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© Fraunhofer, TU Dortmund · Page 1
Prof. Dr. Boris Otto · Cambridge · February 1st, 2016
INDUSTRIAL DATA SPACE
Digital Sovereignty for Industry 4.0 and Smart Services
© Fraunhofer, TU Dortmund · Page 2
AGENDA
 Digitizing the Industrial Enterprise
 The Role of Data and the Industrial Data Space
 Outlook to Upcoming Activities
© Fraunhofer, TU Dortmund · Page 3
adidas combines digital services and lot size 1 production
Source: Handelsblatt, August 6, 2015, No. 149; http://www.adidas-group.com/de/medien/newsarchiv/pressemitteilungen/
2015/adidas-gruppe-erwirbt-runtastic/; startjp.com
In-Store ProductionSmart Service »Runtastic«
© Fraunhofer, TU Dortmund · Page 4
Successful value propositions are becoming increasingly
»hybrid«—as the example of adidas shows
Image sources: otto.de (2015), techglam.com (2015), soccerreviews.com (2015), appfullapk.co (2015).
Time
»Hybridity«
Physical
Product
(Running
Shoe)
»Traditional
Service«
(Work-Out
Monitor)
Digital
Service
(Runtastic)
© Fraunhofer, TU Dortmund · Page 5
Tool machine manufacturer TRUMPF wants to offer an
AppStore around metal sheet processing
Tool Machine as Physical Asset Digital Value-Added Service
Source: http://www.de.trumpf.com/de/produkte/werkzeugmaschinen/services/software/trutops-boost/bedienphilosophie.html;
https://www.media.trumpf.com/trumpfbdb/Object.jsp?web=bdb_press_free&obj_id=7675&view=image.
© Fraunhofer, TU Dortmund · Page 6
Digital products follow a platform architecture logic
 Services can be separated from
physical platforms
 Architectural layers are de-coupled
 Products turn to platforms—and
vice-versa
 Ecosystems form around platforms
 Innovation happens in co-opetition
modes
Digital Business Architecture Principles of the Digital Economy
SMART PRODUCTS
SMART SPACES
SMART DATA
SMART SERVICES
Source: Working Group Smart Service Welt (2015).
© Fraunhofer, TU Dortmund · Page 7
Agricultural machinery manufacturers are driving
comprehensive digital farming solutions
Precision Farming Value Creation in Ecosystems
Image sources: wiwo (2015), traction-magazin.de (2014).
Source: Beecham Research Ltd. (2014).
Digital
Farming
Ecosystem
Machine
Providers
Crop Science
Companies
Farmers
Wholesale
Technology
Providers
Influencers
© Fraunhofer, TU Dortmund · Page 8
Source: Working Group Smart Service Welt (2015), Ernst & Young (2011).
The »Smart Service Welt« is a response to changing
customer needs
End-to-End Customer Process
Individualization
Ubiquity of Service Consumption
Information Transparency
© Fraunhofer, TU Dortmund · Page 9
Thus, Industry 4.0 is a means to an end, not an
end in itself—as the example of Audi shows
Individualization of customer demands ↑
Number of models, variants, features ↑
Product life-cycles ↓
Globalization of processes ↑
Process and product complexity ↑
Cost targets ↗
Decision needs (strategic, tactical,
operational) ↑
»Autonomization« of manufacturing ↑
Real-time information availability ↑
Interoperability of production systems ↑
Market and Customer Demands
Manufacturing and Logistics
Implications and Needs for Action
Industry 4.0
© Fraunhofer, TU Dortmund · Page 10
Industry 4.0 enables smart manufacturing through cyber-
physical systems and decentralized control
Solution Components
 Cyber-physical systems
 Self-configuration
 Virtual representation
 Context-aware
information management
Benefits
 Increased flexibility and
agility
 Coping with complexityNew customer order: We need an
extra shift on Saturday.
I need to go home
now. Who can
take over my
orders?
