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  1. Needs and Intentionality.Luca Biccheri, Roberta Ferrario & Daniele Porello - 2020 - In Formal Ontology in Information Systems - Proceedings of the 11th International Conference, {FOIS} 2020, Cancelled / Bozen-Bolzano, Italy, September 14-17, 2020. Frontiers in Artificial Intelligence and Applications 330. pp. 125-139.
    A thorough understanding of what needs are is fundamental for design- ing well-behaved information systems for many social applications and in partic- ular for public services. Talking about needs pervades indeed the jargon of Public Administrations when motivating their service offering. In this paper, we propose an ontological analysis of needs, aiming at a principled disentangling of the differ- ent uses of the term. We leverage philosophical tradition on intentionality, for its rich understanding of mental entities, we compare it with (...)
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  2. A Semantics-Based Common Operational Command System for Multiagency Disaster Response.Linda Elmhadhbi, Mohamed-Hedi Karray, Bernard Archimède, J. Neil Otte & Barry Smith - 2020 - IEEE Transactions on Engineering Management 68:1-15.
    Disaster response is a highly collaborative and critical process that requires the involvement of multiple emergency responders (ERs), ideally working together under a unified command, to enable a rapid and effective operational response. Following the 9/11 and 11/13 terrorist attacks and the devastation of hurricanes Katrina and Rita, it is apparent that inadequate communication and a lack of interoperability among the ERs engaged on-site can adversely affect disaster response efforts. Within this context, we present a scenario-based terrorism case study to (...)
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  3. PROMES: An Ontology‐Based Messaging Service for Semantically Interoperable Information Exchange During Disaster Response.Linda Elmhadhbi, Mohamed‐Hedi Karray, Bernard Archimède, J. Neil Otte & Barry Smith - 2020 - Journal of Contingencies and Crisis Management 28 (3):324-338.
    Disaster response requires the cooperation of multiple emergency responder organizations (EROs). However, after‐action reports relating to large‐scale disasters identity communication difficulties among EROs as a major hindrance to collaboration. On the one hand, the use of two‐radio communication, based on multiple orthogonal frequencies and uneven coverage, has been shown to degrade inter‐organization communication. On the other hand, because they reflect different areas of expertise, EROs use differing terminologies, which are difficult to reconcile. These issues lead to ambiguities, misunderstandings, and inefficient (...)
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  4. Ontologies for Space and Ground Systems.Barry Smith - 2020 - In Ground System Architectures Workshop. Los Angeles, CA: GSAW. pp. 1-3.
    We will survey a range of ontologies relevant to space and ground system domains. The ontologies form part of the Common Core Ontology ecosystem (CCO) developed under the IARPA KDD initiative. We focus specifically on the Space Domain Ontologies, a suite of ontologies to support space situational awareness, including the Spacecraft Mission Ontology, Spacecraft Ontology, Space Event Ontology and Space Object Ontology.
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  5. A Product Life Cycle Ontology for Additive Manufacturing.Munira Mohd Ali, Rahul Rai, J. Neil Otte & Barry Smith - 2019 - Computers in Industry 105:191-203.
    The manufacturing industry is evolving rapidly, becoming more complex, more interconnected, and more geographically distributed. Competitive pressure and diversity of consumer demand are driving manufacturing companies to rely more and more on improved knowledge management practices. As a result, multiple software systems are being created to support the integration of data across the product life cycle. Unfortunately, these systems manifest a low degree of interoperability, and this creates problems, for instance when different enterprises or different branches of an enterprise interact. (...)
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  6. An Ontological Approach to Representing the Product Life Cycle.J. Neil Otte, Dimitris Kiritsi, Munira Mohd Ali, Ruoyu Yang, Binbin Zhang, Ron Rudnicki, Rahul Rai & Barry Smith - 2019 - Applied Ontology 14 (2):1-19.
    The ability to access and share data is key to optimizing and streamlining any industrial production process. Unfortunately, the manufacturing industry is stymied by a lack of interoperability among the systems by which data are produced and managed, and this is true both within and across organizations. In this paper, we describe our work to address this problem through the creation of a suite of modular ontologies representing the product life cycle and its successive phases, from design to end of (...)
