Towards a Digital Twin Environment for Asset Information Management and Workplace Management practices in large organizations

Workplace Management (WM) encompasses strategic decision-making processes aimed at optimizing office space utilization and personnel allocation. These processes are typically complex, requiring coordination among multiple stakeholders and integration of diverse datasets spanning Human Resources, Facility Management, and Information and Communication Technologies. Despite its critical role, WM is often hindered by fragmented data silos, heterogeneous information formats, and a lack of semantic interoperability. These systemic challenges impair data accessibility and limit the ability to support effective, evidence-based decisions. This thesis addresses these challenges by envisioning a Digital Twin Environment (DTE) tailored for WM. Grounded in principles from Systems Engineering (SE), the built environment (BE), and information systems, it leverages Ontology Engineering to formalize domain knowledge and ensure semantic consistency across heterogeneous data sources. Prodromic to the achievement o f a DTE, a system, referred to as the Workplace Asset Management System (WAMS), is proposed. Its objective is to guide the use and adoption of Knowledge Graph (KG)-based systems for Asset Management activities within the BE, integrating spatial, organizational, and resource-related data, to finally enable coherent data access and advanced reasoning capabilities. The definition of a system architecture encompasses both backend services and a web-based user interface. A software development process adopts a Django framework in Python programming language and requires the definition of object-based logical models, along with bidirectional data mapping functions, compatible with the RDF schema employed by the graph database, using SPARQL query language. The system architecture is designed to meet the functional needs of both technical and managerial users. Technical personnel are enabled to insert and maintain data on physical spaces, equipment, and personnel, while managerial users benefit from interactive visualizations, semantic queries, and decision-support tools for employee allocation and space planning. A real-world case study, identified in the organizational units of the University of Turin occupying the administrative premises of Palazzo degli Stemmi, validates the prototype, demonstrating its usability, functional completeness, and capacity to streamline WM workflows. By aligning user requirements with Semantic Web technologies and Digital Twin principles, this work advances both theoretical understanding and practical implementation of WM systems. It highlights how KG-based approaches can enhance coordination across domains and support holistic, data-driven planning in organizational environments. The thesis also identifies implementation challenges and proposes future enhancements, to further improve spatial analysis and workplace planning accuracy, and foster Open Innovation in organizational settings.