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A NEW IDEA FOR SHARING DATA - INTRODUCTION TO INDUSTRIAL DATA SPACE
WEBINAR
BY LARS NAGEL, SEBASTIAN STEINBUSS AND THORSTEN HUELSMANN, INDUSTRIAL DATA SPACE ASSOCIATION
INDUSTRIAL DATA SPACE
AN ECONOMIC ASSET
DATA
The key focus for a data-driven economy and
new business models is in linking data.
SENSOR DATAMATERIAL CHARACTERISTICSMOBILITY DATAFINANCIAL DATATECHNICAL DRAWINGS
Interoperability
Data Exchange
»Sharing Economy«
Data Centric
Services
Data Ownership
Data Security
Data Value
WITHOUT REGRET
COMPANIES WANT TO LINK DATA
www.industrialdataspace.org // 4
‘‘HOW TO‘‘ DATA ECONOMY
UNLEASH THE VALUE OF YOUR DATA
1. Make data available
2. Link with ecosystem
partners
3. Control the access
to your data
4. Create value
www.industrialdataspace.org
INDUSTRIAL DATA SPACE APPROACH:
// 5
SELF DETERMINED CONTROL OF DATA FLOWS
Endless Connectivity
standard for data flows between
all kinds of data endpoints
Trust between different
security domains
Comprehensive security functions
providing a maximum level of trust
Governance for the
data economy
usage control and enforcement
for data flows
www.industrialdataspace.org // 6
TO DO LIST
INDUSTRY 4.0 AND DATA ECONOMY
Everything needs to be secure
• Authentification & Authorisation
• Usage Policies & Usage Enforcement
• Trustworthy Communication
• Security by Design
• Techn. Certification
SECURITY
Connection of every data endpoint
• Integration of existing vocabularies
• Using different data formats
• Connection of clouds and platforms
STANDARDIZED
CONNECTIVITY Data is being traded as an asset
• Clearing & Billing
• Domain specific Broker and
Marketplaces
• Use Restrictions and Legal
Aspects (Contract Templates,
etc.)
DATA MARKETS
Being able to explain, find and
understand data
• Data source description
• Brokering
• Vocabulary
ECOSYSTEM OF DATA
Typical tasks can be solved
easier with apps
• Processing of Data
• Remote Execution
VALUE ADDING APPS
Trust is the basis of the IDS
• Identitymanagement
• User-certification
TRUST
1 2 3
4 5 6
www.industrialdataspace.org // 7
80+
Companies and
Organisations
5
Working Groups
20+
Use
Cases
1
Ecosystem
=
www.industrialdataspace.org // 8
MILESTONES REACHED
AND NEXT STEPS
ARCHITECTURE
Release of the
reference architecture
model 2.0 on
Hannover Fair
INTERNATIONAL
Members all over the
world, connecting with
important initiatives,
major european RTOs,
intense engagement in
european research
activities
STANDARD
Foundation of a
workinggroup at DIN to
create a DIN
specification for the IDS
connector
GO LIVE
Ecosystem potentially
running, first products,
enhancing global
adoption
www.industrialdataspace.org // 9
OUR USE CASES MAKE IT HAPPEN
ADOPTION OF INDUSTRIAL DATA SPACE
Build up an ecosystem by
integrating further partners (also
from different domains)
Setup use cases to validate and
implement Industrial Data Space
technology
Each member of the association
realizes a business driven use case
!
!
