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arXiv cs.AI / cs.LG / cs.CLpublished ()ingested Kérian Fiter

Involving before Evolving: A Vision for Trustworthy Enterprise Digital Twin Engineering

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AI summary · glm-5.3

Vision paper proposes 'involving before evolving' staged approach for trustworthy enterprise digital twins, validated via an ongoing Michelin prototype.

The paper presents a three-stage vision for enterprise digital twin (EDT) engineering that prioritizes early organizational buy-in before evolving toward federation and full interoperability. The approach combines foundation models for rapid prototyping, an ontological backbone for federated interoperability, and observability tooling to build stakeholder trust. The vision is grounded in an ongoing collaboration with Michelin, where an initial working prototype helped secure stakeholder buy-in.

  • Three-stage paradigm: involve stakeholders via prototype, then federate and interoperate.
  • Combines foundation models, ontology backbone, and observability tooling.
  • Grounded in a real deployment collaboration with Michelin.
Full article115 words · extracted from arxiv.org · click to collapse

Enterprise Digital Twins (EDTs) promise data-driven decision support at organizational scale, but realizing them requires navigating siloed departments, tacit knowledge, and high-stakes decisions with long-horizon consequences. Existing approaches involve domain experts during model development but focus less on early organizational buy-in in EDTs. We present a vision for trustworthy EDT engineering grounded in an `involving before evolving' paradigm: rapidly involving stakeholders through a working prototype before evolving toward federation and full interoperability. Our three-stage approach combines foundation models for rapid prototyping, an ontological backbone for federated interoperability, and observability tooling for stakeholder trust. We ground our vision in an ongoing collaboration with Michelin, a multinational manufacturer, where an initial prototype has helped support stakeholder buy-in.

Text extracted automatically; images, tables and formatting may be missing. Original: https://arxiv.org/abs/2609.13071