Data Sharing: Economic Value Across the Automotive Supply Chain, Built on Trust

Transcript

1. Data Sharing: Economic Value Across the Automotive Supply Chain, Built on Trust Mario Holesch, IDSA
2. cess ple al ful men stan data tary dar spa initi d ces ativ for Neu hav es trust ... is collaborative, dynamic, inclusive tral, e to wor non alre crea thy -pr ady te a data ofit, bee full shar true n stac ing glob built kwhil for al bas data e orga ed shar reali niza on ing zing tion our with data con trust sov cept on erei s fede gnty (Cat rate and ena d pro -X, infra vide Mo stru con bilit ctur sens y es us International Data Spaces Association 2
3. 80% of industrial data is never used *projected figures 2025 (European Commission) AI calls for the biggest amount of data possible Companies could use this data to add value, but they don’t Data Spaces with Data Sovereignty built in can fuel AI and make data economy happen. 3
4. The data economy involves many players Evolution of data sharing Market Adoption Bilateral data exchange 1:1 4 Closed community data sharing few-to-few Decentralized and dynamic data ecosystem: many-to-many
5. Companies want to link data Without regret Interoperability Data exchange “Sharing Economy” Data Centric Services Data Sovereignty Data ownership Data security Data value 5 is the ability of a natural or legal person to exclusively and sovereignly decide concerning the usage of data as an economic asset.
6. USAGE CONTROL IS ESSENTIAL FOR DATA ECONOMY WHEN REGARDING DATA AS AN ECONOMIC ASSET www.internationaldataspaces.org
7. The data space enables trusted data sharing, thus creates added value Observabilit y Da catalo ta gues D Data parti space cipan t valid ate iss ue Da sha ta ring contr acts Da sha ta ring contr acts S Data P Space Conn ector Data space Da catalo ta gues Trusted data sharing enabled by the Data Environment trusted Space Conn dataenabling space data sharing between participating parties, based on an agreed governance framework, alongStandar with an agreed set of policies, semantic ds, models, standardizedprofiles protocols, processes, and , vocabul facilitating services Decenary tralized identifi ers & claims D S P Data space partic ipant ector Data space governance authority valid ate iss ue Role provided by one or more parties that establishes, governs, manages and enforces the technical policies and business rules of a data space.
8. The need for Dataspace Protocol Ensuring data space interoperability Control Plane (one standard procedure to negotiate data sharing) Promotes seamless technical interoperability, while addressing certain aspects of semantic interoperability. Enables standardized data exchange across different data space instances. Data Plane (several possible for Provides flexibility and scalability through the separation of control plane and data plane.
9. The magic triangle IDSA as reliable base for data spaces IDS Reference Architecture − Guarantee interoperability in data spaces and between data spaces − Holistic governance to run data spaces − Reliable foundation for commercial offerings (including clear lifecycle, change management, versioning) − Ensure trust in data spaces Blueprint for data spaces with detailed specifications 1 IDSA How to implement IDS Rulebook in the real world TRUST 1 Portfolio of open-source building blocks Bring IDS in commercial set-ups 9 1 Certification 3rd party conformity Scheme allows for an informed decision about the trustworthiness of partners and components in a data space
10. How to create value in the automotive sector?
11. Data Space Accelerator A publicly funded study to lower the entry barriers into Catena-X DSA www.data-space-accelerator.com V 1.0
12. Why getting started takes effort Three structural realities of joining a data space DSA Joining a Data Space takes some effort Participation requires upfront investment Benefits scale at ecosystem level Data spaces offer significant benefits. Yet, understanding requirements, roles and processes requires learning and orientation. Time, internal resources, and initial setup effort are needed before companies become operational in a data space. Efficiency gains and economic benefits increase as more companies participate, making contributions essential to reaching a critical mass. www.data-space-accelerator.com 12
13. The Data Space Accelerator Study … examines the productive adoption of industrial data spaces using Catena-X as the example. The goal is to derive practically usable results to accelerate onboarding, use case implementation and value realisation. DSA www.data-space-accelerator.com/en/study 13
14. What the study delivers Purpose & output Adoption Gap Diagnosis Readiness gaps and their root causes, mapped along the full data value chain — symptoms separated from causes. High-Probability Adoption Profiles Which company types, use cases and context conditions lead to faster productive participation. Targeted Interventions Evidence-based levers replacing generic onboarding — actionable for Catena-X and other data spaces. DSA www.data-space-accelerator.com/en/study 14
