Electronic commerce (e-commerce) has grown significantly since the first online shops appeared. Such a growth is quantifiable not only in terms of users and sales but also in complexity: assets, supply chains, shipment modalities and payment methods, auctions, digital negotiations and blockchains are examples of how e-commerce is evolving in the WEB 3.0 era. As consequence of the growth and spread, the need of realizing trustworthy marketplaces, especially when decentralized technologies are involved, came forward. Semantic Web technologies may play a crucial role in this mission as their adoption by the major online marketplaces evidenced. The GoodRelations ontology is a milestone in this context. However, many limitations prevent GoodRelations from addressing the challenges of the incoming releases of the WEB: indeed, intricate and intertwined relationships among the digital commerce stakeholders are outside the expressive power of GoodRelations. Improvements to ontological representation in the e-commerce realm derive from the Theory of Agents. Among the available models, the behavioristic approach pursued by the Ontology for Agents, Systems, and Integration of Services ( OASIS ) is well suited to addressing emerging challenges, including those posed by Web 3.0. In this contribution, we present an extension of OASIS for the e-commerce domain, aimed at supporting next-generation digital commerce by incorporating features such as supply chain modeling, distributed ledgers, negotiation mechanisms, and auction processes.

Station–city integration cyberspace behaves as an interdisciplinary field of intelligent transportation and smart city, also a representative scenario in the Architecture, Engineering and Construction (AEC) sector. Due to the growing demands in data integration research, the intelligent operation and maintenance (O&M) of the station–city integration cyberspace needs to implement semantic ontology, which is suitable for semantic web construction. To achieve semantic information fusion of multi-source heterogeneous data, and clarify the decision-making role of various types of data on specific operational goals, this article proposed a framework for semantic ontology model construction, based on the deployed sensor network. Specifically, an ontology model for station–city integration cyberspace O&M was constructed, incorporating sensor data mainly from five categories, named structure, environment, crowd flow, emergency events, and energy consumption, respectively. Subsequently, the r d f l i b library in Python was utilized to assign data flow to static semantic models. Furthermore, a semantic web inference engine was generated using decision rules, ultimately completing risk early warning and equipment maintenance for the sensor network. Finally, a case study was conducted for the station–city integration O&M scenario in Shenzhen North Station, and the experimental results demonstrated the applicability and effectiveness, providing robust, intelligent data support for intelligent O&M.

Ontologies enable knowledge sharing and interdisciplinary collaboration by providing standardized, structured vocabularies for diverse communities. While logical axioms are a cornerstone of ontology design, natural language elements such as annotations are equally critical for conveying intended meaning and ensuring consistent term usage. This paper explores how meaning is represented in ontologies and how it can be effectively represented and communicated, addressing challenges such as indeterminacy of reference and meaning holism. To this end, instead of following the conventional approach of beginning with existing ontologies and working toward alignment or modularization, this article proposes a reversal of perspective: Taking the ontological term as the starting point and introducing a new structure, named “ontological unit,” characterized by: A term-centered design; enhanced characterization of both formal and natural language statements; and an operationalizable definition of communicated meaning based on general assertions. By formalizing the meaning of ontological units, this work seeks to enhance the semantic robustness of terms, improving their clarity and accessibility across domains. Furthermore, it may offer a more effective foundation for ontology generation and significantly improve support for key maintenance tasks such as reuse and versioning. This article aims to establish the theoretical groundwork for the proposed approach and to lay the foundations for future applications in applied ontologies.

Dispositions are properties that can manifest under certain conditions. Their manifestations may create new conditions under which further dispositions can manifest. Thus, the manifestation and activation of dispositions have been described as making the world “tick,” like a clock. Representing dispositions is essential for modeling how their bearers change through time and, therefore, for representing events. However, dispositions rarely work alone: in many cases, the changes undergone by some entity are determined by many interacting dispositions. Nevertheless, dispositions are usually characterized by stimulus-manifestation pairs. This kind of definition provides little information regarding what happens when multiple dispositions manifest simultaneously. Even in cases that we can describe with mathematical models, we lack tools to connect the mathematical and ontological models. We propose a method to represent dispositions by associating them with vectors over quality dimensions. These vectors indicate the direction and intensity of the change that a quality will undergo when the disposition manifests. The interaction between distinct dispositions is a function of their vectors. Thus, we are able to connect mathematical modeling of phenomena to an ontology that supports reasoning using inference tools. Finally, we apply our proposal in modeling oil flow inside a reservoir in the petroleum production domain.

