One could argue that fictional characters in literary texts, films, television series, and other artistic works become part of our lives. Although they do not possess spatio-temporal existence like flesh-and-blood individuals, their presence can be traced in our cities through museums—such as the Sherlock Holmes Museum in London or Juliet’s house in Verona—or through statues like the Rocky Balboa statue in Philadelphia. In this paper, we explore ontology-based approaches to representing and comparing interpretations of literary characters. In particular, we introduce and discuss several similarity measures between interpreted literary characters, and discuss conditions for the identification of characters across heterogeneous interpretations.

Research in Digital Humanities calls for computational systems to document, compare, and analyze interpretations of cultural artifacts such as literary texts. These systems are intended to support scholars, critics, and students by facilitating access to existing analyses of texts, identifying similarities and divergences between interpretations, and more. We propose an approach for documenting interpretations of literary characters, grounded in the empirical practices of literary interpretation to align closely with experts’ methods. To achieve this, we remain neutral regarding the ontological status of characters, instead relying on formal approaches based on linguistics. We demonstrate how our approach can analyze relations between names of fictional characters across texts and authors, bridging discussions in analytic philosophy about identity with the interests of literary scholars.

The representation of manufacturing resources plays a fundamental role in engineering modeling scenarios. These are characterized in a number of ways by taking into account their physical properties, capabilities, roles, etc. In this context, notions like capability, process, and functionality are used in different manners, hence it is not clear how different approaches can interoperate. The aim of this work is to propose an ontology for manufacturing that represents assets involved in manufacturing operations, their characteristics and relations, as defined in a list of requirements. This contribution stems from the existing literature and, in particular, integrates recent works related to the modeling of manufacturing resources, engineering functions, and capabilities. The ontology takes advantage of DOLCE as foundational ontological framework. The relevant axioms are presented and commented on with respect to the identified requirements.

In many application domains, it is common to talk not only about the entities populating that domain, but also about statements (aka claims) that are expressed about those very entities. This is particularly the case in the Humanities, e.g., when scholars express their critical statements about paintings, literary texts, musical works, etc. The ontological modeling of such claims is challenging for various reasons, e.g., because one needs to capture their subjective but also public dimension, because scholars may express contrasting statements about the same phenomena, or because the argumentative logic of scholarly reasoning does not squarely fit into the methods of mathematical logic. Building on previous work on the treatment of observations and being driven by concrete case studies, we propose the first steps for an ontology to document scholarly statements and to trace critical debates in literary studies.

The CIDOC-CRM ontology is a standard for cultural heritage data modeling. Despite its large exploitation, the ontology is primarily maintained in a semi-formal notation, which makes it difficult to homogeneously exploit it in digital environments. In addition, the ontology consists of several classes and relations, whereas one sometimes wishes to reuse it but only partially. The purpose of the paper is to contribute to the use of CIDOC by strengthening its foundations. On the basis of formal ontology theories, we propose a first analysis of the ontology to enhance its conceptual structure. We also present a preliminary modularization of CIDOC aimed at enhancing both its formalization and usage.

Engineers distinguish between nominal and actual qualities, a dichotomy that is fundamental to guarantee that physical objects satisfy design requirements. Computational ontologies are broadly exploited across engineering domains, even though they do not attempt at making explicit the intended semantic of the two notions. The purpose of the paper is to present a foundational analysis of nominal and actual qualities to support their robust specification for knowledge representation. Instead of presenting an ontology, we discuss various modeling alternatives on which users can rely to develop their ontologies.

Product structures are represented in engineering models by depicting and linking components, features and assemblies. Their understanding requires knowledge of both design and manufacturing practices, and yet further contextual reasoning is needed to read them correctly. Since these representations are essential to the engineering activities, the lack of a clear and explicit semantics of these models hampers the use of information systems for their assessment and exploitation. We study this problem by identifying different interpretations of structure representations, and then discuss the formal properties that a suitable language needs for representing components, features and combinations of these. We show that the representation of components and features require a non-standard mereology.

Feature-based product modeling is the leading approach for the integrated representation of engineering product data. On the one side, this approach has stimulated the development of formal models and vocabularies, data standards and computational ontologies. On the other side, the current ways to model features are considered problematic since it lacks a principled and uniform methodology for feature representation. This paper reviews the state of art of feature-based modeling approaches by concentrating on how features are conceptualized. It points out the drawbacks of current approaches and proposes a high-level ontology-based perspective to harmonize the definition of feature.

In the context of business process modelling, the Business Process Model and Notation (BPMN) is a de-facto standard with more than 70 commercial tools that currently support its use. Amongst its main modelling constructs, BPMN includes activities and events. However, the focus of the standard is on providing an intuitive graphical language, rather than formal semantics specifications. This results in semantic ambiguities regarding the interpretation of its modelling constructs. We investigate whether the main building blocks of BPMN commit to an ontological theory of the domain entities at hand, eventually clarifying this commitment by the approach of ontological analysis.