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© Fraunhofer ISST
INTERNATIONAL DATA SPACES
DATA SOVEREIGNTY AND INTEROPERABILITY FOR BUSINESS ECOSYSTEMS
Prof. Dr.-Ing. Boris Otto  8 October 2018  Munich
public· 1
© Fraunhofer ISST
CONTENT
 Data in Business Ecosystems
 Data Sovereignty and Interoperability
 International Data Spaces Approach
public· 2
© Fraunhofer ISST
Business ecosystems are emerging in various sectors
Image source: youtube.com (2018), urban-hub.com (2018); sildeshare.com (2018); SmartFace project (2016).
NB: green – value proposition; blue – ecosystem partners; orange – required data.
Mobility
 Autonomous driving
 Mobility services
 Smart traffic management
Manufacturing
 Smart factory
 Adaptive manufacturing
 Industry 4.0
Healthcare
 Personalized medicine
 Translational medicine
 Smart healthcare devices
Retail
 Supply chain visibility
 Goods and data traceability
 Sustainability
public
 Automobile manufacturers
 Traffic management agencies
 Car sharing providers
 Municipalities
 Data providers
 Original equipment
manufacturers
 Logistics services providers
 Suppliers
 Visibility data providers
 Pharmaceutical research
companies
 University hospitals
 Patients
 Insurance companies
 Retail companies
 Consumer goods
manufacturers
 Consumers
 Logistics service providers
 Location, destination
 Traffic data
 Car control data
 Product, parts data
 Production orders
 Planning data
 Health records
 Treatment plans
 Clinical study data
 Supply chain event data
 Transport data
 Context data (weather, traffic
etc.)
· 3
© Fraunhofer ISST
In a business ecosystem, companies develop their capabilities around a joint
customer value proposition in a coopetition mode
Source: Moore (1993).
Core Business
Suppliers Distribution Channels
Extended Enterprise
Suppliers
of
Suppliers
Customers
Customers
of
Customers
Standards
Organizations
Complementors
Business Ecosystem
Investors
Other
Stakeholders
CompetitorsUnions
Research Organizations
Universities
Trade
Organizations
Core Contributors
public· 4
© Fraunhofer ISST
In business ecosystems, the role of ecosystem partners and the flow of data
are changing fundamentally
Source: Beiersdorf, University of St. Gallen (2012). NB: Viewgraphs show betweenness centrality, i.e. the number of
edges between two nodes that use a certain node. Analysis shows flow of ingredient data for selected products.
2007
Media
2012
public· 5
© Fraunhofer ISST
In the extended enterprise, data must be managed in a consistent way
Legend: Information flow; Material flow.
Public
Data
Value Chain Data
Commercial
Services
Industrial
Services
Lot-Size 1
End-to-End Customer
Process
Business Ecosystem
Hybrid Offerings
Data
Management
Interoperability
Human-Machine-
Collaboration
Autonomous Systems
Internet of Things
Customer
Production
Networks
Logistics
Networks
Digitalized Value PropositionDataDigitalized Value Creation
public· 6
© Fraunhofer ISST
IoT devices represent a rich data source of core business activities for
knowledge generation and business insights
NB:RIOTANA® by Fraunhofer ISST is a flexible, standards-based easy-to-use IoT analytics framework. Legend: IoT –
Internet of Things.
public
ISO/IEC 30141:2016 RIOTANA
IoT Users
Physical Entity
IoT Device
Sensors  Actuators  Tags
IoT Gateway
Local Services  Data
Resource &
Interchange
System
Application
Service
System
Operation &
Mngmt
System
Beacons & Gateway Bosch XDK Smart Sensor
Individual Smart Sensor
RIOTANA Digital Infrastructure and Analytics
· 7
© Fraunhofer ISST
CONTENT
 Data in Business Ecosystems
 Data Sovereignty and Interoperability
 International Data Spaces Approach
public· 8
© Fraunhofer ISST
Data sharing is a key prerequisite for successful business ecosystems
Image sources: Johns Hopkins University (2016), Umweltbundesamt (2016), Smellgard, Schneider & Farkas (2016),
urbanmanagement.nl (2017).
