This research integrates a work system framework with ontology-based meta-modeling to address knowledge silos and fragmented information in enterprises.

Applying a design science research methodology, this thesis bridges the gap between human- and machine-interpretable data, facilitating knowledge sharing and management. Key concepts include the integration of the metamodel created based on a business scenario and work system framework (WSF), creating a dynamic and adaptable knowledge management system. Integration should strengthen the collaborative environment for continuous improvement.

This thesis has five main contributions, one of which is the development of a meta-model enriched with 12 new elements based on expert interviews and literature findings, including the integration of work system elements to support a transition to a cloud-based environment and successful testing queries related to strategic alignment and operational flow. Additionally, this study emphasizes the goal of better governance through improved knowledge management practices. This study highlights both the benefits and challenges of implementing an ontology-based work system for knowledge management and suggests continuous validation and future research for further refinement, adaptability, and enhanced governance.