On 24 February 2026, DEXPI e.V. contributed to the meeting of the DECHEMA specialist group “Digital Technologies in Engineering, Operations and Services (DTABS)”, held at the DECHEMA headquarters in Frankfurt am Main.
The specialist group focuses on IT methods and systems for capturing and processing process data as well as digital support for basic and detail engineering, project management, commissioning, plant operation, and service. In addition, technological innovations and their impact on the working environment of plant engineering companies and operators are discussed regularly. The group is chaired by Martin Rittmeister (Linde AG) with Dr. Uwe Nowak (BASF SE) serving as deputy chair.
From Engineering Data Exchange to Knowledge Graphs and AI
During the session, Dr. Michael Wiedau, Chairman of the Board of DEXPI e.V., presented the talk:
“From Engineering Exchange to Knowledge Graphs and AI – DEXPI as the semantic backbone of industrial data.”
The presentation positioned DEXPI within the broader evolution of digital transformation in the process industry — from early engineering data exchange challenges toward semantic interoperability, knowledge graphs, and artificial intelligence.
The talk highlighted how historical engineering problems — such as proprietary tool silos, manual data re-entry, and loss of engineering meaning during data exchange — led to the creation of DEXPI as a vendor-neutral information model for structured P&ID data.
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DEXPI as a Semantic Foundation
A central message of the presentation was that DEXPI has always been more than a data exchange format. Its object-oriented information model, explicit relationships between plant objects, and reference data concepts already provide semantic structures that align naturally with ontology-based approaches and standards such as ISO 15926.
These characteristics make DEXPI particularly suitable as a foundation for modern knowledge graph architectures, where:
- engineering objects become graph nodes,
- relationships become edges, and
- properties form structured attributes.
This enables lifecycle-spanning data integration and machine-interpretable plant knowledge.
Enabling Reliable Industrial AI
The presentation further addressed the growing role of artificial intelligence in engineering and operations. While AI enables natural language interaction and automated insights, it requires structured and context-rich data to avoid inconsistencies or hallucinations.
DEXPI was therefore presented as a key enabler connecting:
DEXPI → Knowledge Graphs → Artificial Intelligence
By providing standardized engineering semantics, DEXPI helps transform industrial data into contextualized knowledge that AI systems can reliably interpret and reason upon
Industrial Outlook
Practical use cases discussed included:
- AI-assisted engineering queries
- lifecycle-wide impact and dependency analysis
- digital twin intelligence
- knowledge preservation across projects and generations
The presentation concluded with the perspective that industrial standards are evolving from data exchange mechanisms toward foundational infrastructure for industrial intelligence.
Exchange Across the Digital Engineering Community
The DTABS meeting brought together contributions from industry and academia addressing topics such as predictive maintenance, extended P&ID data usage, Manufacturing-X initiatives, BIM integration, and semantic metadata extraction.
The discussion demonstrated the growing convergence between engineering standards, semantic technologies, and AI-driven applications.
DEXPI e.V. appreciates the opportunity to contribute to this exchange and looks forward to continued collaboration with DECHEMA and the broader digital engineering community.