+
+
+
// 10
JOIN US
!LARS NAGEL
MANAGING DIRECTOR
INDUSTRIAL DATA SPACE ASSOCIATION
WWW.LINKEDIN.COM/IN/LARS-NAGEL-704411B8/
JOSEPH-VON-FRAUNHOFER-STR. 2-4
44227 DORTMUND | GERMANY
+49 231 9743 619
INFO@INDUSTRIALDATASPACE.ORG
@ids_association
#industrialdataspace
www.industrialdataspace.org
Ressource Hub – Press Area – Blog
// 11
INDUSTRIAL DATA
SPACE
BASIC IDEAS OF THE
IDS ARCHITECTURE
www.industrialdataspace.org // 12
ARCHITECTURE FOR DATA AND DATA SERVICES
AN INFRASTRUCTURE FOR ALL INDUSTRIES AND DOMAINS
Automotive
Electronics
and IT Logistics Retail and Food Health
… (other
Industries)
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
INDUSTRIAL DATA SPACE
www.industrialdataspace.org // 13
INDUSTRIAL DATA SPACE
P2P NETWORK OF TRUSTED DATA
Security
Data
exchange
Trust
Certified
Participants
Decentral
Approach
distributed
architecture
Sovereignty
over data
and services
Data Governance
“rules of
the game”
Economies of
scale
Networking
effects
Open
Approach
Neutral and
user-driven Network
of platforms
and services
• All actors oblige
themselves to play by the
rules of Industrial Data
Space
• Actors and technical
components are to be
certified
• We provide usage control
for data and different
tailor-made levels of trust
www.industrialdataspace.org // 14
A TRUSTED PEER TO PEER NETWORK
FOR ALL INDUSTRIES TO SHARE DATA
 Software components enable
all stakeholders (defined
roles) to participate in IDS
 The quantity of all (external)
IDS connectors defines the
Industrial Data Space
 Internal IDS connectors are
used to link data sources in
the company, to transform
and to improve them.
© Fraunhofer
www.industrialdataspace.org // 15Source: Fraunhofer – IDS Reference
Architecture, 2017
INTERACTION OF SYSTEMS
BrokerApp
Store
Data
Source Connector
Data Provider Data Consumer
Dataset(s) transferred from
Provider to Consumer
Metadata Description of
Datasets/Provider/Consumer
Application for specific data
manipulation
Data exchange (active)
App download
Metadata exchange
Data exchange (inactive)
Connector Data
Sink
Connector
Meta
Meta
Meta
Meta
Meta
Peer-to-peer
nodes
App
Data
Meta
App
App
App
App
Data
Meta
Connector:
Gives access to the
Industrial Data Space
Broker:
Manages Metadata of
Connectors and Participants
AppStore:
Provides Apps and Vocabularies
www.industrialdataspace.org // 16
REFERENCE ARCHITECURE OF A CONNECTOR
Execution Core Container:
Basic functionality for connectivity
App Store Container:
Environment for Custom Apps to
extend functionality
Custom Container:
Adapter for internal systems
Configuration Manager
Environment for Configurations,
e.g. Process based, Rules oriented
www.industrialdataspace.org // 17Source: Fraunhofer – IDS Reference
Architecture, 2017
REFERENCE ARCHITECURE OF A CONNECTOR
INDIVIDUAL SETUP WITH APPS
Application Container Management
Core OS
Core IDS Container
API for user defined containers
(e.g. Data Apps, System Adapters)
Virtualization
MessageHandling
Message Router
Message Bus
…
IDS Data Core
(e.g. IDS Vocabulary,
GS1 XML)
Data App
(e.g. Protocol
Transformation)
Data App
(e.g. Data
Transformation)
Data App
(e.g.
pseudonymization)
Data App
(e.g. Aggregation)
Data App
(e.g. Analytics)
Data App
(e.g. I18N)
www.industrialdataspace.org // 18
DATA EXCHANGE
Big Data
Analytics
App
(Trusted)
Metatag
App
Application Container Management
Core OS
Core IDS
Container
Application Container Management (Trusted)
Core OS (Trusted)
Core IDS
Container
(Trusted)
Data Consumer
Connec-
tivity App
Encrypted Connection
Query
Authentication and
Authorization
Data
Facility
QueryData
Result
Internal
Interface
Data Provider
• Data Consumer queries data from Data Provider
• Data Provider validates the query and provides data for Data Consumer
• Data Consumer has access to the result, depending on data visibility
www.industrialdataspace.org // 19
REMOTE DATA PROCESSING
Application Container Management (Trusted)
Core OS (Trusted)
Core IDS
Container
(Trusted)
Application Container Management (Trusted)
Core OS (Trusted)
Core IDS
Container
(Trusted)
Data Consumer Data Provider
Connec-
tivity App
Encypted Connection
Query
Authentication and
Authorization
Result
Facility
QueryData
Result
Internal
Interface
Remotely
Executed
App
(Trusted)
App provisioning
Data
• Data Consumer queries data from data provider and provides App (e.g.
