Industrial Data Space - Why we need a European Initiative on Data Sovereignty

WHY WE NEED A EUROPEAN INITIATIVE ON DATA SOVEREIGNTY
THORSTEN HUELSMANN, MANAGING DIRECTOR, INDUSTRIAL DATA SPACE ASSOCIATION
INTRODUCING INDUSTRIAL DATA SPACE

// 2
INDUSTRIAL DATA SPACE
POSITIONING IN THE
DIGITAL ECONOMY
1

www.industrialdataspace.org // 3
INTERNET OF THINGS AND SMART SERVICES
Industrial Data Space –
a basis for connecting the
Internet of Things and smart
services

www.industrialdataspace.org // 4Source: otto.de (2015), techglam.com
(2015), soccerreviews.com (2015)
NEW BUSINESS MODELS
Time
Hybridity
1
P hysical
P roduct
(running
shoes )
»C lassic
Services«
(training
monitor)
Digital
Services
(Social
Network
Integration)
2
3
Digitalisation is both an enabler and a driving force
behind innovative business models.
A key ability for innovative business models is to be
able to combine data in one “ecosystem”.
Digital services follow common architecture principles:
• Services are decoupled from physical platforms/products
• The architecture levels are decoupled
• Products become platforms and vice versa
• “Ecosystems“ develop around platforms
• Innovation takes place cooperatively

DATA AS STRATEGIC RESOURCES
SMART SERVICES
Modern data management
interconnects what is
offered with how it is
produced and delivered in
the digitalized world

NETWORK OF TRUSTED DATA
Sovereignty
over data
and services
Trust
Certified
Participants
Decentral
Approach
distributed
architecture Security
of data exchanges
Data Governance
“rules of
the game”
Economies of
scale
Networking
effects
Open
Approach
Neutral and
user-driven
Network
of platforms
and services

BASIC PRINCIPLES
Network of Trusted Data
Digital Sovereignty The data owner specifies the terms and conditions of the data provided (terms and conditions can simply
be “attached” to the respective data)
Secure Data Supply Chain Data exchange is secure along the entire supply chain, i.e. from data creation or data capture to data use
Easy Linkage of Data Linked-data-concepts and common vocabularies facilitate the integration of data between participants in
Industrial Data Space.
Data Economy Data is viewed as an economic asset. It can be divided into three categories: private data, so-called “club
data” (i.e. data belonging to a specific value added chain which is available to selected companies only)
and public data (weather information, traffic, geo data, etc).
Trust All participants, data sources and data services in Industrial Data Space are certified according to jointly
defined rules.
Decentral Data Management Data can be decentral and stay with the data owner, if so wished.
Data Governance Participants jointly decide on data management processes and on rights and duties.

// 8
THE USER ASSOCIATION
2

• Exchanging experience between business
and science
• Developing new business models
• Standardisation and certification
• Implementing application-oriented,
cross-industry projects
• Pooling user requirements and use cases
• Representing interests at an international
level
INDUSTRIAL DATA SPACE ASSOCIATION
TASKS AND MEMBERS

IDS stands for safer data exchange between companies where the
producer of data remains the owner of the data and maintains
sovereignty over the use of that data.
IDS Association aims to define the conditions and governance for a
reference architecture and interfaces aiming at international
standards.
This standard is actively developed and updated on the basis of use
cases. It forms the basis for a number of certified software
solutions and business models, the development of which is
fostered by the association.
SELF-PERCEPTION
„

DR. REINHOLD ACHATZ
Chairman of the Board of IndustrialData Space Association
CTO and Head of Corporate Function Technology, Innovation &
Sustainability at thyssenkrupp AG
MISSION STATEMENT
” Digital transformation and “Industry 4.0”
are key success factors for companies in
Europe.
The association ensures that the specific
interests of the industry contribute to
applied research.
At the same time, companies will have faster
access to the results from the Industrial
Data Space research projects and be able to
implement them faster too.
DIGITAL TRANSFORMATION
”