I have to be at the goods
issue in 2 hours!
I‘m booked out till
Friday!
Sorry, I‘m not
available on Saturday.
I can work on
Saturday.
Magazine will be
empty soon, please refill!
© Fraunhofer, TU Dortmund · Page 11
Industry 4.0 enables smart manufacturing in electric car
production
Solution Components
 All objects and items are interconnected
 Assembly parts find their way on their
own through production
 Redundant manufacturing capacities are
autonomously distributing work loads
among each other
Benefits
 No central control systems required
 Dynamic system reaction in case of exceptions
 High scalability of all production processes
Source: SMART FACE-Project Consortium (2014).
Supported by
© Fraunhofer, TU Dortmund · Page 12
Industry 4.0 enables smart intralogistics
 Small autonomous transport units (shuttles)
replace inflexible conveyor technology
 Cellular transport systems (CTS) follow self-
control principle
 CTS uses swarm intelligence for handling
complex transport tasks.
 Autonomous transport management
 Increase of:
 Changeability
 Scalability and Flexibility
 Logistics performance where it is required!
© Fraunhofer, TU Dortmund · Page 13
Industry 4.0 increases and efficiency in the warehouse
Solution Components
 Autonomous navigation in the shelf
 No lift needed
 Flexible deployment of rack racers
 85 percent 3D printed components
Benefits
 Functional and cost advantages compared to
state-of-the-art
 Increased flexibility of storage systems
 Reduced fixed costs
 No bottleneck through lift, thus reduced storage
cycle times
Source: Fraunhofer IML (2014).
© Fraunhofer, TU Dortmund · Page 14
Industry 4.0 is a design principle for the industrial
enterprise of the future
Industry 4.0
Connectivity
Autonomy
Human-
Machine-
Interaction
Virtual
Entities
Modularity
Real-Time
Capability
© Fraunhofer, TU Dortmund · Page 15
As a consequence production and supply chain
complexity is dramatically increasing
No. of Variants
Production
Volume per
Variant
1850
1913
1955
1980
2000
Source: Koren (2010), cited in Bauernhansl (2014). Image sources: https://en.wikipedia.org (2015), https://www.impulse.de (2015), audi.de
(2015), o2.co.uk (2015), computerbild.de (2015).
Ford Model T
VW Beetle
Production
Audi Configurator
Mass
Production
Individualization
»Shareconomy«
Complexity
Globalization
iPhone
3D Printed Car
© Fraunhofer, TU Dortmund · Page 16
AGENDA
 Digitizing the Industrial Enterprise
 The Role of Data and the Industrial Data Space
 Outlook to Upcoming Activities
© Fraunhofer, TU Dortmund · Page 17
Data has evolved from a byproduct of operations to a
strategic resource
Time
Value-added
Data as
byproduct
of processes
Data as
process
enabler
Data as
product
enabler
Data as a
product
itself
© Fraunhofer, TU Dortmund · Page 18
Data is the strategic resource to link »Industry 4.0« and
»Smart Service Welt«
Information flow
Public
Data
Data from the
Value Chain
Commercial
Services
Industrial
Services
Individualization
End-to-End
Customer Process
Ecosystem
Ubiquity
Smart Data
Management
Interoperability
Human-Machine-
Collaboration
Autonomous
Systems
Internet of Things
Customer
Production
Networks
Logistics
Networks
»Smart Service Welt«Data»Industry 4.0«
Material flow.Legend:
© Fraunhofer, TU Dortmund · Page 19
The Industrial Data Space aims at a
»Network of Trusted Data«
Sovereignty
Data and ServicesTrustworthiness
Certified Members
Decentralization
Federated Architecture
Openness
Neutral and User-Driven
Governance
Common Rules of the
Game
Scalability
Network Effects
Ecosystem
Platform and Services
Security
Data Exchange
© Fraunhofer, TU Dortmund · Page 20
The overall Industrial Data Space architecture
