Results for 'biomedical ontology'

951 found
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  1. Putting Biomedical Ontologies to Work.Barry Smith & Mathias Brochhausen - 2010 - Methods of Information in Medicine 49 (2):135-40.
    Biomedical ontologies exist to serve integration of clinical and experimental data, and it is critical to their success that they be put to widespread use in the annotation of data. How, then, can ontologies achieve the sort of user-friendliness, reliability, cost-effectiveness, and breadth of coverage that is necessary to ensure extensive usage? Methods: Our focus here is on two different sets of answers to these questions that have been proposed, on the one hand in medicine, by the SNOMED CT (...)
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  2. Biomedical ontology alignment: An approach based on representation learning.Prodromos Kolyvakis, Alexandros Kalousis, Barry Smith & Dimitris Kiritsis - 2018 - Journal of Biomedical Semantics 9 (21).
    While representation learning techniques have shown great promise in application to a number of different NLP tasks, they have had little impact on the problem of ontology matching. Unlike past work that has focused on feature engineering, we present a novel representation learning approach that is tailored to the ontology matching task. Our approach is based on embedding ontological terms in a high-dimensional Euclidean space. This embedding is derived on the basis of a novel phrase retrofitting strategy through (...)
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  3. Relations in Biomedical Ontologies.Barry Smith, Werner Ceusters, Bert Klagges, Jacob Köhler, Anand Kuma, Jane Lomax, Chris Mungall, , Fabian Neuhaus, Alan Rector & Cornelius Rosse - 2005 - Genome Biology 6 (5):R46.
    To enhance the treatment of relations in biomedical ontologies we advance a methodology for providing consistent and unambiguous formal definitions of the relational expressions used in such ontologies in a way designed to assist developers and users in avoiding errors in coding and annotation. The resulting Relation Ontology can promote interoperability of ontologies and support new types of automated reasoning about the spatial and temporal dimensions of biological and medical phenomena.
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  4. Biomedical Ontologies.Barry Smith - 2022 - In Peter L. Elkin (ed.), Terminology, Ontology and Their Implementations: Teaching Guide and Notes. Springer. pp. 125-169.
    We begin at the beginning, with an outline of Aristotle’s views on ontology and with a discussion of the influence of these views on Linnaeus. We move from there to consider the data standardization initiatives launched in the 19th century, and then turn to investigate how the idea of computational ontologies developed in the AI and knowledge representation communities in the closing decades of the 20th century. We show how aspects of this idea, particularly those relating to the use (...)
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  5. The National Center for Biomedical Ontology.Mark A. Musen, Natalya F. Noy, Nigam H. Shah, Patricia L. Whetzel, Christopher G. Chute, Margaret-Anne Story & Barry Smith - 2012 - Journal of the American Medical Informatics Association 19 (2):190-195.
    The National Center for Biomedical Ontology is now in its seventh year. The goals of this National Center for Biomedical Computing are to: create and maintain a repository of biomedical ontologies and terminologies; build tools and web services to enable the use of ontologies and terminologies in clinical and translational research; educate their trainees and the scientific community broadly about biomedical ontology and ontology-based technology and best practices; and collaborate with a variety of (...)
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  6. A realism-based approach to the evolution of biomedical ontologies.Werner Ceusters & Barry Smith - 2006 - In Proceedings of the Annual AMIA Symposium. Washington, DC: American Medical Informatics Association.
    We present a novel methodology for calculating the improvements obtained in successive versions of biomedical ontologies. The theory takes into account changes both in reality itself and in our understanding of this reality. The successful application of the theory rests on the willingness of ontology authors to document changes they make by following a number of simple rules. The theory provides a pathway by which ontology authoring can become a science rather than an art, following principles analogous (...)
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  7. Towards Interoperability of Biomedical Ontologies - Report Number 07132.Mark Musen, Michael Schroeder & Barry Smith - 2008 - In Musen Mark, A. Schroeder, Michael Smith & Barry (eds.), Towards Interoperability of Biomedical Ontologies. Schloss Dagstuhl: Leibniz-Zentrum für Informatik.
