The Circular Economy (CE) aims to reduce value loss and avoid waste by extending the life of products, compo-nents, and materials, applying various CE strategies—R-strategies, e.g., reuse, recycling, etc. Our study targetsthe construction industry, and specifically flat glass, which is infinitely recyclable, but today virtually all glassends up as landfill. One key enabler of CE is digitalisation, allowing data to flow along with the products andmaterials themselves. However, scaling the CE digitalisation requires semantic interoperability, decentralizeddata sharing, collaboration, and automation of parts of the value chain interactions. In this in-use paper wedemonstrate a solution for supporting information flows of flat glass, based on the application of semantictechnologies. In particular, we focus on ontologies to describe the value chain data about flat glass, and designontologies to be used for building inventory, R-strategy selection, and potentially eventually automating parts ofthe value network setup and execution. The ontologies have so far been applied to generate a building inventoryuser interface for inventory applications, to annotate building inventory data, and to semi-automatically makeR-strategy decisions in a collaboration between a flat glass manufacturer and a recycling company, as well as totrain building inventory experts in national training events in Sweden.

As we live in a world of limited resources, the transition from a linear economic model to a circular model is crucial. The Circular Economy (CE) paradigm aims to maintain material continuity through the cycle of production, consumption and recycling. The Digital Product Passport (DPP) is currently recognised as a critical instrument for advancing CE, serving as a comprehensive digital repository for product lifecycle information. The DPP paradigm fosters transparency and traceability. However, so far there is no agreed-upon standard for technically representing and expressing DPPs. This paper aims to provide a comprehensive analysis of the requirements of a general (cross-sectoral) DPP, and to discuss the representation of a core DPP model. We propose to express this in the form of an ontology network, i.e., a formal model serving as a “translation layer” from raw data to interpreted information, along with SHACL shapes for increased data quality and validation. Despite existing research on DPPs, a comprehensive tool enabling this transition into using DPPs is yet to be developed, making this paper a pioneering exploration into the modelling of a DPP core ontology.