87,572 research outputs found

    Ontology For Europe's Space Situational Awareness Program

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    This paper presents an ontology architecture concept for the European Space Agency‘s (ESA) Space Situational Awareness (SSA) Program. It incorporates the author‘s domain ontology, The Space Situational Awareness Ontology and related ontology work. I summarize computational ontology, discuss the segments of ESA SSA, and introduce an option for a modular ontology framework reflecting the divisionsof the SSA program. Among other things, ontologies are used for data sharing and integration. By applying ontology to ESA data, the ESA may better achieve its integration and innovation goals, while simultaneously improving the state of peaceful SSA

    Pragmatic Ontology Evolution: Reconciling User Requirements and Application Performance

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    Increasingly, organizations are adopting ontologies to describe their large catalogues of items. These ontologies need to evolve regularly in response to changes in the domain and the emergence of new requirements. An important step of this process is the selection of candidate concepts to include in the new version of the ontology. This operation needs to take into account a variety of factors and in particular reconcile user requirements and application performance. Current ontology evolution methods focus either on ranking concepts according to their relevance or on preserving compatibility with existing applications. However, they do not take in consideration the impact of the ontology evolution process on the performance of computational tasks – e.g., in this work we focus on instance tagging, similarity computation, generation of recommendations, and data clustering. In this paper, we propose the Pragmatic Ontology Evolution (POE) framework, a novel approach for selecting from a group of candidates a set of concepts able to produce a new version of a given ontology that i) is consistent with the a set of user requirements (e.g., max number of concepts in the ontology), ii) is parametrised with respect to a number of dimensions (e.g., topological considerations), and iii) effectively supports relevant computational tasks. Our approach also supports users in navigating the space of possible solutions by showing how certain choices, such as limiting the number of concepts or privileging trendy concepts rather than historical ones, would reflect on the application performance. An evaluation of POE on the real-world scenario of the evolving Springer Nature taxonomy for editorial classification yielded excellent results, demonstrating a significant improvement over alternative approaches

    Repairing Ontologies via Axiom Weakening.

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    Ontology engineering is a hard and error-prone task, in which small changes may lead to errors, or even produce an inconsistent ontology. As ontologies grow in size, the need for automated methods for repairing inconsistencies while preserving as much of the original knowledge as possible increases. Most previous approaches to this task are based on removing a few axioms from the ontology to regain consistency. We propose a new method based on weakening these axioms to make them less restrictive, employing the use of refinement operators. We introduce the theoretical framework for weakening DL ontologies, propose algorithms to repair ontologies based on the framework, and provide an analysis of the computational complexity. Through an empirical analysis made over real-life ontologies, we show that our approach preserves significantly more of the original knowledge of the ontology than removing axioms

    A black art: Ontology, data, and the Tower of Babel problem

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    Computational ontologies are a new type of emerging scientific media (Smith, 2016) that process large quantities of heterogeneous data about portions of reality. Applied computational ontologies are used for semantically integrating (Heiler, 1995; Pileggi & Fernandez-Llatas, 2012) divergent data to represent reality and in so doing applied computational ontologies alter conceptions of materiality and produce new realities based on levels of informational granularity and abstraction (Floridi, 2011), resulting in a new type of informational ontology (Iliadis, 2013) the critical analysis of which requires new methods and frameworks. Currently, there is a lack of literature addressing the theoretical, social, and critical dimensions of such informational ontologies, applied computational ontologies, and the interdisciplinary communities of practice (Brown & Duguid, 1991; Wenger, 1998) that produce them. This dissertation fills a lacuna in communicative work in an emerging subfield of Science and Technology Studies (Latour & Woolgar, 1979) known as Critical Data Studies (boyd & Crawford, 2012; Dalton & Thatcher, 2014; Kitchin & Lauriault, 2014) by adopting a critical framework to analyze the systems of thought that inform applied computational ontology while offering insight into its realism-based methods and philosophical frameworks to gauge their ethical import. Since the early 1990s, computational ontologies have been used to organize massive amounts of heterogeneous data by individuating reality into computable parts, attributes, and relations. This dissertation provides a theory of computational ontologies as technologies of individuation (Simondon, 2005) that translate disparate data to produce informational cohesion. By technologies of individuation I mean engineered artifacts whose purpose is to partition portions of reality into computable informational objects. I argue that data are metastable entities and that computational ontologies restrain heterogeneous data via a process of translation to produce semantic interoperability. In this way, I show that computational ontologies effectively re-ontologize (Floridi, 2013) and produce reality and thus that have ethical consequences, specifically in terms of their application to social reality and social ontology (Searle, 2006). I use the Basic Formal Ontology (Arp, Smith, & Spear, 2015)—the world’s most widely used upper-level ontology—as a case study and analyze its methods and ensuing ethical issues concerning its social application in the Military Ontology before recommending an ethical framework. “Ontology” is a term that is used in philosophy and computer science in related but different ways—philosophical ontology typically concerns metaphysics while computational ontology typically concerns databases. This dissertation provides a critical history and theory of ontology and the interdisciplinary teams of researchers that came to adopt methods from philosophical ontology to build, persuade, and reason with applied computational ontology. Following a critical communication approach, I define applied computational ontology construction as a solution to a communication problem among scientists who seek to create semantic interoperability among data and argue that applied ontology is philosophical, informational in nature, and communicatively constituted (McPhee & Zaug, 2000). The primary aim is to explain how philosophy informs applied computational ontology while showing how such ontologies became instantiated in material organizations, how to study them, and describe their ethical implications

    Foreign objects? Web content management systems, journalistic cultures and the ontology of software

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    Research on ‘digital’ journalism has focused largely on online news, with comparatively less interest in the longer-term implications of software and computational technologies. Drawing upon a six-year study of the Toronto Star, this paper provides an account of TOPS, an in-house web content management system (CMS) which served as the backbone of thestar.com for six years. For some, TOPS was a successful software innovation, while for others, a strategic digital ‘property’. But for most journalists, it was slow, deficient in functionality, aesthetically unappealing and cumbersome. Although several organizational factors can explain TOPS’ obstinacy, I argue for particular attention to the complex ontology of software. Based on an outline of this ontology, I suggest software be taken seriously as an object of journalism, which implies: acknowledging its partial autonomy from human use or authorization; accounting for its ability to mutate indefinitely; and analyzing its capacity to encourage forms of ‘computational thinking
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