ORGANISATION
Working Groups
• A rchitecture
• U ser Requirements
• Standardisation
• M arket Exploration
• …
Member Companies
28 companies and
associations
(as July 2016)
Head Office
• M embership M anagement
• Internationalisation
• Knowledge T ransfer
• M arketing and
C ommunication
• O rganisation
Executive Board BMBF-Research
Project
(Fraunhofer)
Advisory Board
Technical Advisory Board
Nine work packages
• IDS A rchitecture
• Software Implementation
• U se C ases
• Standardisation
• C ertification
• Digital Business
Engineering
• Recommendations for
A ction
• Institutionalisation
• P roject M anagement
Use Case Advisory Board
Steering Committee
Use Cases

SYNERGIES BETWEEN THE WORKING GROUPS
Market
Projects of Applied Research
Working
Group
U se C ases &
Requirements
Working
Group
A rchitecture
Working
Group
M arket
Exploration
Use Cases
Specific requirements of member
companies are implemented as pilots
Real time testing of lessons
learned and releases from
the research project
Market requirements are registered, structured and implemented
within the architecture
Applicable elements are
checked with respect to
commercialisation and
possible certification and
standardisation Development of
business models
Agile
architecture
releases
Working Group
Standardisation
Gotomarket
(continuously)
Continuous
refilling of product
backlogs
Development - participating in the
development of standards
IDS
Validation of
the
functions in
the business
map

THE BOARD
Chairman of the Board:
Dr. Reinhold Achatz, thyssenkrupp AG
Deputy Chairman of the Board:
Dr. Ralf Brunken, Volkswagen AG
Prof. Dr. Boris Otto, Fraunhofer IML
Treasurer:
Dr. Ralf-Peter Simon, KOMSA AG
Members of the Board:
Markus Vehlow, PwC AG
Ulrich Ahle, Atos GmbH
Dr. Robert Bauer, SICK AG
Prof. Dr. Stefan Wrobel, Fraunhofer IAIS
Heike Niederau-Buck, Salzgitter AG
At the founding of Industrial Data Space e.V. in Berlin: (from left to right) Markus
Vehlow, PwC; Dr. Ralf-Peter Simon, KOMSA AG; Dr. Robert Bauer, SICK; Heike
Niederau-Buck, Salzgitter; Dr. Ralf Brunken, Volkswagen; Prof. Dr. Boris Otto,
Fraunhofer IML; Prof. Dr. Reimund Neugebauer, Fraunhofer-Gesellschaft; Dr.
Reinhold Achatz, thyssenkrupp; Ulrich Ahle, ATOS. © Photo: Matthias Heyde/Fraunhofer

• Exchange of data and services between industrial companies is
essential element of digital transformation
• Added value is generated in the form of new products and smart
services by networking companies, exchanging data between
companies and integrating publicly available data
• New, digital business models are also possible in conventional
industries
• This guarantees the competitiveness of industrial companies and
their independence from IT companies
• Data security and trust in secure data exchange are essential
prerequisites here
MOTIVATION
WHY DOES INDUSTRY
NEED THE INDUSTRIAL
DATA SPACE?
Foto © Accenture

USE CASES FOR INDUSTRIAL DATA SPACE
VERTICAL COOPERATION
Material Sciences Energy Business Life Sciences
High Performance
Supply Chains
Traffic
Management
Exchange of material
and material
properties over the
entire life cycle from
product creation
through to scrapping
Common use of
status data for the
predictive
maintenance of wind
power stations
Design of a jointly
used data platform
for the development
of medical and
pharmaceutical
products
Exchange of status
and quality data for
transport goods
along the entire
supply chain
Use of traffic
management data for
innovative digital
services inside the
vehicle and for
controlling traffic flow

COLLABORATION WITH „PLATTFORM INDUSTRIE 4.0“
FOCUS ON DATA
Retail4.0 Banking 4.0Insurance
4.0
…
Industrie 4.0
Focus on
manufacturing
industry
Smart Services
Transfer and
networks
Real time
systems
Industrial Data Space
Focus on Data
Data
…
The development and
promotion of the
Industrial Data Space are
being conducted in close
cooperation with
„Plattform Industrie 4.0“
initiative.