takes four different viewpoints
Business and Governance Data and Services
Software Security
Industrial Data Space
© Fraunhofer, TU Dortmund · Page 21
A technology-agnostic »Business Map« describes
functional data services
Industrial Data Space
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
Industrial Data Space
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
Industrial Data Space
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
© Fraunhofer, TU Dortmund · Page 22
Industrial Data Space
Upload / Download / Search
Internet
AppsVocabulary
Industrial Data Space
Broker
Clearing
RegistryIndex
Industrial Data Space
App Store
Internal IDS
Connector
Company A Internal IDS
Connector
Company B
External IDS
Connector
External IDS
Connector
Upload
Third Party
Cloud Provider
Download
Upload / Download
© Fraunhofer
The software architecture consists of a set of
components
© Fraunhofer, TU Dortmund · Page 23
The Industrial Data Space recognizes five
different organizational roles
Industrial
Data
Space
Data
Provider
Data
User
AppStore
Provider
Broker
Certifying
Agency
© Fraunhofer, TU Dortmund · Page 24
Some key features characterize the
Industrial Data Space
 Digital sovereignty over data assets
 Secure »Data Supply Chain«
 Easy data linking
 Data economy blueprint
 Trusted participants through certification
 Federated/distributed data storage
 Collaborative data governance models
 Open participation process
© Fraunhofer, TU Dortmund · Page 25
The Industrial Data Space focuses on
data services
Automotive Electronics Services Logistics Manufacturing Life Sciences
Smart Service Domains
Smart Services and Products
»Smart Data Services« (Alerting, Monitoring, Data Quality etc.)
»Basic Data Services« (Data Fusion, Mapping, Aggregation etc.)
Internet of Things ∙ Broadband Infrastructure ∙ 5G
Real-time Scenarios ∙ Sensors and Actuators ∙ Devices
ArchitectureLayers
INDUSTRIAL DATA SPACE
© Fraunhofer, TU Dortmund · Page 26
The activities are organized as a research project
and within a chartered association
Preparation Research Project
Use Phase
Q3/2014 01.10.15 01.10.18
Industrial Data Space Chartered Association
26.01.16
© Fraunhofer, TU Dortmund · Page 27
The Industrial Data Space Chartered Association
was founded on January 26th, 2015, in Berlin
© Fraunhofer, TU Dortmund · Page 28
AGENDA
 Digitizing the Industrial Enterprise
 The Role of Data and the Industrial Data Space
 Outlook to Upcoming Activities
© Fraunhofer, TU Dortmund · Page 29
The work plan for the upcoming months is all set
 Delivering BMBF research project
 Identification of further use cases
 Positioning on European level
 Joint preparation of usage and operating models
 Communication and public relations
© Fraunhofer, TU Dortmund · Page 30
The Industrial Data Space activites are closely aligned
with the »plattform Industrie 4.0«
Retail 4.0 Banking 4.0Insurance
4.0
…Industrie 4.0
Focus on
Manufacturing
Industries Smart Services
Network, Data
Transmission
Real-time
Systems
Industrial Data Space
Focus on Data
Data
…
© Fraunhofer, TU Dortmund · Page 31
Innovative Digital Business Models require the »Tactile
Internet«
Car2Car & Car2X Communication
Industrial Wireless
Requirements
 1000 x Data Throughput
 100 x Devices
 10 x Battery Lifespan
 1 ms Latency
Technology
 DSL boxes and streep lights
become transmitters
 Fibreglass
Testbed Mobile High Speed Internet
© Fraunhofer, TU Dortmund · Page 32
The Industrial Data Space at a Glance!
© Fraunhofer, TU Dortmund · Page 33
Prof. Dr. Boris Otto
Fraunhofer IML & ISST
Boris.Otto@iml.fraunhofer.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
Thank you very much for your attention!