Data Sharing
Energy
Healthcare
Material Sciences
Manufacturing and
Logistics
»Smart Cities«
Sharing of material information along the entire
product life cycle
Shared use of process data for predictive asset
maintenance
Sharing of master and event data along the entire
supply chain
Anonymized, shared data pool for better drug
development
Shared use of data for end-to-end consumer
services
public· 9
© Fraunhofer ISST
Interoperability is key – both on a business ecosystem and in particular on a
data level
Source: BMWi (2016).
Reference Architecture Model Industry 4.0 Administration Shell Concept
The Administration Shell stores all data of a hardware or software component in production scenarios. It makes data and services
related to that component available for Industry 4.0 scenarios in a standardized way.
public· 10
© Fraunhofer ISST
Typically, when shared, data increases in value
Source: Moody & Walsh (1999).
public
Number of users
Share of value
100%
Data
Tangible
Goods
Tangible
Goods
Value
Data
Usage Time
Potential value
Data
Data quality
Value
100%
Data
Integration
Value
Data
Volume
Value
Data
· 11
© Fraunhofer ISST
As a consequence, enterprises are confronted with the need of »squaring the
data circle« …
Source: Otto (2016).
Interoperability
Data Exchange
»Sharing Economy«
Data-centric Services
Data Ownership
Data Privacy and Security
Data Value
Data sovereignty is the capability of a natural person or corporate entity for exclusive self-determination with
regard to its economic data goods
public· 12
© Fraunhofer ISST
CONTENT
 Data in Business Ecosystems
 Data Sovereignty and Interoperability
 International Data Spaces Approach
public· 13
© Fraunhofer ISST
The IDS Reference Architecture Model responds to the most important data
issues in business ecosystems
Source: PwC (2017). The International Data Spaces (IDS) Association publishes the IDS Reference Architecture Model
(IDS-RAM). The Industrial Data Space is a vertical application of the IDS-RAM.
57%
worry about revealing
valuable data and
business secrets.
59%
fear the loss of control
over their data.
55%
feel inconsistent
processes and systems
as a (very) big obstacle.
32%
fear that platforms do
not reach the critical
mass, so that data
exchange will be
interesting.
InteroperabilityData SovereigntyTrust and Security Join us!
Today
IDS Approach
public· 14
© Fraunhofer ISST
The IDS architecture aims at sovereign sharing and smooth exchange of data
in business ecosystems
Legend: IDS Connector; Usage Constraints; Non-IDS Communication.
public
Industrial
Data Cloud
IoT Cloud
Enterprise
Cloud
Data
Marketplace
Company 1 Company 2 Company n + 2Company n + 1Company n
Open Data
Source
IDS
IDS IDS
IDS
IDS IDS
IDS
IDS
IDS
IDS
IDS
IDS
IDS
IDS
IDS
IDS
IDS
· 15
© Fraunhofer ISST
»Production as a
Service« Provider
Use Context
Machine Type
Constraint
Delete CAD data after
first use
OEM
Production
Planning and
Control
Data sovereignty is achieved by attaching usage conditions to shared data –
as the additive manufacturing scenario shows
 Contact information
 CAD data
 Configuration
parameters
 Output
 Use duration
 Temperature
 Certificates
Use Context
Maintenance, no
forwarding
Constraint
Operator anonymous
Maintenance
Service
public· 16
© Fraunhofer ISST
Interoperability is fostered by the use of domain-specific vocabularies and the
IDS Information Model
Administration Shell
Real-World Object
Configuration Parameter
Product Sheet
…
IDS Information Model
Shop Floor Data
Material Master Data
eCl@ss ID
Data Endpoint
Usage Policy
Data Ownership
…
public· 17
© Fraunhofer ISST
The IDS itself forms a business ecosystem for data sharing
Source: Otto et al. (2017); extended representation of the reference architecture model content.
public
Runtime EnvironmentRuntime Environment
authorize
publish app
transfer data
data flow
metadata flow
software flow
identification
useIDSsoftware
useIDSsoftware
useIDSsoftware
identify
Data
Owner
App
Provider
Vocabulary
Provider
Clearing
House
App Store
Provider
Identity
Provider
Data
Consumer
Broker
Service
Provider
Service
Provider
Software
Provider
Data
Provider
Certification mandatory
Membership in the IDSA mandatory
Certification
Authority
· 18
© Fraunhofer ISST
Example Automobile Logistics
The IDS aims at closing a semantic standardization gap
Legend: RFID – Radio-Frequency Identification; IoT – Internet of Things; EDI – Electronic Data Interchange.
