Building trust in Industry Data Spaces: The key to unlocking the full potential of Generative AI and industrial innovation
In the rapidly evolving landscape of Artificial Intelligence and generative AI, organizations, ranging from large corporations to small and medium-sized enterprises, are facing significant opportunities and challenges in leveraging industrial data.
In the industrial world, there are many barriers to accessing industrial data, since these data are often highly sensitive, fragmented across various companies, shop floors, countries, locked in silos within an organization, stored in different formats, and proprietary in nature. Relying solely on open data is not sufficient. As a matter of fact, industrial data are hard to find, and even harder to share. Companies are reluctant to share their data, with fears such as losing competitive advantage due to the data going to competition, and/or violating confidentiality agreements.
So, here are some fundamental questions that need to be addressed:
- How to build trust in data exchanges and data sharing?
- What does trust mean exactly? Trust in the data supplier, in the data acquirer, in the technology that will support the data transaction, ...
- How to ensure that access and usage of this data is fair and compliant? i.e. respecting the terms agreed upon between the participants in the exchange, and complying with regulations.
- How to stimulate the market to share more data?
While building trust is fundamental, next is to build Interoperability. This is where Industry Data Spaces come into play.
What’s an Industry Data Space
An Industry Data Space brings together business partners from a specific sector, industry or value chain. The Industry Data Space participants exchange data products and collaborate in order to improve operational and business efficiency. The Industry Data Space is governed by a Data Space Governance Authority (DGSA), also known as the orchestrator, that defines, maintains, and enforces the data space governance framework and manages its day-to-day operations. The Industry Data Space establishes trustworthiness and enables trusted data transactions between data providers and data users.
The purposes of an Industry Data Space can be manifold, including for example:
- CO2 and CSR achievements: Keep track of CO2 footprint in your organization’s value chain, manage CSR objectives and communicate to public stakeholders by exchanging data products with suppliers and partners
- Optimization of operations and customer experience: Foster coordination, improve user experience, develop new products and services by exchanging operations data products with organizations participating in your market
- Supply chain optimization: Cooperate with tier-1 to N suppliers by exchanging, in trust, detailed supply chain information
- Smart cities’ building information modeling acceleration: Improve the management and maintenance of buildings or town infrastructure by sharing data products with stakeholders
- Digital twins efficiency: Boost digital twins performance or the pertinence of territorial/infrastructure digital mappings, by extending the scope and range of data feeding the models
- Sector data control and integration: Facilitate information circulation by fostering trusted data exchanges within your sector or sub-sector, & make sure the value of the data is captured by the ecosystem and benefits all participants.
Trust is the foundation upon which data exchange must be built, and Industry Data Spaces are essential in fostering that trust. Data spaces serve as secure environments where trusted data transactions can happen. They provide the legal, technical, and operational frameworks that allow data providers to share their data confidently, and data users to use it with trust.
Industry Data Spaces are designed not only to create trusted ecosystems for data exchange but also to ensure better interoperability, both within and across different data spaces. This interoperability extends indeed across industries, making it possible for different sectors - manufacturing, logistics, transportation, energy - to exchange data in ways that were previously too complex or too risky.
Powered by Dawex technology, Data4industry-X is an example of Industry Data Space solution designed to foster seamless, secure and useful data impatriation of all shop floors across the world. Actively contributing to the Manufacturing-X initiative, the Data4Industry-X solution is now initiating interoperability with data spaces, such as the International Manufacturing-X Showcase powered by the LNI 4.0 Association demonstrated at Hannover Messe early April. Data4Industry-X promotes the orchestration of federated data spaces which supports Manufacturing-X ambition to create a compelling and sustainable industry ecosystem.
The interoperability of the Data4Industry-X solution with data spaces will reinforce trust between organizations in the ecosystem and bring new business opportunities to industrial organizations. Thanks to the interconnection between data spaces, industrial organizations will gain broader access to data from players from other data spaces, and be able to exchange data with new participants while benefiting from a pre-defined and pre-negotiated contractual framework, resulting from the negotiations managed . With the interconnection of data spaces, the negotiation efforts are managed by the orchestrators of the interconnected data spaces, who can then spread the resulting benefits to their member organizations. To support industrial organization objectives with plants, shop floors and suppliers, spread across the globe with decentralized manufacturing, secure and compliant data exchange has become essential to ensure trusted data transactions and collaboration across the data ecosystem.
Furthermore European regulations, such as the Data Act coming into force on September 12, 2025, and the EU Digital Product Passport, are exposing industrial organizations to new compliance requirements on data flows.
For Industry Data Spaces to thrive and scale, trust and interoperability are essential. Achieving this requires:
- The development and adoption of standards, such as the GaiaX de facto standard
- Future standards including the Harmonized European Standard on Trusted Data Transaction to enable trusted data transactions at scale, making it easier for companies to collaborate while maintaining control over their data, and for different systems and platforms to work together seamlessly.
- Reference architectures and trust frameworks, as those defined by Gaia-X
- Standardized protocols, such as the data space protocol
- Robust, transparent, and enforceable governance mechanisms, ensuring accountability, clarity of roles and responsibilities, dispute resolution, and compliance monitoring across participants
- A semantic hub and the adoption of semantic standards to ensure seamless interoperability inside and between ecosystems
- And the deployment of the right Data Exchange technologies capable of operationalizing trust and interoperability
Trust and innovation go hand in hand. Without trusted data flows and trusted data transactions, high-quality AI cannot exist. However, by building trust, implementing the right technologies - which already exist today - and leveraging current regulatory frameworks, the full potential of industrial data and Generative AI can be unlocked. This is not just an opportunity, it is a necessity for industrial organizations to remain competitive, innovative, and forward-thinking.
Dive into the power of Industry Data Space solution
More about Data4Industry-X
Supported by the French Government France 2030 initiative and the Alliance Industrie du Futur (AIF), Data4Industry-X relies on technological and industrial expertise of Dawex, Schneider Electric, Valeo, CEA-List and Prosyst.
Powered by Dawex Data Exchange technology, the Data4Industry-X delivers the most flexible and advanced data exchange solution, implementing the Gaia-X de facto standard, using the Gaia-X Digital Clearing House compliance services, interfacing with OPC-UA protocol thanks to the Unified Data Collector solution from Prosyst, interfacing with Data Space protocol, supporting Open API formats and Asset Administration Shell data models, and integrating with decentralized connectors such as Eclipse Dataspace Components Connectors. Data4Industry–X also relies on Schneider Electric building blocks on data continuum from the IIoT box to the data space, on the CEA-List technology development towards the decentralization of data spaces, and on Valeo use cases development leveraging data using AI for the forecasting and reduction of CO2 emissions.
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