© Fraunhofer, TU Dortmund · Page 34
Prof. Dr. Boris Otto · Zurich · December 9th, 2015
INDUSTRIAL DATA SPACE:
STATUS UPDATE

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Industrial Data Space: Digital Sovereignty for Industry 4.0 and Smart Services

  • 1. © Fraunhofer, TU Dortmund · Page 1 Prof. Dr. Boris Otto · Cambridge · February 1st, 2016 INDUSTRIAL DATA SPACE Digital Sovereignty for Industry 4.0 and Smart Services
  • 2. © Fraunhofer, TU Dortmund · Page 2 AGENDA  Digitizing the Industrial Enterprise  The Role of Data and the Industrial Data Space  Outlook to Upcoming Activities
  • 3. © Fraunhofer, TU Dortmund · Page 3 adidas combines digital services and lot size 1 production Source: Handelsblatt, August 6, 2015, No. 149; http://www.adidas-group.com/de/medien/newsarchiv/pressemitteilungen/ 2015/adidas-gruppe-erwirbt-runtastic/; startjp.com In-Store ProductionSmart Service »Runtastic«
  • 4. © Fraunhofer, TU Dortmund · Page 4 Successful value propositions are becoming increasingly »hybrid«—as the example of adidas shows Image sources: otto.de (2015), techglam.com (2015), soccerreviews.com (2015), appfullapk.co (2015). Time »Hybridity« Physical Product (Running Shoe) »Traditional Service« (Work-Out Monitor) Digital Service (Runtastic)
  • 5. © Fraunhofer, TU Dortmund · Page 5 Tool machine manufacturer TRUMPF wants to offer an AppStore around metal sheet processing Tool Machine as Physical Asset Digital Value-Added Service Source: http://www.de.trumpf.com/de/produkte/werkzeugmaschinen/services/software/trutops-boost/bedienphilosophie.html; https://www.media.trumpf.com/trumpfbdb/Object.jsp?web=bdb_press_free&obj_id=7675&view=image.
  • 6. © Fraunhofer, TU Dortmund · Page 6 Digital products follow a platform architecture logic  Services can be separated from physical platforms  Architectural layers are de-coupled  Products turn to platforms—and vice-versa  Ecosystems form around platforms  Innovation happens in co-opetition modes Digital Business Architecture Principles of the Digital Economy SMART PRODUCTS SMART SPACES SMART DATA SMART SERVICES Source: Working Group Smart Service Welt (2015).
  • 7. © Fraunhofer, TU Dortmund · Page 7 Agricultural machinery manufacturers are driving comprehensive digital farming solutions Precision Farming Value Creation in Ecosystems Image sources: wiwo (2015), traction-magazin.de (2014). Source: Beecham Research Ltd. (2014). Digital Farming Ecosystem Machine Providers Crop Science Companies Farmers Wholesale Technology Providers Influencers
  • 8. © Fraunhofer, TU Dortmund · Page 8 Source: Working Group Smart Service Welt (2015), Ernst & Young (2011). The »Smart Service Welt« is a response to changing customer needs End-to-End Customer Process Individualization Ubiquity of Service Consumption Information Transparency
  • 9. © Fraunhofer, TU Dortmund · Page 9 Thus, Industry 4.0 is a means to an end, not an end in itself—as the example of Audi shows Individualization of customer demands ↑ Number of models, variants, features ↑ Product life-cycles ↓ Globalization of processes ↑ Process and product complexity ↑ Cost targets ↗ Decision needs (strategic, tactical, operational) ↑ »Autonomization« of manufacturing ↑ Real-time information availability ↑ Interoperability of production systems ↑ Market and Customer Demands Manufacturing and Logistics Implications and Needs for Action Industry 4.0
  • 10. © Fraunhofer, TU Dortmund · Page 10 Industry 4.0 enables smart manufacturing through cyber- physical systems and decentralized control Solution Components  Cyber-physical systems  Self-configuration  Virtual representation  Context-aware information management Benefits  Increased flexibility and agility  Coping with complexityNew customer order: We need an extra shift on Saturday. I need to go home now. Who can take over my orders? I have to be at the goods issue in 2 hours! I‘m booked out till Friday! Sorry, I‘m not available on Saturday. I can work on Saturday. Magazine will be empty soon, please refill!
