGEL
@