    The meeting focused on uses of ontologies, with a special focus on spatial ontologies, in addressing the ever increasing needs faced by biology and medicine to cope with ever expanding quantities of data. To provide effective solutions computers need to integrate data deriving from myriad heterogeneous sources by bringing the data together within a single framework. The meeting brought together leaders in the field of what are called "top-level ontologies" to address this issue, and to establish strategies among leaders in (...)
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  8. Clonal complexes in biomedical ontologies.Albert Goldfain, Lindsay Cowell & Barry Smith - 2009 - In Barry Smith (ed.), ICBO 2009: Proceedings of the First International Conference on Biomedical Ontology. Buffalo: NCOR. pp. 168.
    An accurate classification of bacteria is essential for the proper identification of patient infections and subsequent treatment decisions. Multi-Locus Sequence Typing (MLST) is a genetic technique for bacterial classification. MLST classifications are used to cluster bacteria into clonal complexes. Importantly, clonal complexes can serve as a biological species concept for bacteria, facilitating an otherwise difficult taxonomic classification. In this paper, we argue for the inclusion of terms relating to clonal complexes in biomedical ontologies.
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  9. A realism-based approach to the evolution of biomedical ontologies.Barry Smith - 2006 - In Proceedings of the Annual AMIA Symposium. Washington, DC: American Medical Informatics Association. pp. 121-125.
    We present a novel methodology for calculating the improvements obtained in successive versions of biomedical ontologies. The theory takes into account changes both in reality itself and in our understanding of this reality. The successful application of the theory rests on the willingness of ontology authors to document changes they make by following a number of simple rules. The theory provides a pathway by which ontology authoring can become a science rather than an art, following principles analogous (...)
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  10. (1 other version)A strategy for improving and integrating biomedical ontologies.Cornelius Rosse, Anand Kumar, Jose L. V. Mejino, Daniel L. Cook, Landon T. Detwiler & Barry Smith - 2007 - In Ron Rudnicki (ed.), Proceedings of the Annual Symposium of the American Medical Informatics Association. AMIA. pp. 639-643.
    The integration of biomedical terminologies is indispensable to the process of information integration. When terminologies are linked merely through the alignment of their leaf terms, however, differences in context and ontological structure are ignored. Making use of the SNAP and SPAN ontologies, we show how three reference domain ontologies can be integrated at a higher level, through what we shall call the OBR framework (for: Ontology of Biomedical Reality). OBR is designed to facilitate inference across the boundaries (...)
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  11. Classificatory Theory in Data-intensive Science: The Case of Open Biomedical Ontologies.Sabina Leonelli - 2012 - International Studies in the Philosophy of Science 26 (1):47 - 65.
    Knowledge-making practices in biology are being strongly affected by the availability of data on an unprecedented scale, the insistence on systemic approaches and growing reliance on bioinformatics and digital infrastructures. What role does theory play within data-intensive science, and what does that tell us about scientific theories in general? To answer these questions, I focus on Open Biomedical Ontologies, digital classification tools that have become crucial to sharing results across research contexts in the biological and biomedical sciences, and (...)
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  12. On the proper treatment of pathologies in biomedical ontologies.Barry Smith & Anand Kumar - 2005 - In Barry Smith & Anand Kumar (eds.), Proceedings of the Bio-Ontologies Workshop, Intelligent Systems for Molecular Biology (ISMB 2005). Detroit: pp. 22-23.
    In previous work on biomedical ontologies we showed how the provision of formal definitions for relations such as is_a and part_of can support new types of auto-mated reasoning about biomedical phenomena. We here extend this approach to the transformation_of characteristic of pathologies.
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  13. The Role of Foundational Relations in the Alignment of Biomedical Ontologies.Barry Smith & Cornelius Rosse - 2004 - In Stefan Schulze-Kremer (ed.), MedInfo. IOS Press. pp. 444-448.
    The Foundational Model of Anatomy (FMA) symbolically represents the structural organization of the human body from the macromolecular to the macroscopic levels, with the goal of providing a robust and consistent scheme for classifying anatomical entities that is designed to serve as a reference ontology in biomedical informatics. Here we articulate the need for formally clarifying the is-a and part-of relations in the FMA and similar ontology and terminology systems. We diagnose certain characteristic errors in the treatment (...)