// 18
ARCHITECTURE AND
FUNCTION
3

REFERENCE ARCHITECTURE MODEL
BLUEPRINT FOR DIGITAL ECOSYSTEMS
 Software components enable
all stakeholders (defined
roles) to participate in IDS
 The quantity of all (external)
IDS connectors defines
 Internal IDS connectors are
used to link data sources in
the company, to transform
and to improve them.

REFERENCE ARCHITECTURE MODEL
BLUEPRINT FOR DIGITAL ECOSYSTEMS
Business
architecture
Data and
service
architecture
Software
architecture
Security
architecture
Reference
Architecture
Model

ARCHITECTURE FOR DATA AND DATA SERVICES
FOCUS ON BASIC AND ADDED VALUE SERVICES
Automobile
Manufacturers
Electronics
and IT Services Logistics
Mechanical &
Plant Engineering
Pharmaceutical &
Medical Supplies
Smart-Service-Scenarios
Service and product innovations
»Smart Data Services« (alerting, monitoring, data quality etc.)
»Basic Data Services« (information fusion, mapping, aggregation etc.)
Internet of Things ∙ broad band infrastructure ∙ 5G
Real Time Area ∙ sensors, actuators, devices
Architecturelevel

RANGE OF FUNCTIONS
BUSINESS MAP OF BASIS SERVICES
App Store
Basic Data Services
Provisioning
Data Service
Management and Use
Vocabulary Management Software Curation
Data Provenance Reporting
Data Transformation
Data Curation
Data Anonymization
Data Service Publication
Data Service Search
Data Service Request
Data Service Subscription
Vocabulary Creation
Collaborative Vocabulary
Maintenance
Vocabulary/Schema
Matching
Knowledge Database
Management
Software Quality and
Security Testing
Broker
Data Source
Management
Data Source Search Data Exchange
Agreement
Data Exchange
Monitoring
Data Source Publication
Data Source Maintenance
Version Controlling
Key Word Search
Taxonomy Search
Multi-criteria Search
»One Click« Agreement
Data Source Subscription
Transaction Accounting
Data Exchange Clearing
Data Usage Reporting
Connector
Data Exchange Execution Data Preprocessing
Software Injection
Remote Software Execution
Data Request from Certified Endpoint
Usage Information Maintenance (Expiration etc.)
Data Mapping (from Source to Target Schema)
Secure Data Transmission between Trusted
Endpoints
Preprocessing Software
Deployment and
Execution at Trusted
Endpoint
Data Compliance Monitoring (Usage
Restrictions etc.)
Remote Attestation
Endpoint Authentication

• The Industrial Data Space specifies all roles and actors
of the ecosystems
• In addition to data providers and data consumers there
are operators of brokers and App stores
• All actors oblige themselves to play by the rules of IDS
• Actors and technical components are to be certified
ECOSYSTEM INDUSTRIAL DATA SPACE
ROLES AND ACTORS

ECOSYSTEM - INDUSTRIAL DATA SPACE
FOUR BASIC ROLES
Data Owner Data User Broker Certification point
• Provides data
• Operates own
endpoint in Industrial
Data Space or
through a service
provider
• Determines terms of
service and prices for
data
• Uses data to offer
services
or for internal
purposes
• Keeps the terms of
data services
• Brings together
data owner and user
• Operates
»Data register«
• Takes on tasks for
monitoring and
clearing
• Certifies
participants
in accordance with the
standards of
(i.e. security, terms of
service, standards)

USE CASES
INDUSTRIAL DATA SPACE IN ACTION Use Case Company
Broker-based design of supply chains Atos
Inbound and outbound logistics with control of
parameters
Bayer AG
Industrial SiteNavigation Bayer AG
Data Space for Clinical Data Boehringer-Ingelheim
Data Space for HCP/HCO Data Boehringer-Ingelheim
TraQ: Trackingquality with sensors Robert Bosch GmbH
Product Data Exchange Robert Bosch GmbH
Digital networkingof a production line Schaeffler
Coaster SICK
Smart Sensor Intelligence SICK
Timeframe management ThyssenKrupp AG
Upstream Supply Chain Volkswagen
Transparency in Outbound Volkswagen
Downstream Supply Chain Volkswagen
Platformintegration of a production facility Festo
Localisation of containers and alerts Wacker Chemie
• Identify and bundle requirements
• Active design and validation of services and
functionalities of Industrial Data Space by
the users
• Demonstrate innovations based on
• Demonstrate and integrate existing
standardisation plans
• Develop a prototype reference for the
participating companies
• Potential core of an ecosystem by
integrating further partners (also from
different domains)