  • 11. © Fraunhofer, TU Dortmund · Page 11 Industry 4.0 enables smart manufacturing in electric car production Solution Components  All objects and items are interconnected  Assembly parts find their way on their own through production  Redundant manufacturing capacities are autonomously distributing work loads among each other Benefits  No central control systems required  Dynamic system reaction in case of exceptions  High scalability of all production processes Source: SMART FACE-Project Consortium (2014). Supported by
  • 12. © Fraunhofer, TU Dortmund · Page 12 Industry 4.0 enables smart intralogistics  Small autonomous transport units (shuttles) replace inflexible conveyor technology  Cellular transport systems (CTS) follow self- control principle  CTS uses swarm intelligence for handling complex transport tasks.  Autonomous transport management  Increase of:  Changeability  Scalability and Flexibility  Logistics performance where it is required!
  • 13. © Fraunhofer, TU Dortmund · Page 13 Industry 4.0 increases and efficiency in the warehouse Solution Components  Autonomous navigation in the shelf  No lift needed  Flexible deployment of rack racers  85 percent 3D printed components Benefits  Functional and cost advantages compared to state-of-the-art  Increased flexibility of storage systems  Reduced fixed costs  No bottleneck through lift, thus reduced storage cycle times Source: Fraunhofer IML (2014).
  • 14. © Fraunhofer, TU Dortmund · Page 14 Industry 4.0 is a design principle for the industrial enterprise of the future Industry 4.0 Connectivity Autonomy Human- Machine- Interaction Virtual Entities Modularity Real-Time Capability
  • 15. © Fraunhofer, TU Dortmund · Page 15 As a consequence production and supply chain complexity is dramatically increasing No. of Variants Production Volume per Variant 1850 1913 1955 1980 2000 Source: Koren (2010), cited in Bauernhansl (2014). Image sources: https://en.wikipedia.org (2015), https://www.impulse.de (2015), audi.de (2015), o2.co.uk (2015), computerbild.de (2015). Ford Model T VW Beetle Production Audi Configurator Mass Production Individualization »Shareconomy« Complexity Globalization iPhone 3D Printed Car
  • 16. © Fraunhofer, TU Dortmund · Page 16 AGENDA  Digitizing the Industrial Enterprise  The Role of Data and the Industrial Data Space  Outlook to Upcoming Activities
  • 17. © Fraunhofer, TU Dortmund · Page 17 Data has evolved from a byproduct of operations to a strategic resource Time Value-added Data as byproduct of processes Data as process enabler Data as product enabler Data as a product itself
  • 18. © Fraunhofer, TU Dortmund · Page 18 Data is the strategic resource to link »Industry 4.0« and »Smart Service Welt« Information flow Public Data Data from the Value Chain Commercial Services Industrial Services Individualization End-to-End Customer Process Ecosystem Ubiquity Smart Data Management Interoperability Human-Machine- Collaboration Autonomous Systems Internet of Things Customer Production Networks Logistics Networks »Smart Service Welt«Data»Industry 4.0« Material flow.Legend:
  • 19. © Fraunhofer, TU Dortmund · Page 19 The Industrial Data Space aims at a »Network of Trusted Data« Sovereignty Data and ServicesTrustworthiness Certified Members Decentralization Federated Architecture Openness Neutral and User-Driven Governance Common Rules of the Game Scalability Network Effects Ecosystem Platform and Services Security Data Exchange
  • 20. © Fraunhofer, TU Dortmund · Page 20 The overall Industrial Data Space architecture takes four different viewpoints Business and Governance Data and Services Software Security Industrial Data Space