Release orders · Dispatch notifications · Invoices …
Parts master data · Change requests · Product information sheets …
Supply chain event data …
Data usage constraints 
Data resource
information
EDI
Electronic
Business
RFID · IoT
IDS
Time
Value-added, sensitivity
of shared data
1990 2000 2010 today
public· 19
© Fraunhofer ISST
The IDS initiative makes various contributions to business ecosystem
interoperability – mainly through semantic standardization
public
Object of Standardization IDS Scope Remark
Data Ecosystem IDS Reference Architecture Model
Tangible objects (e.g. machinery, parts) Using domain-specific standards such as eCl@ss
Virtual objects (e.g. supply chain events, orders) Using domain-specific standards such as GS1 EPCIS
Data objects Contributing to existing standards development
organizations such as the W3C
Usage constraints/conditions Inventory of policies and rules based on ODRL
Communication interface Using von REST, MQTT as well as IDS Communication
Protocol
· 20
© Fraunhofer ISST
Prof. Dr.-Ing. Boris Otto
Fraunhofer ISST · Executive Director
TU Dortmund · Faculty of Mechanical Engineering
Boris.Otto@isst.fraunhofer.de · Boris.Otto@tu-dortmund.de
https://de.linkedin.com/pub/boris-otto/1/1b5/570
https://twitter.com/drborisotto
https://www.xing.com/profile/Boris_Otto
http://www.researchgate.net/profile/Boris_Otto
http://de.slideshare.net/borisotto
Please get in touch!
public· 21
© Fraunhofer ISST
INTERNATIONAL DATA SPACES
DATA SOVEREIGNTY AND INTEROPERABILITY FOR BUSINESS ECOSYSTEMS
Prof. Dr.-Ing. Boris Otto  8 October 2018  Munich
public· 22

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International Data Spaces: Data Sovereignty and Interoperability for Business Ecosystems

  • 1. © Fraunhofer ISST INTERNATIONAL DATA SPACES DATA SOVEREIGNTY AND INTEROPERABILITY FOR BUSINESS ECOSYSTEMS Prof. Dr.-Ing. Boris Otto  8 October 2018  Munich public· 1
  • 2. © Fraunhofer ISST CONTENT  Data in Business Ecosystems  Data Sovereignty and Interoperability  International Data Spaces Approach public· 2
  • 3. © Fraunhofer ISST Business ecosystems are emerging in various sectors Image source: youtube.com (2018), urban-hub.com (2018); sildeshare.com (2018); SmartFace project (2016). NB: green – value proposition; blue – ecosystem partners; orange – required data. Mobility  Autonomous driving  Mobility services  Smart traffic management Manufacturing  Smart factory  Adaptive manufacturing  Industry 4.0 Healthcare  Personalized medicine  Translational medicine  Smart healthcare devices Retail  Supply chain visibility  Goods and data traceability  Sustainability public  Automobile manufacturers  Traffic management agencies  Car sharing providers  Municipalities  Data providers  Original equipment manufacturers  Logistics services providers  Suppliers  Visibility data providers  Pharmaceutical research companies  University hospitals  Patients  Insurance companies  Retail companies  Consumer goods manufacturers  Consumers  Logistics service providers  Location, destination  Traffic data  Car control data  Product, parts data  Production orders  Planning data  Health records  Treatment plans  Clinical study data  Supply chain event data  Transport data  Context data (weather, traffic etc.) · 3
  • 4. © Fraunhofer ISST In a business ecosystem, companies develop their capabilities around a joint customer value proposition in a coopetition mode Source: Moore (1993). Core Business Suppliers Distribution Channels Extended Enterprise Suppliers of Suppliers Customers Customers of Customers Standards Organizations Complementors Business Ecosystem Investors Other Stakeholders CompetitorsUnions Research Organizations Universities Trade Organizations Core Contributors public· 4
