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J. Neil Otte
Johns Hopkins University Applied Physics Laboratory
  1.  76
    The Industrial Ontologies Foundry (IOF) Perspectives.Mohamed Karray, Neil Otte, Rahul Rai, Farhad Ameri, Boonserm Kulvatunyou, Barry Smith, Dimitris Kiritsis, Chris Will, Rebecca Arista & Others - 2021 - Proceedings: Industrial Ontology Foundry (IOF) Achieving Data Interoperability Workshop, International Conference on Interoperability for Enterprise Systems and Applications, Tarbes, France, March 17-24, 2020.
    In recent years there has been a number of promising technical and institutional developments regarding use of ontologies in industry. At the same time, however, most industrial ontology development work remains within the realm of academic research and is without significant uptake in commercial applications. In biomedicine, by contrast, ontologies have made significant inroads as valuable tools for achieving interoperability between data systems whose contents derive from widely heterogeneous sources. In this position paper, we present a set of principles learned (...)
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  2. An Ontological Approach to Territorial Disputes.Neil Otte, Brian Donohue & Barry Smith - 2014 - In Semantic Technology in Intelligence, Defense and Security (STIDS), CEUR, vol. 1304. CEUR. pp. 2-9.
    Disputes over territory are a major contributing factor to the disruption of international relations. We believe that a cumulative, integrated, and continuously updated resource providing information about such disputes in an easily accessible form would be of benefit to intelligence analysts, military strategists, political scientists, and also to historians and others concerned with international disputes. We propose an ontology-based strategy for creating such a resource. The resource will contain information about territorial disputes, arguments for and against claims pertaining to sovereignty, (...)
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  3.  73
    Wind Turbine Analysis Project.Neil Otte, Rahul Rai, Clare Paul & Barry Smith - 2018 - Final Project Report.
    The report describes an application of ontologies to the analysis of wind turbine manufacturing data. We show how applying ontologies to composite materials data may facilitate the discovery of optimum composite material designs that will deliver maximum wind turbine blade performance within environmental constraints.
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