Ontologies and Knowledge Graphs – Corporate IT & R&D

Semantic Data Modelling, Knowledge Graphs

Ontologies and Knowledge Graphs – Corporate IT & R&D

Automotive, Engineering, Digital Innovation

Scania and Traton

Stockholm and Munich

Challenge

Structuring Knowledge

Within Scania’s Corporate IT and R&D organizations, the challenge was to connect large volumes of diverse data across systems, domains, and departments. As digitalization accelerated, the need to link information semantically, ensure data consistency, and enable machine-readable knowledge sharing became critical.

Scania needed a unified approach to represent its product, system, and process knowledge across multiple IT platforms — bridging R&D, operations, and enterprise data while aligning with long-term data governance principles.

Solution

Our Approach: Building Semantic Foundations

Susanne Vejdemo, Ontology Architect at Multiply, played a central role in introducing and expanding the use of ontologies and knowledge graphs within Scania’s Corporate IT and R&D environments.

Working across organizational boundaries, Susanne designed scalable ontology frameworks and demonstrated how semantic technologies could create a shared understanding of data between systems and teams.

Key focus areas included:

· Introducing ontology-driven design, promoting a structured and consistent way to describe and interlink data across systems.

· Integrating ontologies with existing IT landscapes, enabling smoother information exchange and reducing system silos.

· Leveraging knowledge graphs to visualize relationships and dependencies within Scania’s data ecosystems — maximizing reusability and insight generation.

· Embedding data governance principles, ensuring that semantic models align with enterprise data quality, ownership, and lifecycle standards.

· Collaborating across Corporate IT and R&D, translating complex research and engineering data into usable digital knowledge structures.

· Evangelizing best practices, coaching teams and promoting awareness of ontology and semantic data approaches across departments.

Implementation & Execution

Multiply’s structured approach focused on bridging theory and practice — making ontologies and knowledge graphs tangible, usable tools within Scania’s digital ecosystem.

Key achievements included:

· Creating foundational ontology structures supporting product and system knowledge representation.

· Establishing semantic integration principles across data platforms in Corporate IT and R&D.

· Building pilot implementations connecting ontology-based data with existing Scania systems.

· Strengthening cross-department collaboration through workshops, practical demos, and data modeling sessions.

Result

Shared Understanding and Integrations

Key Outcomes:

· Ontology and knowledge graph principles successfully adopted within Corporate IT and R&D.

· Improved semantic consistency and clarity in data integrations.

· Greater cross-functional understanding of complex data relationships.

· Foundation established for scalable, enterprise-wide knowledge modeling.

Future Outlook

Solid Semantic and Knowlege Foundation

With a solid semantic foundation in place, Scania is now positioned to extend ontology and knowledge graph usage across more domains. The initiative lays the groundwork for data-driven decision-making, AI readiness, and cross-domain traceability — ensuring that Scania continues to lead in applying advanced knowledge management to product development and enterprise systems.

Susanne Vejdemo

Ontology Architect