  • 5. © Fraunhofer ISST In business ecosystems, the role of ecosystem partners and the flow of data are changing fundamentally Source: Beiersdorf, University of St. Gallen (2012). NB: Viewgraphs show betweenness centrality, i.e. the number of edges between two nodes that use a certain node. Analysis shows flow of ingredient data for selected products. 2007 Media 2012 public· 5
  • 6. © Fraunhofer ISST In the extended enterprise, data must be managed in a consistent way Legend: Information flow; Material flow. Public Data Value Chain Data Commercial Services Industrial Services Lot-Size 1 End-to-End Customer Process Business Ecosystem Hybrid Offerings Data Management Interoperability Human-Machine- Collaboration Autonomous Systems Internet of Things Customer Production Networks Logistics Networks Digitalized Value PropositionDataDigitalized Value Creation public· 6
  • 7. © Fraunhofer ISST IoT devices represent a rich data source of core business activities for knowledge generation and business insights NB:RIOTANA® by Fraunhofer ISST is a flexible, standards-based easy-to-use IoT analytics framework. Legend: IoT – Internet of Things. public ISO/IEC 30141:2016 RIOTANA IoT Users Physical Entity IoT Device Sensors  Actuators  Tags IoT Gateway Local Services  Data Resource & Interchange System Application Service System Operation & Mngmt System Beacons & Gateway Bosch XDK Smart Sensor Individual Smart Sensor RIOTANA Digital Infrastructure and Analytics · 7
  • 8. © Fraunhofer ISST CONTENT  Data in Business Ecosystems  Data Sovereignty and Interoperability  International Data Spaces Approach public· 8
  • 9. © Fraunhofer ISST Data sharing is a key prerequisite for successful business ecosystems Image sources: Johns Hopkins University (2016), Umweltbundesamt (2016), Smellgard, Schneider & Farkas (2016), urbanmanagement.nl (2017). Data Sharing Energy Healthcare Material Sciences Manufacturing and Logistics »Smart Cities« Sharing of material information along the entire product life cycle Shared use of process data for predictive asset maintenance Sharing of master and event data along the entire supply chain Anonymized, shared data pool for better drug development Shared use of data for end-to-end consumer services public· 9
  • 10. © Fraunhofer ISST Interoperability is key – both on a business ecosystem and in particular on a data level Source: BMWi (2016). Reference Architecture Model Industry 4.0 Administration Shell Concept The Administration Shell stores all data of a hardware or software component in production scenarios. It makes data and services related to that component available for Industry 4.0 scenarios in a standardized way. public· 10
  • 11. © Fraunhofer ISST Typically, when shared, data increases in value Source: Moody & Walsh (1999). public Number of users Share of value 100% Data Tangible Goods Tangible Goods Value Data Usage Time Potential value Data Data quality Value 100% Data Integration Value Data Volume Value Data · 11
  • 12. © Fraunhofer ISST As a consequence, enterprises are confronted with the need of »squaring the data circle« … Source: Otto (2016). Interoperability Data Exchange »Sharing Economy« Data-centric Services Data Ownership Data Privacy and Security Data Value Data sovereignty is the capability of a natural person or corporate entity for exclusive self-determination with regard to its economic data goods public· 12
  • 13. © Fraunhofer ISST CONTENT  Data in Business Ecosystems  Data Sovereignty and Interoperability  International Data Spaces Approach public· 13
  • 14. © Fraunhofer ISST The IDS Reference Architecture Model responds to the most important data issues in business ecosystems Source: PwC (2017). The International Data Spaces (IDS) Association publishes the IDS Reference Architecture Model (IDS-RAM). The Industrial Data Space is a vertical application of the IDS-RAM. 57% worry about revealing valuable data and business secrets. 59% fear the loss of control over their data. 55% feel inconsistent processes and systems as a (very) big obstacle. 32% fear that platforms do not reach the critical mass, so that data exchange will be interesting. InteroperabilityData SovereigntyTrust and Security Join us! Today IDS Approach public· 14
