Industrial Data Space The Framework for Asset Management in - - PowerPoint PPT Presentation

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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

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Data in Data Economy

Source: International Data Space Association

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How To Unleash The value of Your Data

Make data available Link with ecosystem partners Control access to your data Create value INDUSTRIAL DATA SPACE

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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

• f standards and by means of common governance models.

Source: International Data Space Association

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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.

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• 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

Industrial Data Space – 2016

e.V. : registered association or incorporated association in Germany

7 /22 Founding members of Industrial Data Space e.V.

Industrial Data Space Association (IDSA)

Source: International Data Space Association

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• 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…)

Reference Architecture Model of IDS

Source: Fraunhofer – Reference Architecture Model for the Industrial Data Space

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Mapping of IDS to RAMI4.0

Image source: International Data Space Association

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Roles of Participants in IDS

Source: Fraunhofer – Reference Architecture Model for the Industrial Data Space Metadata contains information about the Data Provider, syntax and semantics of the data itself, and additional information (e.g., pricing information or usage policies).

Business Layer

11 /22 Broker Data Provider Data Owner Data User Data Consumer Clearing House Service Provider App Store Provider Vocabulary Provider App Provider

Ecosystem of Data

12 /22 Broker Data Provider Data Owner Data User Data Consumer Clearing House Service Provider App Store Provider Vocabulary Provider App Provider Authorize

Ecosystem of Data

13 /22 Broker Data Provider Data Owner Data User Data Consumer Clearing House Service Provider App Store Provider Vocabulary Provider App Provider Authorize

Ecosystem of Data

14 /22 Broker Data Provider Data Owner Data User Data Consumer Clearing House Service Provider App Store Provider Vocabulary Provider App Provider Authorize

Ecosystem of Data

15 /22 Broker Data Provider Data Owner Data User Data Consumer Clearing House Service Provider App Store Provider Vocabulary Provider App Provider Authorize

Ecosystem of Data

16 /22 Broker Data Provider Data Owner Data User Data Consumer Clearing House Service Provider App Store Provider Vocabulary Provider App Provider Authorize transfer data

Ecosystem of Data

17 /22 Broker Data Provider Data Owner Data Consumer Clearing House Service Provider App Store Provider Vocabulary Provider App Provider Authorize transfer data Data User

Ecosystem of Data

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Ecosystem of Data

Broker Data Provider Data Owner Data User Data Consumer Clearing House Service Provider App Store Provider Vocabulary Provider App Provider Authorize transfer data use data

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Glossary of IDS Participants

Source: Fraunhofer, Reference Architecture Model for the Industrial Data Space

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

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Core Principles of Industrial Data Space

Source: Core principles of Industrial Data Space – EU Presentation

(Self determination)

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Strategic Requirements of Industrial Data

• 1. TRUST
• Roles
• Identity

management

• User certification
• Governance
• 4. STANDARDIZED

INTEROPERABILI TY

• Integration of

existing vocabularies

• Handling of different

data formats

• Connection of clouds

and platforms

• 2. SECURITY AND

DATA SOVEREIGNTY

• Authentication &

authorization

• Usage policies & usage

enforcement

• Trustworthy communication

& security by design

• Technical certification
• 5. VALUE ADDING

APPS

• Processing of data
• Remote execution
• 3. ECOSYSTEM

OF DATA

• Data source

description

• Brokering
• Vocabularies
• 6. DATA MARKETS
• Clearing & billing
• Domain-specific broker

and marketplaces

• Use restrictions and legal

aspects (contract templates, etc.)

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Security and Data Sovereignty

• Authentication & authorization
• Usage policies & usage enforcement
• Trustworthy communication and security by

design

• Technical certification

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Standardized Interoperability

• Integration of existing vocabularies
• Handling of different data formats
• Connection of clouds and platforms

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IDS Connector

Source: International Data Space Association

25 /22 Asset ID Repository Asset (Data Owner)

Edge Asset Management

(Data Provider)

SMI/SME (Data Provider) Broker (TAR UC)

Connectivity API

Asset Management System (Brokering)

Asset Indexing, Clearing, Identity Providing

Application Software

(Data Consumer) Connectivity API

SMI/SME (Data Consumer)

Asset ID (Metadata) Asset Management System (IDS Reference Architecture) Main Functions

• Asset Classification
• Asset Certification
• Asset Clearing
• Consumer Identity
• Consumer Authentication

Transfer digital data after authenticated RAMI 4.0 Framework Team TAR UC – 25 PhDs and Masters Kian Joo – 5 masters (2018, RM 450K) Ajiya – 5 masters (2019, RM 450K) More in 2019 include SI

RAMI 4.0 Framework

Industry 4.0 Framework Development

Asset Data

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Base IDS Connector

• System Adapter
• Data Access Control
• IDS Communication Protocol

IDS Broker (Hosted in TAR UC)

Trusted IDS Connector

• Data Usage

Control

• Audit Logging

IDS Clearing House (Hosted in TAR UC)

Pilot Run with Industrial partner IDS Identity and Trust Management support

2019 Q3 2019 Q4 2020 Q1 2020 Q2 2020 Q3 2020 Q4 2021 Q1

IDS Implementation Milestones

Domain-specific Vocabulary Creation (based

• n eCl@ss

standard) AAS creation and storage

2018 Q4

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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

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IDS Use Case Example in Industrie 4.0

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Supplier Create Product Types AAS

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Product Types Information to Integrator

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Integrator Create Composite Product AAS

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Product Instances from Supplier to Integrator

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Integrator Monitor the Composite Product

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Supplier Monitor the Product Instances

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Supplier Improved Functionality at Operator

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Digitized Assets in the Supply Chain

Data Consumer Data Consumer Data Provider Data Provider

Asset Asset

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Q & A

Thank You for Your Attention