The deep dive

Explore our papers and strategy statements by our members and affiliated researchers for a deeper understanding of our mission and goals.

Data Spaces Business Models

Position Paper 2024 | Version 1.0

Data Spaces for the Al Act - Analysis of the Standardization Request regarding the European Al Act in the context of Data Spaces

Position Paper 2024 | Version 1.0

Semantic Interoperability in Data Spaces

Position Paper | April 2024

Bridging the Gap Between IDS and Industry 4.0 – Lessons Learned and Recommendations for the Future

Position Paper | Version 1.0 | March 2024

IDSA Rulebook

White Paper | 2023

To The IDSA Rulebook

IDSA Rulebook on GitHub

Interoperability Framework for Energy Data Spaces

Position Paper | Draft Version | October 2023

Reflections on the DGA and Data Intermediaries

Position Paper | October 2023

Data Spaces Landscape – Overview and relations of data spaces initiatives, standards and tools

Position Paper 2023 | Version 1.0

IDS Reference Architecture Model

Version 4.0 | 2022

The IDS Reference Testbed. Key in Development and Certification

Position Paper 2022 | Version 1.0

IDSA Position Paper Data Sovereignty - Requirements Analysis of Manufacturing Use Cases

Data Sovereignty – Requirements Analysis of Manufacturing Use Cases

Position Paper 2022 | Version 1.0

Governance for Data Space Instances – Aspects and Roles for the IDS Stakeholders

Position Paper 2021 | Version 0.1

Usage Control in the International Data Spaces

Position Paper 2021 | Version 3.0

Data Sovereignty – Critical Success Factor for the Manufacturing Industry

Position Paper 2021 | Version 1.0

Specification: IDS Meta Data Broker

White Paper 2020 | Version 1.0

Criteria Catalogue: Components-Broker

White Paper 2020 | Version 1.0

Specification: IDS Clearing House

White Paper 2020 | Version 1.0

Criteria Catalogue: Components-Connector

White Paper 2021 | Version 2.1.2

Criteria Catalogue: Operational Environments

White Paper 2020 | Version 1.0

Framework for the IDS Certification Scheme

Strategy Paper 2018 | Version 2.0

MONDRAGON ASSEMBLY EGOKIA

MONDRAGON ASSEMBLY - an international firm specializing in the development of automatization and assembly solutions for various sectors. It operates 6 production plants around the world and is part of the largest cooperative group in the world | IKERLAN Technical research center and member of IDSA

CHALLENGE:

EGOKIA solution allows collaborative learning and knowledge sharing between geographically distributed plants, integrating headquarters in Basque Country and domain experts. Thanks to the data space, data, and AI assets can be securely shared throughout different corporate sites and a new knowledge-based economy emerges.

SUCCESS:

Deploys an architecture based on IDSA connectors, linking Mondragon Assembly’s data and AI platforms from different corporate sites. With this new reliable data space, we extend the lifecycle of artificial intelligence models, enhance their capabilities, and facilitate trusted access and use of its assets by EGOKIA participants.

BENEFITS:

NEW BUSINESS MODEL: A new business model based on AI services and a knowledge-based economy. RELIABLE AI SOLUTIONS: A "standardized", flexible, and secure solution to break data silos to share and complete AI assets and processes between trusted organizations and production plants. Measurable benefits can be listed as: Up to 30% quality on models thanks to the application of federated learning techniques, reduce inversion and time to market on IA-based solutions or lower communications loads. STANDARIZED DATA SPACE – The organization is ready to take part in the knowledge economy with other entities, domain experts, and technology providers.

COMPONENTS:

Data Space connectors 8.0.2 Metada Broker 5.0.3 Identity Provider 1.6.0

Increased visibility of order delivery process

VTT | Wärtsilä | Uwira

CHALLENGE:

The use case revolves around expediting and enhancing transparency between a focal company of a manufacturing ecosystem (OEM) and its supplier in their production order management processes. The existing communication methods have proven inadequate in facilitating efficient and adaptable exchanges between the two entities. By facilitating transparency and fostering a more seamless integration between the IT systems of both companies, the management of product orders can be streamlined, resulting in heightened efficiency and a reduction in errors.

SUCCESS:

The objective is to facilitate a reliable and seamless flow of data between the OEM and its supplier by establishing a dedicated data space. The developed solution will be seamlessly integrated with pre-existing IT infrastructures of both companies and the solution is grounded in the framework of the IDS reference architecture.

The OEM can selectively disclose data from their production environment to the supplier without the fear of data leakages. Respectively, the supplier receives only the data that are essential for them and there is no need to locally extract meaningful insights and valuable information from big data sets.

BENEFITS:

The established data space solution has the potential to significantly enhance transparency between the OEM and the supplier. This gives rise to several potential benefits, including:
Effective Communication: Transparent communication helps in conveying accurate information about product specifications, requirements, changes, and timelines.
Risk Management: Sharing information about potential risks, such as changes in demand or design modifications, allows suppliers to proactively address these issues. Furthermore, in times of disruptions, such as supply shortages or unexpected market shifts, transparent communication helps both parties respond more effectively.
Cost Efficiency: Transparent communication allows both parties to work together to find cost-effective solutions.

COMPONENTS:

IDS connectors - serve as the communication interface linking the two companies and their existing IT systems. With IDS connectors, a data provider can define the rules and conditions (usage policies) under which data are shared with a data consumer.
DAPS - enables connectors to authenticate themselves using X.509 certificates. After successful authentication, the DAPS issues OAuth2 access tokens for connectors, who need these tokens to access the services and data of other connectors.
Metadata Broker— stores information about the data end-points offered by the participants. The broker provides a query interface for connectors and can hence be considered as the search engine in this use case.

LEARN MORE:

Show Use Case