analytics)
• Data Provider queries data and provides data to localy provided App
• The result set leaves the connector of the Data Provider and is available
for the Data Consumer
www.industrialdataspace.org // 20Source: Fraunhofer – IDS internal documentation, to
be published in Reference Architecture 2018
DATA USAGE CONTROL
USAGE CONTROL VS. ACCESS CONTROL
 Usage Control – a generalization of access control
 Fine-grained policies specify how data is handled after access has been granted
www.industrialdataspace.org // 21Source: Fraunhofer – IDS internal documentation, to
be published in Reference Architecture 2018
DATA USAGE CONTROL
BULDING BLOCKS
 Enforcement (technology-dependent components)
 Policy Enforcement Point (PEP): intercepts data
flows and enforces decision from PDP
 Policy Execution Point (PXP): performs actions in the system
 Decision and Enforcement (technology-independent components)
 Policy Decision Point (PDP): decision engine (e.g., rule based)
 Policy Information Point (PIP): provides additional information for decision making
 Specification and Management
 Policy Management Point (PMP): manages policies and components
 Policy Administration Point (PAP): user interface for policy specification (e.g., Policy Editor)
www.industrialdataspace.org // 22Source: Fraunhofer – IDS internal documentation, to
be published in Reference Architecture 2018
DATA USAGE CONTROL
TECHNICAL ENFORCEMENT, ORGANIZATIONAL RULES,
AND LEGAL CONTRACTS
 Usage Control extends, substitutes, and completes organizational rules/legal contracts
 Long term: replacement of organizational rules / legal contracts by technical enforcement
www.industrialdataspace.org // 23Source: Fraunhofer – IDS internal documentation, to
be published in Reference Architecture 2018
DATA USAGE CONTROL
ENFORCEMENT EXAMPLE
PEP and PXP within IDS Connector
PEP controlling data flow
PXP triggering delete action
www.industrialdataspace.org // 24Source: Fraunhofer – IDS internal documentation, to
be published in Reference Architecture 2018
DATA USAGE CONTROL
USAGE CONTROL TECHNOLOGIES IN THE INDUSTRIAL
DATA SPACE
 Integrated Distributed Data Usage Control
Enforcement (IND²UCE)
Fraunhofer IESE
 Label-based Usage Control (LUCON)
Fraunhofer AISEC
 Information Flow Tracking (IFT)/
Provenance Tracking
Fraunhofer IOSB
www.industrialdataspace.org // 25Source: Fraunhofer – IDS Reference
Architecture, 2017
IDENTIFICATION PROCESS
THE IDS HANDSHAKE
Prerequisites:
Certification of
Participants and Connectors
Handshake:
1. Establish Secure connection
based on IDS X.509 certificates
2. Request Self Assessment (IDS InfoModel)
3. Validate against Identity Provider
4. Check if partner is trustworthy
5. Check if provided data is consumable
6. Exchange data
www.industrialdataspace.org // 26Source: Fraunhofer – IDS internal documentation, to
be published in Reference Architecture 2018
IDS API
THE IDS PROVIDES AN API FOR YOUR API
www.industrialdataspace.org // 27Source: Fraunhofer – IDS internal documentation, to
be published in Reference Architecture 2018
INDUSTRIAL DATA SPACE INFORMATION MODEL
HIGH LEVEL VIEW / DOMAINS
www.industrialdataspace.org // 28Source: Fraunhofer – IDS internal documentation, to
be published in Reference Architecture 2018
INDUSTRIAL DATA SPACE INFORMATION MODEL
DATA PRODUCTS
www.industrialdataspace.org // 29Source: Fraunhofer – IDS internal documentation, to
be published in Reference Architecture 2018
INDUSTRIAL DATA SPACE INFORMATION MODEL
HERE IS YOUR API
www.industrialdataspace.org // 30