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  14. ICBO 2009: Proceedings of the First International Conference on Biomedical Ontology.Barry Smith (ed.) - 2009 - Buffalo: NCOR.
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  15. A Unified Framework for Biomedical Terminologies and Ontologies.Werner Ceusters & Barry Smith - 2010 - Studies in Health Technology and Informatics 160:1050-1054.
    The goal of the OBO (Open Biomedical Ontologies) Foundry initiative is to create and maintain an evolving collection of non-overlapping interoperable ontologies that will offer unambiguous representations of the types of entities in biological and biomedical reality. These ontologies are designed to serve non-redundant annotation of data and scientific text. To achieve these ends, the Foundry imposes strict requirements upon the ontologies eligible for inclusion. While these requirements are not met by most existing biomedical terminologies, the latter (...)
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  16. Towards Interoperability of Biomedical Ontologies.Musen Mark, A. Schroeder, Michael Smith & Barry - 2008 - Schloss Dagstuhl: Leibniz-Zentrum für Informatik.
    Report on Dagstuhl Seminar 07132, Schloss Dagstuhl, March 27-30 , 2007.
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  17. The Ontology for Biomedical Investigations.Anita Bandrowski, Ryan Brinkman, Mathias Brochhausen, Matthew H. Brush, Bill Bug, Marcus C. Chibucos, Kevin Clancy, Mélanie Courtot, Dirk Derom, Michel Dumontier, Liju Fan, Jennifer Fostel, Gilberto Fragoso, Frank Gibson, Alejandra Gonzalez-Beltran, Melissa A. Haendel, Yongqun He, Mervi Heiskanen, Tina Hernandez-Boussard, Mark Jensen, Yu Lin, Allyson L. Lister, Phillip Lord, James Malone, Elisabetta Manduchi, Monnie McGee, Norman Morrison, James A. Overton, Helen Parkinson, Bjoern Peters, Philippe Rocca-Serra, Alan Ruttenberg, Susanna-Assunta Sansone, Richard H. Scheuermann, Daniel Schober, Barry Smith, Larisa N. Soldatova, Christian J. Stoeckert, Chris F. Taylor, Carlo Torniai, Jessica A. Turner, Randi Vita, Patricia L. Whetzel & Jie Zheng - 2016 - PLoS ONE 11 (4):e0154556.
    The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such (...)
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  18. Negative findings in electronic health records and biomedical ontologies: a realist approach.Werner Ceusters, Peter Elkin & Barry Smith - 2007 - International Journal of Medical Informatics 76 (3):S326-S333.
    PURPOSE—A substantial fraction of the observations made by clinicians and entered into patient records are expressed by means of negation or by using terms which contain negative qualifiers (as in “absence of pulse” or “surgical procedure not performed”). This seems at first sight to present problems for ontologies, terminologies and data repositories that adhere to a realist view and thus reject any reference to putative non-existing entities. Basic Formal Ontology (BFO) and Referent Tracking (RT) are examples of such paradigms. (...)
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  19. (1 other version)Ontology-assisted database integration to support natural language processing and biomedical data-mining.Jean-Luc Verschelde, Marianna C. Santos, Tom Deray, Barry Smith & Werner Ceusters - 2004 - Journal of Integrative Bioinformatics. Repr. In: Yearbook of Bioinformatics , 39–48 1:1-10.
    Successful biomedical data mining and information extraction require a complete picture of biological phenomena such as genes, biological processes, and diseases; as these exist on different levels of granularity. To realize this goal, several freely available heterogeneous databases as well as proprietary structured datasets have to be integrated into a single global customizable scheme. We will present a tool to integrate different biological data sources by mapping them to a proprietary biomedical ontology that has been developed for (...)
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  20. Biomedical Terminologies and Ontologies: Enabling Biomedical Semantic Interoperability and Standards in Europe.Bernard de Bono, Mathias Brochhausen, Sybo Dijkstra, Dipak Kalra, Stephan Keifer & Barry Smith - 2009 - In Bernard de Bono, Mathias Brochhausen, Sybo Dijkstra, Dipak Kalra, Stephan Keifer & Barry Smith (eds.), European Large-Scale Action on Electronic Health.
