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  1. The Unified Medical Language System and the Gene Ontology: Some critical reflections.Anand Kumar & Barry Smith - 2003 - In A. Günter, R. Kruse & B. Neumann (eds.), KI 2003: Advances in Artificial Intelligence. Berlin: Springer. pp. 135-148.
    The Unified Medical Language System and the Gene Ontology are among the most widely used terminology resources in the biomedical domain. However, when we evaluate them in the light of simple principles for wellconstructed ontologies we find a number of characteristic inadequacies. Employing the theory of granular partitions, a new approach to the understanding of ontologies and of the relationships ontologies bear to instances in reality, we provide an application of this theory in relation to an example drawn from the (...)
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  • Anatomical information science.Barry Smith, Jose Mejino, Stefan Schulz, Anand Kumar & Cornelius Rosse - 2005 - In A. G. Cohn & D. M. Mark (eds.), Spatial Information Theory. Springer. pp. 149-164.
    The Foundational Model of Anatomy (FMA) is a map of the human body. Like maps of other sorts – including the map-like representations we find in familiar anatomical atlases – it is a representation of a certain portion of spatial reality as it exists at a certain (idealized) instant of time. But unlike other maps, the FMA comes in the form of a sophisticated ontology of its objectdomain, comprising some 1.5 million statements of anatomical relations among some 70,000 anatomical kinds. (...)
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  • Revising the UMLS Semantic Network.Steffen Schulze-Kremer, Barry Smith & Anand Kumar - 2004 - In Schulze-Kremer Steffen, Smith Barry & Kumar Anand (eds.), MedInfo.
    The integration of standardized biomedical terminologies into a single, unified knowledge representation system has formed a key area of applied informatics research in recent years. The Unified Medical Language System (UMLS) is the most advanced and most prominent effort in this direction, bringing together within its Metathesaurus a large number of distinct source-terminologies. The UMLS Semantic Network, which is designed to support the integration of these source-terminologies, has proved to be a highly successful combination of formal coherence and broad scope. (...)
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  • Reference ontologies for biomedical ontology integration and natural language processing.Jonathan Simon, James Fielding, Mariana Dos Santos & Barry Smith - 2004 - In Simon Jonathan, Fielding James, Dos Santos Mariana & Smith Barry (eds.), Proceedings of the International Joint Meeting EuroMISE 2004. pp. 62-72.
    The central hypothesis of the collaboration between Language and Computing (L&C) and the Institute for Formal Ontology and Medical Information Science (IFOMIS) is that the methodology and conceptual rigor of a philosophically inspired formal ontology greatly benefits application ontologies.[1] To this end LinKBase®, L&C’s ontology, which is designed to integrate and reason across various external databases simultaneously, has been submitted to the conceptual demands of IFOMIS’s Basic Formal Ontology (BFO).[2] With this project we aim to move beyond the level of (...)
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  • Ontology for task-based clinical guidelines and the theory of granular partitions.Anand Kumar & Barry Smith - 2003 - In Michel Dojat, Elpida T. Keravnou & Pedro Barahona (eds.), Proceedings of 9th Conference on Artificial Intelligence in Medicine Europe (AIME 2003). Springer. pp. 71-75.
    The theory of granular partitions (TGP) is a new approach to the understanding of ontologies and other classificatory systems. The paper explores the use of this new theory in the treatment of task-based clinical guidelines as a means for better understanding the relations between different clinical tasks, both within the framework of a single guideline and between related guidelines. We used as our starting point a DAML+OIL-based ontology for the WHO guideline for hypertension management, comparing this with related guidelines and (...)
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  • The OBO Foundry: Coordinated evolution of ontologies to support biomedical data integration.Barry Smith, Michael Ashburner, Cornelius Rosse, Jonathan Bard, William Bug, Werner Ceusters, Louis J. Goldberg, Karen Eilbeck, Amelia Ireland, Christopher J. Mungall, Neocles Leontis, Philippe Rocca-Serra, Alan Ruttenberg, Susanna-Assunta Sansone, Richard H. Scheuermann, Nigam Shah, Patricia L. Whetzel & Suzanna Lewis - 2007 - Nature Biotechnology 25 (11):1251-1255.