  • 21. © Fraunhofer, TU Dortmund · Page 21 A technology-agnostic »Business Map« describes functional data services Industrial Data Space 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 Industrial Data Space 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 Industrial Data Space 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
  • 22. © Fraunhofer, TU Dortmund · Page 22 Industrial Data Space Upload / Download / Search Internet AppsVocabulary Industrial Data Space Broker Clearing RegistryIndex Industrial Data Space App Store Internal IDS Connector Company A Internal IDS Connector Company B External IDS Connector External IDS Connector Upload Third Party Cloud Provider Download Upload / Download © Fraunhofer The software architecture consists of a set of components
  • 23. © Fraunhofer, TU Dortmund · Page 23 The Industrial Data Space recognizes five different organizational roles Industrial Data Space Data Provider Data User AppStore Provider Broker Certifying Agency
  • 24. © Fraunhofer, TU Dortmund · Page 24 Some key features characterize the Industrial Data Space  Digital sovereignty over data assets  Secure »Data Supply Chain«  Easy data linking  Data economy blueprint  Trusted participants through certification  Federated/distributed data storage  Collaborative data governance models  Open participation process
  • 25. © Fraunhofer, TU Dortmund · Page 25 The Industrial Data Space focuses on data services Automotive Electronics Services Logistics Manufacturing Life Sciences Smart Service Domains Smart Services and Products »Smart Data Services« (Alerting, Monitoring, Data Quality etc.) »Basic Data Services« (Data Fusion, Mapping, Aggregation etc.) Internet of Things ∙ Broadband Infrastructure ∙ 5G Real-time Scenarios ∙ Sensors and Actuators ∙ Devices ArchitectureLayers INDUSTRIAL DATA SPACE
  • 26. © Fraunhofer, TU Dortmund · Page 26 The activities are organized as a research project and within a chartered association Preparation Research Project Use Phase Q3/2014 01.10.15 01.10.18 Industrial Data Space Chartered Association 26.01.16
  • 27. © Fraunhofer, TU Dortmund · Page 27 The Industrial Data Space Chartered Association was founded on January 26th, 2015, in Berlin
  • 28. © Fraunhofer, TU Dortmund · Page 28 AGENDA  Digitizing the Industrial Enterprise  The Role of Data and the Industrial Data Space  Outlook to Upcoming Activities
  • 29. © Fraunhofer, TU Dortmund · Page 29 The work plan for the upcoming months is all set  Delivering BMBF research project  Identification of further use cases  Positioning on European level  Joint preparation of usage and operating models  Communication and public relations
  • 30. © Fraunhofer, TU Dortmund · Page 30 The Industrial Data Space activites are closely aligned with the »plattform Industrie 4.0« Retail 4.0 Banking 4.0Insurance 4.0 …Industrie 4.0 Focus on Manufacturing Industries Smart Services Network, Data Transmission Real-time Systems Industrial Data Space Focus on Data Data …
  • 31. © Fraunhofer, TU Dortmund · Page 31 Innovative Digital Business Models require the »Tactile Internet« Car2Car & Car2X Communication Industrial Wireless Requirements  1000 x Data Throughput  100 x Devices  10 x Battery Lifespan  1 ms Latency Technology  DSL boxes and streep lights become transmitters  Fibreglass Testbed Mobile High Speed Internet
  • 32. © Fraunhofer, TU Dortmund · Page 32 The Industrial Data Space at a Glance!
  • 33. © Fraunhofer, TU Dortmund · Page 33 Prof. Dr. Boris Otto Fraunhofer IML & ISST Boris.Otto@iml.fraunhofer.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 Thank you very much for your attention!
  • 34. © Fraunhofer, TU Dortmund · Page 34 Prof. Dr. Boris Otto · Zurich · December 9th, 2015 INDUSTRIAL DATA SPACE: STATUS UPDATE