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  1. DOLCE: A descriptive ontology for linguistic and cognitive engineering1.Stefano Borgo, Roberta Ferrario, Aldo Gangemi, Nicola Guarino, Claudio Masolo, Daniele Porello, Emilio M. Sanfilippo & Laure Vieu - 2022 - Applied ontology 17 (1):45-69.
    dolce, the first top-level ontology to be axiomatized, has remained stable for twenty years and today is broadly used in a variety of domains. dolce is inspired by cognitive and linguistic considerations and aims to model a commonsense view of reality, like the one human beings exploit in everyday life in areas as diverse as socio-technical systems, manufacturing, financial transactions and cultural heritage. dolce clearly lists the ontological choices it is based upon, relies on philosophical principles, is richly formalized, and (...)
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  2.  61
    Technical Artefact Theories: A Comparative Study and a New Empirical Approach.Claudio Masolo & Emilio M. Sanfilippo - 2020 - Review of Philosophy and Psychology 11 (4):831-858.
    Embracing an inter-disciplinary approach grounded on Gärdenfors’ theory of conceptual spaces, we introduce a formal framework to analyse and compare selected theories about technical artefacts present in the literature. Our focus is on design-oriented approaches where both designing and manufacturing activities play a crucial role. Intentional theories, like Kroes’ dual nature thesis, are able to solve disparate problems concerning artefacts but they face both the philosophical challenge of clarifying the ontological nature of intentional properties, and the empirical challenge of testing (...)
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  3.  32
    Ontologies for information entities: State of the art and open challenges.Emilio M. Sanfilippo - 2021 - Applied ontology 16 (2):111-135.
    Information entities are used in ontologies to represent engineering technical specifications, health records, pictures or librarian data about, e.g., narrative fictions, among others. The literature in applied ontology lacks a comparison of the state of the art, and foundational questions on the nature of information entities remain open for research. The purpose of the paper is twofold. First, to compare existing ontologies with both each other and theories proposed in philosophy, semiotics, librarianship, and literary studies in order to understand how (...)
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  4. Design Knowledge Representation: An Ontological Perspective.Emilio M. Sanfilippo, Claudio Masolo & Daniele Porello - 2015 - In Emilio M. Sanfilippo, Claudio Masolo & Daniele Porello (eds.), Proceedings of the 1st Workshop on Artificial Intelligence and Design, {A} workshop of the {XIV} International Conference of the Italian Association for Artificial Intelligence (AI*IA 2015), Ferrara, Italy, September 22, 2015. pp. 41-54.
    We present a preliminary high-level formal theory, grounded on knowledge representation techniques and foundational ontologies, for the uniform and integrated representation of the different kinds of (quali- tative and quantitative) knowledge involved in the designing process. We discuss the conceptual nature of engineering design by individuating and analyzing the involved notions. These notions are then formally charac- terized by extending the DOLCE foundational ontology. Our ultimate purpose is twofold: (i) to contribute to foundational issues of design; and (ii) to support (...)
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  5. Features and Components in Product Models.Emilio M. Sanfilippo, Claudio Masolo, Stefano Borgo & Daniele Porello - 2016 - In Emilio M. Sanfilippo, Claudio Masolo, Stefano Borgo & Daniele Porello (eds.), Formal Ontology in Information Systems - Proceedings of the 9th International Conference, {FOIS} 2016, Annecy, France, July 6-9, 2016. Frontiers in Artificial Intelligence and Applications 283. pp. 227-240.
    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 essen- tial 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 exploita- tion. We study this problem by identifying different interpretations of structure rep- resentations, (...)
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    Formal ontologies in manufacturing.Emilio M. Sanfilippo, Yoshinobu Kitamura & Robert I. M. Young - 2019 - Applied ontology 14 (2):119-125.
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  7. Formal Ontology in Information Systems - Proceedings of the 9th International Conference, {FOIS} 2016, Annecy, France, July 6-9, 2016. Frontiers in Artificial Intelligence and Applications 283.Emilio M. Sanfilippo, Claudio Masolo, Stefano Borgo & Daniele Porello (eds.) - 2016
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  8. Proceedings of the 1st Workshop on Artificial Intelligence and Design, {A} workshop of the {XIV} International Conference of the Italian Association for Artificial Intelligence (AI*IA 2015), Ferrara, Italy, September 22, 2015.Emilio M. Sanfilippo, Claudio Masolo & Daniele Porello (eds.) - 2015
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  9.  18
    Ontological modeling of manufacturing resources.Emilio M. Sanfilippo, Walter Terkaj & Stefano Borgo - 2021 - Applied ontology 16 (1):87-109.
    Standards and ontologies for manufacturing understand resources differently. Because of this heterogeneity, misunderstandings arise concerning the basic features that characterize them. The purpose of the paper is to investigate how to ontologically model resources with the goal of facilitating the development of knowledge representation models for manufacturing. By reviewing the literature, we discuss and compare three approaches for the representation of resources depending on whether they are conceived in connection to either processes, plans or goals. By addressing the advantages and (...)
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