    In the management of biomedical data, vocabularies such as ontologies and terminologies (O/Ts) are used for (i) domain knowledge representation and (ii) interoperability. The knowledge representation role supports the automated reasoning on, and analysis of, data annotated with O/Ts. At an interoperability level, the use of a communal vocabulary standard for a particular domain is essential for large data repositories and information management systems to communicate consistently with one other. Consequently, the interoperability benefit of selecting a particular O/T as (...)
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  21. Biomedical imaging ontologies: A survey and proposal for future work.Barry Smith, Sivaram Arabandi, Mathias Brochhausen, Michael Calhoun, Paolo Ciccarese, Scott Doyle, Bernard Gibaud, Ilya Goldberg, Charles E. Kahn Jr, James Overton, John Tomaszewski & Metin Gurcan - 2015 - Journal of Pathology Informatics 6 (37):37.
    Ontology is one strategy for promoting interoperability of heterogeneous data through consistent tagging. An ontology is a controlled structured vocabulary consisting of general terms (such as “cell” or “image” or “tissue” or “microscope”) that form the basis for such tagging. These terms are designed to represent the types of entities in the domain of reality that the ontology has been devised to capture; the terms are provided with logical defi nitions thereby also supporting reasoning over the tagged (...)
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  22. Creating a Controlled Vocabulary for the Ethics of Human Research: Towards a biomedical ethics ontology.David Koepsell, Robert Arp, Jennifer Fostel & Barry Smith - 2009 - Journal of Empirical Research on Human Research Ethics 4 (1):43-58.
    Ontologies describe reality in specific domains in ways that can bridge various disciplines and languages. They allow easier access and integration of information that is collected by different groups. Ontologies are currently used in the biomedical sciences, geography, and law. A Biomedical Ethics Ontology would benefit members of ethics committees who deal with protocols and consent forms spanning numerous fields of inquiry. There already exists the Ontology for Biomedical Investigations (OBI); the proposed BMEO would interoperate (...)
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  23. Biodynamic Ontology: Applying BFO in the Biomedical Domain.Barry Smith, Pierre Grenon & Louis Goldberg - 2004 - Studies in Health and Technology Informatics 102:20–38.
    Current approaches to formal representation in biomedicine are characterized by their focus on either the static or the dynamic aspects of biological reality. We here outline a theory that combines both perspectives and at the same time tackles the by no means trivial issue of their coherent integration. Our position is that a good ontology must be capable of accounting for reality both synchronically (as it exists at a time) and diachronically (as it unfolds through time), but that these (...)
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  24. Bioportal: Ontologies and integrated data resources at the click of the mouse.L. Whetzel Patricia, H. Shah Nigam, F. Noy Natalya, Dai Benjamin, Dorf Michael, Griffith Nicholas, Jonquet Clement, Youn Cherie, Callendar Chris, Coulet Adrien, Barry Smith, Chris Chute & Mark Musen - 2011 - In Whetzel Patricia L., Shah Nigam H., Noy Natalya F., Benjamin Dai, Michael Dorf, Nicholas Griffith, Clement Jonquet, Cherie Youn, Chris Callendar, Adrien Coulet, Smith Barry, Chute Chris & Musen Mark (eds.), Proceedings of the 2nd International Conference on Biomedical Ontology, Buffalo, NY. pp. 292-293.
    BioPortal is a Web portal that provides access to a library of biomedical ontologies and terminologies developed in OWL, RDF(S), OBO format, Protégé frames, and Rich Release Format. BioPortal functionality, driven by a service-oriented architecture, includes the ability to browse, search and visualize ontologies (Figure 1). The Web interface also facilitates community-based participation in the evaluation and evolution of ontology content.
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  25. Formal Ontology for Natural Language Processing and the Integration of Biomedical Databases.Jonathan Simon, James M. Fielding, Mariana C. Dos Santos & Barry Smith - 2005 - International Journal of Medical Informatics 75 (3-4):224-231.
    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. To this end r®, 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). With this project we aim to move (...)
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  26. Ontology as the core discipline of biomedical informatics: Legacies of the past and recommendations for the future direction of research.Barry Smith & Werner Ceusters - 2007 - In Gordana Dodig Crnkovic & Susan Stuart (eds.), Computation, Information, Cognition: The Nexus and the Liminal.f. Cambridge Scholars Press. pp. 104-122.