15. Data Space Accelerator Study Purpose and Outputs The Data Space Accelerator is a study funded by the German Ministry for Economic Affairs and Energy (BMWE) and coordinated by the International Data Spaces Association (IDSA). What the study delivers: o Empirical evidence on economic and organizational benefits of data sharing. Public Funds >€ 20 M. 15k or 30k € o Actionable recommendations to strengthen digital readiness. IDSA Study Period 2026 Catena-X Cofinity-X o Case‑based insights from multiple use cases. Notice: For participants based outside Germany, the remuneration amount is recalculated using a purchasing power index. Details can be found in the program tender documents. DSA www.data-space-accelerator.com 4
16. Who the Program is for Suppliers not yet active in Catena-X Primarily small and mid-sized – Tier 1, 2, 3, n | larger companies also welcome Automotive and adjacent industries (e.g. mechanical engineering) DSA Joining in 2026 Use case commitment Study participation Catena-X onboarding planned for this year at least 1 concrete use case deployable in daily operations Accompanying survey on effort and value created www.data-space-accelerator.com 16
17. What’s in it for me? What participation means in practice Easily join Catena‑X: Start with a simple, predefined use case that enables meaningful participation in a data space. Guided Onboarding: No prior data space experience is required. Onboarding and use‑case implementation can optionally be supported by certified partners. Remuneration: Receive remuneration based on verified results. Remuneration is paid after successful onboarding and proven productive data sharing. DSA www.data-space-accelerator.com 5
18. Choose Your Path Choice based on your available capacity and ambition A B Recommended Basic Path (Lot 1) Advanced Path (Lot 2) Remuneration of Remuneration of EUR 15,000 (net plus VAT) EUR 30,000 (net plus VAT) > Data space onboarding > Data space onboarding > Use case: Company Certificate Management > Use case: Company Certificate Management > Baseline questionnaire > Baseline questionnaire > Follow-up questionnaire > Follow-up questionnaire + Additional Catena-X use case DSA Notice: For participants based outside Germany, the remuneration amount is recalculated using a purchasing power index. Details can www.data-space-accelerator.com Explore more use cases at www.cofinity-x.com 18
19. Program Partners Strong partners for your data space success DSA International Data Spaces e. V. Catena-X Automotive Network e. V. Cofinity-X GmbH Program organizer driving the vision of sovereign data sharing across industries and enabling trusted data ecosystems worldwide. Governance body of the Catena-X data space, establishing standards and rules for secure, interoperable data exchange in the automotive industry. Secure and trusted data space operating company, providing the technical infrastructure to connect and exchange data within the Catena-X ecosystem. www.data-space-accelerator.com 19
20. Your first data exchange starts here. DSA Find in the FAQ section answers to the most important questions about the program. www.data-space-accelerator.com V 1.0
21. A decade of pionieeri ng. A future of impact. 21
22. Two surveys, one storyline The measurement The participation is measured before and after onboarding. Comparing the two waves lets the study show genuine organizational change — not just differences between respondents. 1 DSA 2 Setup survey (baseline) Exit survey (follow-up) Captures the starting point: business innovation, data strategy & governance, data usage & quality, data products, internal/external/data space exchange, IT landscape, and Catena-X readiness. After the first productive data exchange: measures change in readiness, usage intensity, organizational adaptation, and the value experienced by the company. www.data-space-accelerator.com/en/study 22
23. Data sovereignty is about maintaining control about your data Balancing control and generation of value Please be aware: IDS-Connector are a subset of Data Connectors A Data Owner or a Data Subject wants to stay in control on access to their data and the usage of the data at the data consumer and during usage or storage of data in a Service Ecosystem. 23 Check the monthly Data Connector Report: https://internationaldataspaces.org/data-connector-report/
24. There is a continuum of data sovereignty approaches Higher Data Sovereignty Less complexity and lower entry barriers Data Use Case Focus • Functionality Usage Contracts Trust Mechanism & Certification Standardization 24 2. Traceability 1. Interoperability • • • • Definition, exchange and interpretation of data usage conditions Specification of syntax and semantics of usage conditions Identity Management Secure Data Transfer Interoperability test against Testbed or Self Assessment (Level 1/1) • Standardized Interoperability • • • • • Contract agreements for usage conditions Proof of delivery and receipt Identity Management Secure Data Transfer Certification Trust Level 1 and Assurance Level 2 • Standardized Interoperability 3. Enforcement • • • • • Software enforcement of usage conditions in data consumer connector Proof of enforcement Identity Management Secure Data Transfer Certification Trust Level 2, Assurance Level 2 or 3 • Standardized Interoperability 4. Hardware Anchor • • • • • • Tamper protection for connector software Enables IoT and location-based applications Identity Management Secure Data Transfer Remote Attestation (requires TPM or similar) Certification Trust Level 3 and Assurance Level 2 or 3 • Standardized Interoperability