www.industrialdataspace.org // 26Quelle: Fraunhofer IPA
USE CASES
CHARACTERISTICS OF IDEAL USE CASES
Ideal use cases:
• Link data from several data sources
• Integrate various kinds of data
(for example master data and status data in manufacturing)
• Combine various data goods
(private and public data, »club goods«)
• Involve at least two companies
• Integrate more than two company architecture levels
(for example »shop floor« and »office floor«)
• Basis for offering »smart services«
• Develop core components/basic services

SCOPE FOR 2016
ACTIVITIES
• Establish a Working
Group for user
requirements and a
WG for Architecture
• Develop the
association strategy
• Basic marketing
activities
• Start topic of commercialisation (individual working
group)
• Networking and internationalisation
• Implementation of growth and marketing strategy,
in particular internal and external events
• Accelerate the work on the use cases
• Task forces certification, EU, Asia
Q1 Q2 Q3 Q4
• Found the
association
• Set up the
office/agency
• Positioning

BECOME A MEMBER
MEMBERSHIP FEES
Type of organisation Annual turnover [million.
EUR] (for corporate group)
Annual fee [EUR]
Company from 10,000 35,000
from 2,500 to under 10,000 25,000
from 500 to under 2,500 15,000
from 50 to under 500 7,500
under 50 2,500
Universities, non-commercial
institutions, associations etc.
- 1,000*
* each university, RTO or association should acquire min. three company members

HOW YOU CAN GET INVOLVED
• Piloting, applying and testing
• Implementing requirements
in the development of the
architecture
• Development of Smart Services
Use Cases
ArchitectureProcessing
• Support to help design the
reference architecture
• Contribution of company-
specific know-how
Workings groups
• Participation in working groups
• Regular exchange with all
member companies
• Dealing jointly with problems
concerning data exchange
• Development of business models
in the IDS
• Innovation camp
• Development of common user
models
Exchange of information
• Transferring the content of the
research project
• Common events
Networking events
• Organisation of marketing
activities/fairs
Standardisation/
Certification
• Defining and implementing
standards
• Designing certification
measures
Foto © Christian Rolfes/Ford

WHITEPAPER
Whitepaper
http://s.fhg.de/white-paper-industrial-data-space
This white paper gives an overview on aims and architecture
of the Industrial Data Space. Additionally, some use case and
the Industrial Data Space User Association are introduced.

BECOME A MEMBER
PROCEDURE
• Website
• White paper
• Briefing and information
events
• Articles of the association and
membership fee regulations
INFORMATION APPLICATION
• Fill in a membership
application
• Send the application to
IDSA Head Office:
info@industrialdataspace.org
ADMITTANCE
• IDSA board vote to
admit new
members
• Working groups
• Use cases
• Events
• Business models
• …
MEMBERSHIP
1 2 3 4

HEAD OFFICE
CONTACT POINT FOR ALL MEMBERS!
Ina Brendt
Marketing and
Communication
Sebastian Kleff
Business Development &
Networking
Thorsten Hülsmann
Managing Director, Finance,
Internationalisation
Services and activities:
• Linking research projects and industry
• Coordinating use cases
• Member management
• Coordinating the working groups
• Support for business model development
• Public funding advice and syndication
• Marketing, public relations
• Finances, accounting, book-keeping
• Internationalisation
• Continuing education activities
Lars Nagel
Managing Director, Content,
Knowledge

// 33
CONTACTHEAD OFFICE
JOSEPH-VON-FRAUNHOFER-STR. 2-4
44227 DORTMUND, GERMANY
+49 231 9743 619
INFO@INDUST RIALDATASPACE.ORG
WWW.INDUSTRIALDATASPACE.ORG

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