    The automatic integration of rapidly expanding information resources in the life sciences is one of the most challenging goals facing biomedical research today. Controlled vocabularies, terminologies, and coding systems play an important role in realizing this goal, by making it possible to draw together information from heterogeneous sources – for example pertaining to genes and proteins, drugs and diseases – secure in the knowledge that the same terms will also represent the same entities on all occasions of use. In (...)
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  27. Ontological theory for ontological engineering: Biomedical systems information integration.James M. Fielding, Jonathan Simon, Werner Ceusters & Barry Smith - 2004 - In Fielding James M., Simon Jonathan, Ceusters Werner & Smith Barry (eds.), Proceedings of the Ninth International Conference on the Principles of Knowledge Representation and Reasoning (KR2004), Whistler, BC, 2-5 June 2004. pp. 114–120.
    Software application ontologies have the potential to become the keystone in state-of-the-art information management techniques. It is expected that these ontologies will support the sort of reasoning power required to navigate large and complex terminologies correctly and efficiently. Yet, there is one problem in particular that continues to stand in our way. As these terminological structures increase in size and complexity, and the drive to integrate them inevitably swells, it is clear that the level of consistency required for such navigation (...)
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  28. Towards a Reference Terminology for Ontology Research and Development in the Biomedical Domain.Barry Smith, Waclaw Kusnierczyk, Daniel Schober, & Werner Ceusters - 2006 - In Barry Smith, Waclaw Kusnierczyk, Schober & Werner Ceusters (eds.), Proceedings of KR-MED, CEUR, vol. 222. pp. 57-65.
    Ontology is a burgeoning field, involving researchers from the computer science, philosophy, data and software engineering, logic, linguistics, and terminology domains. Many ontology-related terms with precise meanings in one of these domains have different meanings in others. Our purpose here is to initiate a path towards disambiguation of such terms. We draw primarily on the literature of biomedical informatics, not least because the problems caused by unclear or ambiguous use of terms have been there most thoroughly addressed. (...)
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  29. An ontology-based methodology for the migration of biomedical terminologies to electronic health records.Barry Smith & Werner Ceusters - 2005 - In Smith Barry & Ceusters Werner (eds.), Proceedings of AMIA Symposium 2005, Washington DC,. AMIA. pp. 704-708.
    Biomedical terminologies are focused on what is general, Electronic Health Records (EHRs) on what is particular, and it is commonly assumed that the step from the one to the other is unproblematic. We argue that this is not so, and that, if the EHR of the future is to fulfill its promise, then the foundations of both EHR architectures and biomedical terminologies need to be reconceived. We accordingly describe a new framework for the treatment of both generals and (...)
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  30. Building Ontologies with Basic Formal Ontology.Robert Arp, Barry Smith & Andrew D. Spear - 2015 - Cambridge, MA: MIT Press.
    In the era of “big data,” science is increasingly information driven, and the potential for computers to store, manage, and integrate massive amounts of data has given rise to such new disciplinary fields as biomedical informatics. Applied ontology offers a strategy for the organization of scientific information in computer-tractable form, drawing on concepts not only from computer and information science but also from linguistics, logic, and philosophy. This book provides an introduction to the field of applied ontology (...)
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  31. Protein-centric connection of biomedical knowledge: Protein Ontology research and annotation tools.Cecilia N. Arighi, Darren A. Natale, Judith A. Blake, Carol J. Bult, Michael Caudy, Alexander D. Diehl, Harold J. Drabkin, Peter D'Eustachio, Alexei Evsikov, Hongzhan Huang, Barry Smith & Others - 2011 - In Landgrebe Jobst & Smith Barry (eds.), Proceedings of the 2nd International Conference on Biomedical Ontology. CEUR, vol. 833. pp. 285-287.
    The Protein Ontology (PRO) web resource provides an integrative framework for protein-centric exploration and enables specific and precise annotation of proteins and protein complexes based on PRO. Functionalities include: browsing, searching and retrieving, terms, displaying selected terms in OBO or OWL format, and supporting URIs. In addition, the PRO website offers multiple ways for the user to request, submit, or modify terms and/or annotation. We will demonstrate the use of these tools for protein research and annotation.