SECURITY PROFILES
APPROACH
1. Use Cases:
Driven by Use Cases
2. Dimensions
Identified:
• Development
• Roles
• Communication Abilities
• Higher Security Classes
3. Security Profiles
Important Insights:
• 4 Profiles Base Free, Base, Trust, Trust+
• All Connectors (not Base Free) can communicate in public IDS
• Base Free is public available
Development
Higher Security Classes
Trust+
Trust
Base
BaseFree
Public IDSDIY
www.industrialdataspace.org // 31
SECURITY PROFILES
BASE FREE, BASE, TRUST, TRUST+
Base Free Base Trust (Managed)Trust+
Reference
Development
Open Source IDS Community IDS Community Bound to strong SLAs
Roles Own infrastructure All IDS Roles supported,
Billing and Clearing
optional
All IDS Roles supported All IDS Roles supported
Communication
Abilities
Only private IDS with
self signed certificates
Full interoperable,
reduced trust
Full interoperable, Free
decision of
communication
Full interoperable, Free
decision of
communication,
Hardware anchor
Higher Security
Classes
Standard Security Level
required
Standard Security Level
required
High Security Level Higher Security Level
// 32
JOIN US
!SEBASTIAN STEINBUSS
LEAD ARCHITECT
INDUSTRIAL DATA SPACE ASSOCIATION
WWW.LINKEDIN.COM/IN/SEBASTIAN-STEINBUSS/
@SSTEINBUSS
JOSEPH-VON-FRAUNHOFER-STR. 2-4
44227 DORTMUND | GERMANY
+49 231 97677 428
SEBASTIAN.STEINBUSS@INDUSTRIALDATASPACE.ORG
@ids_association
#industrialdataspace
www.industrialdataspace.org
Ressource Hub – Press Area – Blog

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Webinar Industrial Data Space Association: Introduction and Architecture

  • 1. A NEW IDEA FOR SHARING DATA - INTRODUCTION TO INDUSTRIAL DATA SPACE WEBINAR BY LARS NAGEL, SEBASTIAN STEINBUSS AND THORSTEN HUELSMANN, INDUSTRIAL DATA SPACE ASSOCIATION INDUSTRIAL DATA SPACE
  • 2. AN ECONOMIC ASSET DATA The key focus for a data-driven economy and new business models is in linking data. SENSOR DATAMATERIAL CHARACTERISTICSMOBILITY DATAFINANCIAL DATATECHNICAL DRAWINGS
  • 3. Interoperability Data Exchange »Sharing Economy« Data Centric Services Data Ownership Data Security Data Value WITHOUT REGRET COMPANIES WANT TO LINK DATA
  • 4. www.industrialdataspace.org // 4 ‘‘HOW TO‘‘ DATA ECONOMY UNLEASH THE VALUE OF YOUR DATA 1. Make data available 2. Link with ecosystem partners 3. Control the access to your data 4. Create value
  • 5. www.industrialdataspace.org INDUSTRIAL DATA SPACE APPROACH: // 5 SELF DETERMINED CONTROL OF DATA FLOWS Endless Connectivity standard for data flows between all kinds of data endpoints Trust between different security domains Comprehensive security functions providing a maximum level of trust Governance for the data economy usage control and enforcement for data flows
  • 6. www.industrialdataspace.org // 6 TO DO LIST INDUSTRY 4.0 AND DATA ECONOMY Everything needs to be secure • Authentification & Authorisation • Usage Policies & Usage Enforcement • Trustworthy Communication • Security by Design • Techn. Certification SECURITY Connection of every data endpoint • Integration of existing vocabularies • Using different data formats • Connection of clouds and platforms STANDARDIZED CONNECTIVITY Data is being traded as an asset • Clearing & Billing • Domain specific Broker and Marketplaces • Use Restrictions and Legal Aspects (Contract Templates, etc.) DATA MARKETS Being able to explain, find and understand data • Data source description • Brokering • Vocabulary ECOSYSTEM OF DATA Typical tasks can be solved easier with apps • Processing of Data • Remote Execution VALUE ADDING APPS Trust is the basis of the IDS • Identitymanagement • User-certification TRUST 1 2 3 4 5 6
