The transition from a linear economic model to a circular model is crucial, due to the limited resources of our planet. The Circular Economy (CE) aims to maintain material continuity through the cycle of production, consumption and recycling. The Digital Product Passport (DPP) is 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 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 ensuring increased data quality. Despite existing research on DPPs, a comprehensive tool for technically representing DPPs is missing, making this paper a pioneering exploration into the modelling of a DPP core ontology.

The Circular Economy (CE) domain is increasingly leveraging ontologies to represent domain knowledge for data sharing and exchange. Several CE-related ontologies have been developed to model CE-specific knowledge for circular value networks. However, CE knowledge representation also relies heavily on existing ontologies from related domains, such as materials and manufacturing, due to the cross-industry nature of CE. Aligning CE-related ontologies is a key step toward enhancing interoperability and reusability. In this paper, we present alignment results and discussions on CE-related ontologies based on an extended ontology survey within the scope of the Onto-DESIDE project.

Units of measure are central in all areas of science and technology. There are several ontologicalframeworks aiming to improve interoperability and precision in digital data exchange of quantitiesinvolving units. We introduce an ontology that specifically targets challenges for handling units acrossdatabases of computational and experimental data from various sources. The ontology is created usingdefinition files from the community-driven OPTIMADE standard for a common API for materialsdatabases. The resulting ontology allows addressing data integration challenges encountered in thateffort, including (i) referencing both specific and more general instances of units that have changedover time; (ii) the use of unit systems to define short domain-relevant identifiers for a collection of unitsthat make sense within a specific subdomain, rather than having to adopt globally standardized namingschemes; (iii) specifications of relationships between units that enables tools to convert between them;and (iv) units not part of the International System of Units (SI) can be represented without defining themin SI units or using SI system conventions. This paper provides a brief survey of existing ontologiesfor units of measure and then presents the design and discuss features of an ontology based on theOPTIMADE unit definitions.

In different sports fields, collecting play-by-play data has become significant for data analysis, as seen in sports like baseball, basketball, ice hockey and football. Badminton remains a relatively new domain in terms of systematically collecting game play data (i.e., play-by-play or shot-by-shot) with only some recently published datasets online. While the game play data provides some detailed information about matches, it lacks rich semantics for complex information retrieval and data analysis. Consequently, the data cannot be used for applications where semantics are needed. This paper introduces a badminton domain ontology - BadmintONTO, along with its illustrative usages to showcase the capability of this ontology to represent basic domain knowledge and to annotate play-by-play data. 

The Circular Economy (CE) domain has a nature of connecting and linking multiple cross-industry domains (e.g., manufacturing and materials) aiming to reduce value loss and avoid waste by building and implementing CE models (i.e., circular value networks) across these domains. In recent years, ontologies have been recognized as a key for representing domain knowledge in CE. Both CE-specific and domain-specific ontologies exist, with more continuously emerging. Matching CE-related ontologies can generate alignments that enhance the interoperability and reusability of such ontologies.In this paper, we present our initial efforts and findings in matching ontologies within the CE domain.