  • 15. © Fraunhofer ISST The IDS architecture aims at sovereign sharing and smooth exchange of data in business ecosystems Legend: IDS Connector; Usage Constraints; Non-IDS Communication. public Industrial Data Cloud IoT Cloud Enterprise Cloud Data Marketplace Company 1 Company 2 Company n + 2Company n + 1Company n Open Data Source IDS IDS IDS IDS IDS IDS IDS IDS IDS IDS IDS IDS IDS IDS IDS IDS IDS · 15
  • 16. © Fraunhofer ISST »Production as a Service« Provider Use Context Machine Type Constraint Delete CAD data after first use OEM Production Planning and Control Data sovereignty is achieved by attaching usage conditions to shared data – as the additive manufacturing scenario shows  Contact information  CAD data  Configuration parameters  Output  Use duration  Temperature  Certificates Use Context Maintenance, no forwarding Constraint Operator anonymous Maintenance Service public· 16
  • 17. © Fraunhofer ISST Interoperability is fostered by the use of domain-specific vocabularies and the IDS Information Model Administration Shell Real-World Object Configuration Parameter Product Sheet … IDS Information Model Shop Floor Data Material Master Data eCl@ss ID Data Endpoint Usage Policy Data Ownership … public· 17
  • 18. © Fraunhofer ISST The IDS itself forms a business ecosystem for data sharing Source: Otto et al. (2017); extended representation of the reference architecture model content. public Runtime EnvironmentRuntime Environment authorize publish app transfer data data flow metadata flow software flow identification useIDSsoftware useIDSsoftware useIDSsoftware identify Data Owner App Provider Vocabulary Provider Clearing House App Store Provider Identity Provider Data Consumer Broker Service Provider Service Provider Software Provider Data Provider Certification mandatory Membership in the IDSA mandatory Certification Authority · 18
  • 19. © Fraunhofer ISST Example Automobile Logistics The IDS aims at closing a semantic standardization gap Legend: RFID – Radio-Frequency Identification; IoT – Internet of Things; EDI – Electronic Data Interchange. Release orders · Dispatch notifications · Invoices … Parts master data · Change requests · Product information sheets … Supply chain event data … Data usage constraints  Data resource information EDI Electronic Business RFID · IoT IDS Time Value-added, sensitivity of shared data 1990 2000 2010 today public· 19
  • 20. © Fraunhofer ISST The IDS initiative makes various contributions to business ecosystem interoperability – mainly through semantic standardization public Object of Standardization IDS Scope Remark Data Ecosystem IDS Reference Architecture Model Tangible objects (e.g. machinery, parts) Using domain-specific standards such as eCl@ss Virtual objects (e.g. supply chain events, orders) Using domain-specific standards such as GS1 EPCIS Data objects Contributing to existing standards development organizations such as the W3C Usage constraints/conditions Inventory of policies and rules based on ODRL Communication interface Using von REST, MQTT as well as IDS Communication Protocol · 20
  • 21. © Fraunhofer ISST Prof. Dr.-Ing. Boris Otto Fraunhofer ISST · Executive Director TU Dortmund · Faculty of Mechanical Engineering [email protected] · [email protected] https://de.linkedin.com/pub/boris-otto/1/1b5/570 https://twitter.com/drborisotto https://www.xing.com/profile/Boris_Otto http://www.researchgate.net/profile/Boris_Otto http://de.slideshare.net/borisotto Please get in touch! public· 21
  • 22. © Fraunhofer ISST INTERNATIONAL DATA SPACES DATA SOVEREIGNTY AND INTEROPERABILITY FOR BUSINESS ECOSYSTEMS Prof. Dr.-Ing. Boris Otto  8 October 2018  Munich public· 22