  • 7. www.industrialdataspace.org // 7 80+ Companies and Organisations 5 Working Groups 20+ Use Cases 1 Ecosystem =
  • 8. www.industrialdataspace.org // 8 MILESTONES REACHED AND NEXT STEPS ARCHITECTURE Release of the reference architecture model 2.0 on Hannover Fair INTERNATIONAL Members all over the world, connecting with important initiatives, major european RTOs, intense engagement in european research activities STANDARD Foundation of a workinggroup at DIN to create a DIN specification for the IDS connector GO LIVE Ecosystem potentially running, first products, enhancing global adoption
  • 9. www.industrialdataspace.org // 9 OUR USE CASES MAKE IT HAPPEN ADOPTION OF INDUSTRIAL DATA SPACE Build up an ecosystem by integrating further partners (also from different domains) Setup use cases to validate and implement Industrial Data Space technology Each member of the association realizes a business driven use case ! ! + + +
  • 10. // 10 JOIN US !LARS NAGEL MANAGING DIRECTOR INDUSTRIAL DATA SPACE ASSOCIATION WWW.LINKEDIN.COM/IN/LARS-NAGEL-704411B8/ JOSEPH-VON-FRAUNHOFER-STR. 2-4 44227 DORTMUND | GERMANY +49 231 9743 619 INFO@INDUSTRIALDATASPACE.ORG @ids_association #industrialdataspace www.industrialdataspace.org Ressource Hub – Press Area – Blog
  • 11. // 11 INDUSTRIAL DATA SPACE BASIC IDEAS OF THE IDS ARCHITECTURE
  • 12. www.industrialdataspace.org // 12 ARCHITECTURE FOR DATA AND DATA SERVICES AN INFRASTRUCTURE FOR ALL INDUSTRIES AND DOMAINS Automotive Electronics and IT Logistics Retail and Food Health … (other Industries) 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 INDUSTRIAL DATA SPACE
  • 13. www.industrialdataspace.org // 13 INDUSTRIAL DATA SPACE P2P NETWORK OF TRUSTED DATA Security Data exchange Trust Certified Participants Decentral Approach distributed architecture Sovereignty over data and services Data Governance “rules of the game” Economies of scale Networking effects Open Approach Neutral and user-driven Network of platforms and services • All actors oblige themselves to play by the rules of Industrial Data Space • Actors and technical components are to be certified • We provide usage control for data and different tailor-made levels of trust
  • 14. www.industrialdataspace.org // 14 A TRUSTED PEER TO PEER NETWORK FOR ALL INDUSTRIES TO SHARE DATA  Software components enable all stakeholders (defined roles) to participate in IDS  The quantity of all (external) IDS connectors defines the Industrial Data Space  Internal IDS connectors are used to link data sources in the company, to transform and to improve them. © Fraunhofer
  • 15. www.industrialdataspace.org // 15Source: Fraunhofer – IDS Reference Architecture, 2017 INTERACTION OF SYSTEMS BrokerApp Store Data Source Connector Data Provider Data Consumer Dataset(s) transferred from Provider to Consumer Metadata Description of Datasets/Provider/Consumer Application for specific data manipulation Data exchange (active) App download Metadata exchange Data exchange (inactive) Connector Data Sink Connector Meta Meta Meta Meta Meta Peer-to-peer nodes App Data Meta App App App App Data Meta Connector: Gives access to the Industrial Data Space Broker: Manages Metadata of Connectors and Participants AppStore: Provides Apps and Vocabularies
