Industrial Data Space – The Framework for Asset Management in Horizontal Integration of Industry 4.0 Presented by Dr. Wong Thein Lai, Principal Researcher Faculty of Computing and Information Technology Tunku Abdul Rahman University College Date: 29 March 2019 Venue: TAR UC Main Campus 1 /22
Data in Data Economy 2 /22 Source: International Data Space Association
How To Unleash The value of Your Data Link with Make data ecosystem available partners INDUSTRIAL DATA SPACE Control Create access to value your data 3 /22
What is the Industrial Data Space (IDS)? • Industrial Data Space is a peer-to-peer network, a virtual data space that supports the secure exchange and the simple linking of data in business eco-systems on the basis of standards and by means of common governance models. 4 /22 Source: International Data Space Association
What is so special about IDS? • Data security and data sovereignty are the essential features of Industrial Data Space. • Data owners always keep control over their data and can also fulfil their own standards of data security. • The data are exchanged safely on demand, if they are requested by certified, trustworthy partners. 5 /22
Industrial Data Space – 2016 • Industrial Data Space is a virtual data space leveraging existing standards and technologies, as well as accepted governance models, to facilitate the secure exchange and easy linkage of data in a trusted business ecosystem . • Industrial Data Space research projects are funded by the German Federal Ministry of Education and Research (BMBF) and Fraunhofer-Gesellschaft (a key role in Industrie 4.0) • Industrial Data Space e.V. was founded on January 26, 2016 in Berlin. it is a non-profit user association. • Industrial Data Space kicks off its post-Summer international tour at IoT Solutions World Congress 2017 in Barcelona e.V. : registered association or incorporated association in Germany 6 /22
Industrial Data Space Association (IDSA) Founding members of Industrial Data Space e.V. 7 /22 Source: International Data Space Association
Reference Architecture Model of IDS • a five-layer structure expressing stakeholder concerns and viewpoints at different levels of granularity • compliance with common system architecture models and standards (such as ISO 42010, 4+1 view model…) Source: Fraunhofer – Reference Architecture Model for the Industrial Data Space 8 /22
Mapping of IDS to RAMI4.0 9 /22 Image source: International Data Space Association
Roles of Participants in IDS Business Layer Metadata contains information about the Data Provider, syntax and semantics of the Source: Fraunhofer – Reference Architecture data itself, and additional information (e.g., pricing information or usage policies). Model for the Industrial Data Space 10 /22
Ecosystem of Data Service Provider Broker Data Data Data Data User Provider Owner Consumer Clearing House Vocabulary Provider App Store App Provider Provider 11 /22
Ecosystem of Data Service Provider Broker Authorize Data Data Data Data User Provider Owner Consumer Clearing House Vocabulary Provider App Store App Provider Provider 12 /22
Ecosystem of Data Service Provider Broker Authorize Data Data Data Data User Provider Owner Consumer Clearing House Vocabulary Provider App Store App Provider Provider 13 /22
Ecosystem of Data Service Provider Broker Authorize Data Data Data Data User Provider Owner Consumer Clearing House Vocabulary Provider App Store App Provider Provider 14 /22
Ecosystem of Data Service Provider Broker Authorize Data Data Data Data User Provider Owner Consumer Clearing House Vocabulary Provider App Store App Provider Provider 15 /22
Ecosystem of Data Service Provider Broker Authorize transfer Data Data Data Data User data Provider Owner Consumer Clearing House Vocabulary Provider App Store App Provider Provider 16 /22
Ecosystem of Data Service Provider Broker Authorize transfer Data Data Data Data User data Provider Owner Consumer Clearing House Vocabulary Provider App Store App Provider Provider 17 /22
Ecosystem of Data Service Provider Broker use data Authorize transfer Data Data Data Data User data Provider Owner Consumer Clearing House Vocabulary Provider App Store App Provider Provider 18 /22