Defeasible reasoning is a kind of reasoning where some generalisations may not be valid in all circumstances, that is, general conclusions may fail in some cases. Various formalisms have been developed to model this kind of reasoning, especially characteristic of common-sense contexts. However, it is not easy for a modeller to choose a formalism that is a good fit for a particular domain from an ontological point of view. In this paper, we present a framework for formulating the characteristics of defeasibility and reasoning with exceptions which exploits and incorporates related fields of inquiry, including generics, ceteris paribus laws, and a truthmaking theory for generalisations. The resulting theory allows a grounded comparison of the various formalisms and reveals their ontological commitments. To illustrate and apply this framework, we compare the main systems of non-monotonic logics, showing the differences that may occur from an ontological perspective.

The Joint Ontology Workshops (JOWO) is the flagship venue of the International Association for Ontology and its Applications (IAOA), bringing together workshops that connect the communities of formal and applied ontology with intersecting communities in other fields of knowledge. Since its conception in 2015, JOWO has been held annually, regularly co-locating with the International Conference on Formal Ontology in Information Systems (FOIS). To celebrate its 10th edition, a special edition of the Applied Ontology journal has been organized, welcoming extended versions of papers originally published at JOWO workshops, and with the aim of showcasing the evolutions of high-quality works that originated in this venue. This editorial serves as the preface to the first volume of this two-volume special issue.

We propose an axiomatic ontological framework for both informational templates and the substantial informational entities (named “fillers”) that can comply with such templates. The mereological structure of a filler is provided by its slots, following seminal work by Bennett and the mereology of slots approach by Tarbouriech et al. Templates are composed of placeholders satisfying an extensional mereology. The parthood relation between placeholders is mirrored into the parthood between slots of the fillers compliant with those placeholders, where if a filler x complies with a placeholder a , the relation of mirroring is an isomorphism between a subset of slots of x and the template-parts of a . Some placeholders are mandatory and are mirrored into slots that need to be filled by a non-empty filler, whereas others are optional and are mirrored into slots that can be filled by an empty filler. We discuss mereological sum among placeholders and slots, order considerations, the distinction between empty fillers and empty concretizations (such as spaces or silences), the notion of semantic compliance and applications to clinical documents, relational databases and linguistics.

Foundational ontologies are usually developed in powerful logical languages, while they are often implemented in applications via their formalisations in the Web Ontology language (OWL). These OWL formalisations are in fact approximations of the original theories, to cope with the well-known limited expressivity of OWL. In this paper, we propose a novel modular approach to the OWL rendering of the Descriptive Ontology for Linguistic and Cognitive Engineering ( dolce ). We start presenting two fundamental modules of dolce in OWL 2: (i) a core module of dolce (termed ‘DOLCEbasic OWL ’), which provides the main taxonomy and the binary relations of the foundational ontology and (ii) an extension (termed ‘DOLCEnaryRel OWL ’) to deal with the n -ary relations of dolce (for n > 2 ). We examine how the OWL rendering requires approaching delicate and truly ontological issues to motivate the choices made to circumvent the limited expressivity. To provide a minimal justification of our approximation, we establish that the OWL 2 versions are compatible with the original version of dolce by offering an automated proof that the first-order version of dolce entails the translations into first-order logic of the OWL 2 modules. Other adequacy criteria are then discussed. Finally, we illustrate the functioning of our rendering by means of examples. We conclude by discussing a number of other modules to cope with other core concepts and specific domains.

Research in the Digital Humanities requires computer systems that can document and analyze interpretations of creative works, such as literary texts. These systems are designed to provide access to existing interpretations and identify their similarities and differences. To this end, we propose an approach to formally representing interpretations. In particular, we develop an ontology of observations aimed at capturing, through what we call observational vocabularies, what interpreters claim about the texts that they interpret. We distinguish between different types of observations, in particular, basic observations, which represent specific and domain-dependent claims (e.g., regarding the analysis of literary characters’ traits), and observations such as assertion, denial, support, and defeat to document more nuanced claims. We also introduce formal mechanisms that can be used to analyze particular (sets of) observations, texts, and so on. Throughout the article, we illustrate the discussion with examples from literary studies.

Ontologies are a means to codify our knowledge of existence, representing concepts and their relationships. Applied ontology is the use of ontological approaches for practical purposes, including representing and solving problems within specific domains. This article retrospectively reflects on the applied ontology aspects of developing a computer-aided security modelling tool. It discusses the evolution of the ontology that underpins the modelling tool, in accordance with the incremental development of tool features to address new domain problems and feedback from concrete applications. The reflection is supported by a new OntoUML interpretation of the tool's evolving metamodel, which originally codified domain knowledge and practices. The retrospective analysis of the iterative and incremental tool development demonstrates the applied ontology aspects of a metamodel-driven development approach and provides empirical groundings of ontological unpacking, multi-level modelling, and a newly suggested technique: ontological packing. Making metamodel evolution aspects explicit highlights the significant role of metamodels and other applied ontology techniques in system development, and it suggests that they could be more systematically used for development-related decision making. A comparison with state-of-the-art ontologies further highlights aspects of applied ontology design and validation attributed to the metamodel-driven development approach.