  • 16. www.industrialdataspace.org // 16 REFERENCE ARCHITECURE OF A CONNECTOR Execution Core Container: Basic functionality for connectivity App Store Container: Environment for Custom Apps to extend functionality Custom Container: Adapter for internal systems Configuration Manager Environment for Configurations, e.g. Process based, Rules oriented
  • 17. www.industrialdataspace.org // 17Source: Fraunhofer – IDS Reference Architecture, 2017 REFERENCE ARCHITECURE OF A CONNECTOR INDIVIDUAL SETUP WITH APPS Application Container Management Core OS Core IDS Container API for user defined containers (e.g. Data Apps, System Adapters) Virtualization MessageHandling Message Router Message Bus … IDS Data Core (e.g. IDS Vocabulary, GS1 XML) Data App (e.g. Protocol Transformation) Data App (e.g. Data Transformation) Data App (e.g. pseudonymization) Data App (e.g. Aggregation) Data App (e.g. Analytics) Data App (e.g. I18N)
  • 18. www.industrialdataspace.org // 18 DATA EXCHANGE Big Data Analytics App (Trusted) Metatag App Application Container Management Core OS Core IDS Container Application Container Management (Trusted) Core OS (Trusted) Core IDS Container (Trusted) Data Consumer Connec- tivity App Encrypted Connection Query Authentication and Authorization Data Facility QueryData Result Internal Interface Data Provider • Data Consumer queries data from Data Provider • Data Provider validates the query and provides data for Data Consumer • Data Consumer has access to the result, depending on data visibility
  • 19. www.industrialdataspace.org // 19 REMOTE DATA PROCESSING Application Container Management (Trusted) Core OS (Trusted) Core IDS Container (Trusted) Application Container Management (Trusted) Core OS (Trusted) Core IDS Container (Trusted) Data Consumer Data Provider Connec- tivity App Encypted Connection Query Authentication and Authorization Result Facility QueryData Result Internal Interface Remotely Executed App (Trusted) App provisioning Data • Data Consumer queries data from data provider and provides App (e.g. analytics) • Data Provider queries data and provides data to localy provided App • The result set leaves the connector of the Data Provider and is available for the Data Consumer
  • 20. www.industrialdataspace.org // 20Source: Fraunhofer – IDS internal documentation, to be published in Reference Architecture 2018 DATA USAGE CONTROL USAGE CONTROL VS. ACCESS CONTROL  Usage Control – a generalization of access control  Fine-grained policies specify how data is handled after access has been granted
  • 21. www.industrialdataspace.org // 21Source: Fraunhofer – IDS internal documentation, to be published in Reference Architecture 2018 DATA USAGE CONTROL BULDING BLOCKS  Enforcement (technology-dependent components)  Policy Enforcement Point (PEP): intercepts data flows and enforces decision from PDP  Policy Execution Point (PXP): performs actions in the system  Decision and Enforcement (technology-independent components)  Policy Decision Point (PDP): decision engine (e.g., rule based)  Policy Information Point (PIP): provides additional information for decision making  Specification and Management  Policy Management Point (PMP): manages policies and components  Policy Administration Point (PAP): user interface for policy specification (e.g., Policy Editor)
  • 22. www.industrialdataspace.org // 22Source: Fraunhofer – IDS internal documentation, to be published in Reference Architecture 2018 DATA USAGE CONTROL TECHNICAL ENFORCEMENT, ORGANIZATIONAL RULES, AND LEGAL CONTRACTS  Usage Control extends, substitutes, and completes organizational rules/legal contracts  Long term: replacement of organizational rules / legal contracts by technical enforcement