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  7. A First-Order Logic Formalization of the Industrial Ontology Foundry Signature Using Basic Formal Ontology.Barry Smith, Farhad Ameri, Hyunmin Cheong, Dimitris Kiritsis, Dusan Sormaz, Chris Will & J. Neil Otte - 2019 - In Proceedings of the Joint Ontology Workshops (JOWO), Graz.
    Basic Formal Ontology (BFO) is a top-level ontology used in hundreds of active projects in scientific and other domains. BFO has been selected to serve as top-level ontology in the Industrial Ontologies Foundry (IOF), an initiative to create a suite of ontologies to support digital manufacturing on the part of representatives from a number of branches of the advanced manufacturing industries. We here present a first draft set of axioms and definitions of an IOF upper ontology descending from BFO. The (...)
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  8. The Plant Ontology Facilitates Comparisons of Plant Development Stages Across Species.Ramona Lynn Walls, Laurel Cooper, Justin Lee Elser, Maria Alejandra Gandolfo, Christopher J. Mungall, Barry Smith, Dennis William Stevenson & Pankaj Jaiswal - 2019 - Frontiers in Plant Science 10.
    The Plant Ontology (PO) is a community resource consisting of standardized terms, definitions, and logical relations describing plant structures and development stages, augmented by a large database of annotations from genomic and phenomic studies. This paper describes the structure of the ontology and the design principles we used in constructing PO terms for plant development stages. It also provides details of the methodology and rationale behind our revision and expansion of the PO to cover development stages for all plants, particularly (...)
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  9. Integrating Computer Vision Algorithms and Ontologies for Spectator Crowd Behavior Analysis.Davide Conigliaro, Celine Hudelot, Roberta Ferrario & Daniele Porello - 2017 - In Vittorio Murino, Marco Cristani, Shishir Shah & Silvio Savarese (eds.), Group and Crowd Behavior for Computer Vision, 1st Edition. pp. 297-319.
    In this paper, building on these previous works, we propose to go deeper into the understanding of crowd behavior by proposing an approach which integrates ontologi- cal models of crowd behavior and dedicated computer vision algorithms, with the aim of recognizing some targeted complex events happening in the playground from the observation of the spectator crowd behavior. In order to do that, we first propose an ontology encoding available knowledge on spectator crowd behavior, built as a spe- cialization of the (...)
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  10. The Space Object Ontology.Alexander P. Cox, Christopher Nebelecky, Ronald Rudnicki, William Tagliaferri, John L. Crassidis & Barry Smith - 2016 - In 19th International Conference on Information Fusion (FUSION 2016). IEEE.
    Achieving space domain awareness requires the identification, characterization, and tracking of space objects. Storing and leveraging associated space object data for purposes such as hostile threat assessment, object identification, and collision prediction and avoidance present further challenges. Space objects are characterized according to a variety of parameters including their identifiers, design specifications, components, subsystems, capabilities, vulnerabilities, origins, missions, orbital elements, patterns of life, processes, operational statuses, and associated persons, organizations, or nations. The Space Object Ontology provides a consensus-based realist framework (...)
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  11. Development of a Manufacturing Ontology for Functionally Graded Materials.Francesco Furini, Rahul Rai, Barry Smith, Georgio Colombo & Venkat Krovi - 2016 - In Proceedings of International Design Engineering Technical Conferences & Computers and Information in Engineering Conference (IDETC/CIE).
    The development of manufacturing technologies for new materials involves the generation of a large and continually evolving volume of information. The analysis, integration and management of such large volumes of data, typically stored in multiple independently developed databases, creates significant challenges for practitioners. There is a critical need especially for open-sharing of data pertaining to engineering design which together with effective decision support tools can enable innovation. We believe that ontology applied to engineering (OE) represents a viable strategy for the (...)
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  12. Features and Components in Product Models.Emilio M. Sanfilippo, Claudio Masolo, Stefano Borgo & Daniele Porello - 2016 - In 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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  13. Design Knowledge Representation: An Ontological Perspective.Emilio M. Sanfilippo, Claudio Masolo & Daniele Porello - 2015 - In 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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