    The value of any kind of data is greatly enhanced when it exists in a form that allows it to be integrated with other data. One approach to integration is through the annotation of multiple bodies of data using common controlled vocabularies or ‘ontologies’. Unfortunately, the very success of this approach has led to a proliferation of ontologies which itself creates obstacles to integration. The Open Biomedical Ontologies (OBO) consortium has set in train a strategy to overcome this problem. Existing (...)
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  • Advanced lexical ontologies and hybrid knowledge based systems: First steps to a dynamic legal electronic commentary. [REVIEW]Erich Schweighofer & Doris Liebwald - 2007 - Artificial Intelligence and Law 15 (2):103-115.
    Legal Information Retrieval (IR) research has stressed the fact that legal knowledge systems should be sufficiently capable to interpret and handle the semantics of a database. Modeling (expert-) knowledge by using ontologies enhances the ability to extract and exploit information from documents. This contribution presents theories, ideas and notions regarding the development of dynamic electronic commentaries based on a comprehensive legal ontology.
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  • Binding ontologies and coding systems to electronic health records and messages.Alan L. Rector, Rahil Qamar & Tom Marley - 2009 - Applied ontology 4 (1):51-69.
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  • Representing the NCI Thesaurus in OWL DL: Modeling tools help modeling languages.Natalya F. Noy, Sherri de Coronado, Harold Solbrig, Gilberto Fragoso, Frank W. Hartel & Mark A. Musen - 2008 - Applied ontology 3 (3):173-190.
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  • Adapting Clinical Ontologies in Real-World Environments.Holger Stenzhorn, Stefan Schulz, Martin Boeker & Barry Smith - 2008 - Journal of Universal Computer Science 14 (22):3767-3780.
    The desideratum of semantic interoperability has been intensively discussed in medical informatics circles in recent years. Originally, experts assumed that this issue could be sufficiently addressed by insisting simply on the application of shared clinical terminologies or clinical information models. However, the use of the term ‘ontology’ has been steadily increasing more recently. We discuss criteria for distinguishing clinical ontologies from clinical terminologies and information models. Then, we briefly present the role clinical ontologies play in two multicentric research projects. Finally, (...)
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  • A terminological and ontological analysis of the NCI thesaurus.Werner Ceusters, Barry Smith & Louis Goldberg - 2005 - Methods of Information in Medicine 44 (4):498-507.
    We performed a qualitative analysis of the Thesaurus in order to assess its conformity with principles of good practice in terminology and ontology design. We used both the on-line browsable version of the Thesaurus and its OWL-representation (version 04.08b, released on August 2, 2004), measuring each in light of the requirements put forward in relevant ISO terminology standards and in light of ontological principles advanced in the recent literature. Version 04.08b of the NCI Thesaurus suffers from the same broad range (...)
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  • Ontology-based error detection in SNOMED-CT.Werner Ceusters, Barry Smith, Anand Kumar & Christoffel Dhaen - 2004 - Proceedings of Medinfo 2004:482-6.
    Quality assurance in large terminologies is a difficult issue. We present two algorithms that can help terminology developers and users to identify potential mistakes. We demon­strate the methodology by outlining the different types of mistakes that are found when the algorithms are applied to SNOMED-CT. On the basis of the results, we argue that both formal logical and linguistic tools should be used in the development and quality-assurance process of large terminologies.
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  • Oncology ontology in the NCI Thesaurus.Anand Kumar & Barry Smith - 2005 - Artificial Intelligence in Medicine:213-220.
    The National Cancer Institute’s Thesaurus (NCIT) has been created with the goal of providing a controlled vocabulary which can be used by specialists in the various sub-domains of oncology. It is intended to be used for purposes of annotation in ways designed to ensure the integration of data and information deriving from these various sub-domains, and thus to support more powerful cross-domain inferences. In order to evaluate its suitability for this purpose, we examined the NCIT’s treatment of the kinds of (...)
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