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Digital Sovereignty for Collaborative AI Engineering: A Survey
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science. (SDS)ORCID iD: 0000-0001-6895-4503
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science. (SDS)ORCID iD: 0000-0003-4814-4428
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science. (SDS)ORCID iD: 0000-0003-4071-4596
Oslo Metropolitan University. (SDS)ORCID iD: 0000-0002-5235-5335
2025 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 13, p. 216438-216465Article in journal (Refereed) Published
Abstract [en]

Collaborative AI engineering is a paradigm that enables multiple stakeholders to maintain AI pipelines by exchanging artifacts, such as data, models, and software packages. It is a cost-efficient engineering process that accelerates the development of AI applications, specifically for small and medium-sized enterprises (SMEs). However, AI artifacts are often associated with inherent intellectual property (IP) or sensitive information, which hinders collaboration due to a lack of trust among stakeholders. Digital sovereignty is viewed as an ideal state where artifact owners maintain full control over their assets, such as making key decisions regarding access, storage, and interoperability. Thus, it is postulated that implementing digital sovereignty mechanisms in multi-stakeholder information systems can address the trust gap and promote collaboration. This work addresses this gap by conducting a systematic review of the literature on digital sovereignty for collaborative AI engineering. The main contributions of this work include: i) mapping digital sovereignty definitions and requirements within the context of collaborative AI engineering, ii) identifying existing technologies and concepts for implementing sovereignty features in AI engineering, and iii) analyzing existing collaborative AI platforms such as data marketplaces, data spaces, and GAIA-X. This analysis highlights their sovereignty requirements, solutions, benefits, and implementation challenges. In addition, this work iv) identifies research gaps in data pricing, confidentiality, and interoperability, and proposes future directions to enhance digital sovereignty in collaborative AI ecosystems. 

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2025. Vol. 13, p. 216438-216465
Keywords [en]
AI marketplaces, collaborative AI engineering, data marketplaces, data sovereignty, Digital sovereignty
National Category
Information Systems Artificial Intelligence
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:bth-27711DOI: 10.1109/ACCESS.2025.3647085ISI: 001652010400039Scopus ID: 2-s2.0-105026443105OAI: oai:DiVA.org:bth-27711DiVA, id: diva2:1951325
Projects
dAIEDGE A network of excellence for distributed, trustworthy, efficient and scalable AI at the Edge
Funder
EU, Horizon Europe, 101120726Available from: 2025-04-10 Created: 2025-04-10 Last updated: 2026-01-16Bibliographically approved
In thesis
1. Digital Sovereignty for Collaborative AI Engineering
Open this publication in new window or tab >>Digital Sovereignty for Collaborative AI Engineering
2025 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

In Information Systems, implementing digital sovereignty is essential for improving transparency and establishing trust among stakeholders. This need for digital sovereignty is more prevalent in crowdsourcing platforms, where the stakeholders are often unknown to each other. AI marketplaces belong to the category of crowdsourcing information systems, where individuals and organizations collaborate to share various AI artifacts with one another. These marketplaces act as platforms that enable artifact exchange, thus accelerating the AI application development process through a multi-stakeholder approach to collaborative AI engineering. This work, investigates techniques for implementing digital sovereignty to promote collaboration among the stakeholders.

Digital sovereignty thrives by empowering true owners with control and the ability to make independent decisions over their digital footprint. Depending on the application context, the type of control and the decision-makers change accordingly. For governments, digital sovereignty means the ability to manage citizens’ personal data and ensure data residency within a political region. For individual technology users, digital sovereignty refers to the ability to manage and control the interoperability of personal data across similar platforms. Nevertheless, digital sovereignty focuses on transferring control to the true owner by eliminating intermediaries or centralized organizations.

The scope of this work lies in achieving digital sovereignty for marketplace platforms that operate in the context of exchanging data and other AI software artifacts. The Horizon 2020 projects, BonsApps and dAIEdge,  provide a functional crowdsourcing AI marketplace with beta stakeholders, which also serves as a source for gathering requirements and validating concepts. The main contributions of this work are translating digital sovereignty definitions and requirements into the context of collaborative AI, as well as designing and implementing technical solutions to empower stakeholders of the underlying information system with digital sovereignty over their digital assets.

Place, publisher, year, edition, pages
Karlskrona: Blekinge Tekniska Högskola, 2025. p. 140
Series
Blekinge Institute of Technology Licentiate Dissertation Series, ISSN 1650-2140 ; 2025:03
Keywords
Digital Sovereignty, Collaborative AI Engineering, Data Sovereignty, Data Marketplaces, AI Marketplaces
National Category
Computer and Information Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:bth-27712 (URN)978-91-7295-497-7 (ISBN)
Presentation
2025-05-28, J1630, BTH, Valhallavägen 1, Karlskrona, 09:00 (English)
Opponent
Supervisors
Funder
EU, Horizon 2020, 101120726
Available from: 2025-04-11 Created: 2025-04-10 Last updated: 2025-09-30Bibliographically approved

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Daliparthi, Venkata Satya Sai AjayTutschku, KurtKebande, Victor R.

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