  • 23. www.industrialdataspace.org // 23Source: Fraunhofer – IDS internal documentation, to be published in Reference Architecture 2018 DATA USAGE CONTROL ENFORCEMENT EXAMPLE PEP and PXP within IDS Connector PEP controlling data flow PXP triggering delete action
  • 24. www.industrialdataspace.org // 24Source: Fraunhofer – IDS internal documentation, to be published in Reference Architecture 2018 DATA USAGE CONTROL USAGE CONTROL TECHNOLOGIES IN THE INDUSTRIAL DATA SPACE  Integrated Distributed Data Usage Control Enforcement (IND²UCE) Fraunhofer IESE  Label-based Usage Control (LUCON) Fraunhofer AISEC  Information Flow Tracking (IFT)/ Provenance Tracking Fraunhofer IOSB
  • 25. www.industrialdataspace.org // 25Source: Fraunhofer – IDS Reference Architecture, 2017 IDENTIFICATION PROCESS THE IDS HANDSHAKE Prerequisites: Certification of Participants and Connectors Handshake: 1. Establish Secure connection based on IDS X.509 certificates 2. Request Self Assessment (IDS InfoModel) 3. Validate against Identity Provider 4. Check if partner is trustworthy 5. Check if provided data is consumable 6. Exchange data
  • 26. www.industrialdataspace.org // 26Source: Fraunhofer – IDS internal documentation, to be published in Reference Architecture 2018 IDS API THE IDS PROVIDES AN API FOR YOUR API
  • 27. www.industrialdataspace.org // 27Source: Fraunhofer – IDS internal documentation, to be published in Reference Architecture 2018 INDUSTRIAL DATA SPACE INFORMATION MODEL HIGH LEVEL VIEW / DOMAINS
  • 28. www.industrialdataspace.org // 28Source: Fraunhofer – IDS internal documentation, to be published in Reference Architecture 2018 INDUSTRIAL DATA SPACE INFORMATION MODEL DATA PRODUCTS
  • 29. www.industrialdataspace.org // 29Source: Fraunhofer – IDS internal documentation, to be published in Reference Architecture 2018 INDUSTRIAL DATA SPACE INFORMATION MODEL HERE IS YOUR API
  • 30. www.industrialdataspace.org // 30 SECURITY PROFILES APPROACH 1. Use Cases: Driven by Use Cases 2. Dimensions Identified: • Development • Roles • Communication Abilities • Higher Security Classes 3. Security Profiles Important Insights: • 4 Profiles Base Free, Base, Trust, Trust+ • All Connectors (not Base Free) can communicate in public IDS • Base Free is public available Development Higher Security Classes Trust+ Trust Base BaseFree Public IDSDIY
  • 31. www.industrialdataspace.org // 31 SECURITY PROFILES BASE FREE, BASE, TRUST, TRUST+ Base Free Base Trust (Managed)Trust+ Reference Development Open Source IDS Community IDS Community Bound to strong SLAs Roles Own infrastructure All IDS Roles supported, Billing and Clearing optional All IDS Roles supported All IDS Roles supported Communication Abilities Only private IDS with self signed certificates Full interoperable, reduced trust Full interoperable, Free decision of communication Full interoperable, Free decision of communication, Hardware anchor Higher Security Classes Standard Security Level required Standard Security Level required High Security Level Higher Security Level
  • 32. // 32 JOIN US !SEBASTIAN STEINBUSS LEAD ARCHITECT INDUSTRIAL DATA SPACE ASSOCIATION WWW.LINKEDIN.COM/IN/SEBASTIAN-STEINBUSS/ @SSTEINBUSS JOSEPH-VON-FRAUNHOFER-STR. 2-4 44227 DORTMUND | GERMANY +49 231 97677 428 SEBASTIAN.STEINBUSS@INDUSTRIALDATASPACE.ORG @ids_association #industrialdataspace www.industrialdataspace.org Ressource Hub – Press Area – Blog