Glossary of IDS Participants Data Owner Legal rights and complete control over its data. To authorize a Data Provider to publish its data. Any authorization is in documented contract or policy Data Provider Exchanging data, facilitate a data request with a Data Consumer, provide metadata to broker, can be also Data Owner Data Consumer Similar to Data Provider to exchange data, log record in Clearing House, use Data Apps to manage data from Data Provider connect to IDS Broker Service Provider Manage a metadata repository that provides information about the data sources available in IDS. Focus on receiving and providing metadata Clearing House Intermediary that provides clearing and settlement services for all financial and data exchange transactions. Identity Provider For secure operation, to avoid unauthorized access to data in IDS, service to verify identities described by a set of properties App Provider develop Data Apps to be used in IDS. To be deployable, a Data App has to be compliant with the system architecture of IDS Vocabulary Provider manages and offers vocabularies (i.e., ontologies, reference data models, or metadata elements) that can be used to annotate and describe datasets. Software Provider provides software required by IDS. Not through App Store but individual agreements between Software Provider and software user Service Provider Provide additional services such as data analysis, integration, cleaning or semantic enrichment to improve data exchanged in IDS 19 /22 Source: Fraunhofer, Reference Architecture Model for the Industrial Data Space
Core Principles of Industrial Data Space (Self determination) Source: Core principles of Industrial Data Space – EU Presentation 20 /22
Strategic Requirements of Industrial Data 2. SECURITY AND DATA SOVEREIGNTY 1. TRUST 3. ECOSYSTEM • Authentication & • Roles OF DATA authorization • Identity • Data source • Usage policies & usage management description enforcement • User certification • Brokering • Trustworthy communication • Governance • Vocabularies & security by design • Technical certification 4. STANDARDIZED 6. DATA MARKETS INTEROPERABILI • Clearing & billing TY 5. VALUE ADDING • Domain -specific broker • Integration of APPS and marketplaces • Processing of data existing vocabularies • Use restrictions and legal • Handling of different • Remote execution aspects data formats (contract templates, etc.) • Connection of clouds and platforms 21 /22
Security and Data Sovereignty • Authentication & authorization • Usage policies & usage enforcement • Trustworthy communication and security by design • Technical certification 22 /22
Standardized Interoperability • Integration of existing vocabularies • Handling of different data formats • Connection of clouds and platforms 23 /22
IDS Connector 24 /22 Source: International Data Space Association
Industry 4.0 Framework Development RAMI 4.0 Framework Team Application SMI/SME TAR UC – 25 PhDs and Masters Software Kian Joo – 5 masters (2018, RM 450K) (Data Consumer) (Data Consumer) Ajiya – 5 masters (2019, RM 450K) More in 2019 include SI Connectivity API Asset ID Repository Asset Management RAMI 4.0 Transfer digital data System (Brokering) after authenticated Framework Asset Indexing, Clearing, Identity Providing Asset ID ( Metadata ) Broker (TAR UC) Asset Connectivity API Data Edge Asset Asset Management System Management (IDS Reference Architecture) ( Data Provider ) Main Functions • Asset Classification • Asset Certification SMI/SME • Asset Clearing • Consumer Identity Asset (Data Provider) • Consumer Authentication (Data Owner) 25 /22
IDS Implementation Milestones Base IDS Connector Pilot Run IDS Broker IDS Identity • System Adapter with and Trust (Hosted in • Data Access Control Industrial Management TAR UC) • IDS Communication Protocol partner support 2018 Q4 2019 Q4 2020 Q2 2020 Q4 2019 Q3 2020 Q1 2020 Q3 2021 Q1 AAS creation Domain-specific Trusted IDS IDS Clearing and storage Vocabulary Connector House (Hosted • Data Usage Creation (based in TAR UC) on eCl@ss Control • Audit Logging standard) 26 /22
Benefits and Strengths of IDS • Linking data of multiple data sources • Integration of different data types such as product data and environment data of production • Involvement of multiple factories or companies • Integration of multiple layers of the enterprise architecture such as shop floor and top floor • Foundation for Smart Factory and Smart Services 27 /22
IDS Use Case Example in Industrie 4.0 28 /22
Supplier Create Product Types AAS 29 /22
Product Types Information to Integrator 30 /22
Integrator Create Composite Product AAS 31 /22
Product Instances from Supplier to Integrator 32 /22
Integrator Monitor the Composite Product 33 /22
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