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Ron Rudnicki [6]Ronald Rudnicki [2]R. Rudnicki [1]
  1. The Space Object Ontology.Alexander P. Cox, Christopher Nebelecky, Ronald Rudnicki, William Tagliaferri, John L. Crassidis & Barry Smith - 2016 - In Alexander P. Cox, Christopher Nebelecky, Ronald Rudnicki, William Tagliaferri, John L. Crassidis & Barry Smith (eds.), 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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  2. Ontology and Cognitive Outcomes.David Limbaugh, Jobst Landgrebe, David Kasmier, Ronald Rudnicki, James Llinas & Barry Smith - 2020 - Journal of Knowledge Structures and Systems 1 (1): 3-22.
    The term ‘intelligence’ as used in this paper refers to items of knowledge collected for the sake of assessing and maintaining national security. The intelligence community (IC) of the United States (US) is a community of organizations that collaborate in collecting and processing intelligence for the US. The IC relies on human-machine-based analytic strategies that 1) access and integrate vast amounts of information from disparate sources, 2) continuously process this information, so that, 3) a maximally comprehensive understanding of world actors (...)
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  3. The Space Domain Ontologies.Alexander P. Cox, C. K. Nebelecky, R. Rudnicki, W. A. Tagliaferri, J. L. Crassidis & B. Smith - 2021 - In Alexander P. Cox, C. K. Nebelecky, R. Rudnicki, W. A. Tagliaferri, J. L. Crassidis & B. Smith (eds.), National Symposium on Sensor & Data Fusion Committee.
    Achieving space situational awareness requires, at a minimum, the identification, characterization, and tracking of space objects. Leveraging the resultant space object data for purposes such as hostile threat assessment, object identification, and conjunction assessment presents major challenges. This is in part because in characterizing space objects we reference a variety of identifiers, components, subsystems, capabilities, vulnerabilities, origins, missions, orbital elements, patterns of life, operational processes, operational statuses, and so forth, which tend to be defined in highly heterogeneous and sometimes inconsistent (...)
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  4. 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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  5. IAO-Intel: An Ontology of Information Artifacts in the Intelligence Domain.Barry Smith, Tatiana Malyuta, Ron Rudnicki, William Mandrick, David Salmen, Peter Morosoff, Danielle K. Duff, James Schoening & Kesny Parent - 2013 - In Kathryn Blackmond Laskey, Ian Emmons & Paulo C. G. Costa (eds.), Proceedings of the Eighth International Conference on Semantic Technologies for Intelligence, Defense, and Security (STIDS), CEUR, vol. 1097. pp. 33-40.
    We describe on-going work on IAO-Intel, an information artifact ontology developed as part of a suite of ontologies designed to support the needs of the US Army intelligence community within the framework of the Distributed Common Ground System (DCGS-A). IAO-Intel provides a controlled, structured vocabulary for the consistent formulation of metadata about documents, images, emails and other carriers of information. It will provide a resource for uniform explication of the terms used in multiple existing military dictionaries, thesauri and metadata registries, (...)
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  6. Joint Doctrine Ontology: A Benchmark for Military Information Systems Interoperability.Peter Morosoff, Ron Rudnicki, Jason Bryant, Robert Farrell & Barry Smith - 2015 - In Peter Morosoff, Ron Rudnicki, Jason Bryant, Robert Farrell & Barry Smith (eds.), Joint Doctrine Ontology: A Benchmark for Military Information Systems Interoperability. CEUR vol. 1325. pp. 2-9.
    When the U.S. conducts warfare, elements of a force are drawn from different services and work together as a single team to accomplish an assigned mission. To achieve such unified action, it is necessary that the doctrines governing the actions of members of specific services be both consistent with and subservient to joint Doctrine. Because warfighting today increasingly involves not only live forces but also automated systems, unified action requires that information technology that is used in joint warfare must be (...)
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  7. Controlled and uncontrolled English for ontology editing.Brian Donohue, Douglas Kutach, Robert Ganger, Ron Rudnicki, Tien Pham, Geeth de Mel, Dave Braines & Barry Smith - 2015 - Semantic Technology for Intelligence, Defense and Security 1523:74-81.
    Ontologies formally represent reality in a way that limits ambiguity and facilitates automated reasoning and data fusion, but is often daunting to the non-technical user. Thus, many researchers have endeavored to hide the formal syntax and semantics of ontologies behind the constructs of Controlled Natural Languages (CNLs), which retain the formal properties of ontologies while simultaneously presenting that information in a comprehensible natural language format. In this paper, we build upon previous work in this field by evaluating prospects of implementing (...)
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  8. What particulars are referred to in EHR data? A case study in integrating referent tracking into an electronic health record application.Ron Rudnicki, Werner Ceusters, Shaid Manzoo & Barry Smith - 2007 - In Proceedings of the Annual Symposium of the American Medical Informatics Association. AMIA. pp. 630-634.
    Referent Tracking (RT) advocates the use of instance unique identifiers to refer to the entities comprising the subject matter of patient health records. RT promises many benefits to those who use health record data to improve patient care. To further the adoption of the paradigm we provide an illustration of how data from an EHR application needs to be decomposed in order to make it accord with the tenets of RT. We describe the ontological principles on which this decomposition is (...)
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  9. What Particulars are Referred to in EHR Data? A Case Study in Integrating Referent Tracking into an Electronic Health Record Application.Ron Rudnicki - 2007 - In Proceedings of the Annual Symposium of the American Medical Informatics Association. AMIA.
    The Referent Tracking paradigm, which advocates the use of instance unique identifiers to refer to the entities comprising the subject matter of patient health records, promises many benefits to those who use health record data to improve patient care. To further the adoption of the paradigm we provide an illustration of how data from an EHR application needs to be decomposed to make it accord with the tenets of Referent Tracking. We describe the ontological principles on which such decomposition needs (...)
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