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  32. The Environment Ontology: Contextualising biological and biomedical entities.Pier Luigi Buttigieg, Norman Morrison, Barry Smith, Christopher J. Mungall & Suzanna E. Lewis - 2013 - Journal of Biomedical Semantics 4 (43):1-9.
    As biological and biomedical research increasingly reference the environmental context of the biological entities under study, the need for formalisation and standardisation of environment descriptors is growing. The Environment Ontology (ENVO) is a community-led, open project which seeks to provide an ontology for specifying a wide range of environments relevant to multiple life science disciplines and, through an open participation model, to accommodate the terminological requirements of all those needing to annotate data using ontology classes. This (...)
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  33. Formal ontology for biomedical knowledge systems integration.J. M. Fielding, J. Simon & Barry Smith - 2004 - Proceedings of Euromise:12-17.
    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 will greatly benefit software application ontologies. 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). With this, we aim to (...)
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  34. Constructing a lattice of Infectious Disease Ontologies from a Staphylococcus aureus isolate repository.Albert Goldfain, Lindsay G. Cowell & Barry Smith - 2012 - In Goldfain Albert, Cowell Lindsay G. & Smith Barry (eds.), Proceeedings of the Third International Conference on Biomedical Ontology (CEUR 897).
    A repository of clinically associated Staphylococcus aureus (Sa) isolates is used to semi‐automatically generate a set of application ontologies for specific subfamilies of Sa‐related disease. Each such application ontology is compatible with the Infectious Disease Ontology (IDO) and uses resources from the Open Biomedical Ontology (OBO) Foundry. The set of application ontologies forms a lattice structure beneath the IDO‐Core and IDO‐extension reference ontologies. We show how this lattice can be used to define a strategy for the (...)
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  35. The Ontology-Epistemology Divide: A Case Study in Medical Terminology.OIivier Bodenreider, Barry Smith & Anita Burgun - 2004 - In Achille C. Varzi & Laure Vieu (eds.), ”, Formal Ontology in Information Systems. Proceedings of the Third International Conference. IOS Press.
    Medical terminology collects and organizes the many different kinds of terms employed in the biomedical domain both by practitioners and also in the course of biomedical research. In addition to serving as labels for biomedical classes, these names reflect the organizational principles of biomedical vocabularies and ontologies. Some names represent invariant features (classes, universals) of biomedical reality (i.e., they are a matter for ontology). Other names, however, convey also how this reality is perceived, measured, (...)
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  36. Saliva Ontology: An ontology-based framework for a Salivaomics Knowledge Base.Jiye Ai, Barry Smith & David Wong - 2010 - BMC Bioinformatics 11 (1):302.
    The Salivaomics Knowledge Base (SKB) is designed to serve as a computational infrastructure that can permit global exploration and utilization of data and information relevant to salivaomics. SKB is created by aligning (1) the saliva biomarker discovery and validation resources at UCLA with (2) the ontology resources developed by the OBO (Open Biomedical Ontologies) Foundry, including a new Saliva Ontology (SALO). We define the Saliva Ontology (SALO; http://www.skb.ucla.edu/SALO/) as a consensus-based controlled vocabulary of terms and relations (...)
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  37. Strengths and Limitations of Formal Ontologies in the Biomedical Domain.Barry Smith - 2009 - Electronic Journal of Communication, Information and Innovation in Health 3 (1):31-45.
    We propose a typology of representational artifacts for health care and life sciences domains and associate this typology with different kinds of formal ontology and logic, drawing conclusions as to the strengths and limitations for ontology in a description logics framework. The four types of domain representation we consider are: (i) lexico-semantic representation, (ii) representation of types of entities, (iii) representations of background knowledge, and (iv) representation of individuals. We advocate a clear distinction of the four kinds of (...)
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  38. Ontology based annotation of contextualized vital signs.Goldfain Albert, Xu Min, Bona Jonathan & Barry Smith - 2013 - In Albert Goldfain, Min Xu, Jonathan Bona & Smith Barry (eds.), Proceedings of the Fourth International Conference on Biomedical Ontology (ICBO). pp. 28-33.
    Representing the kinetic state of a patient (posture, motion, and activity) during vital sign measurement is an important part of continuous monitoring applications, especially remote monitoring applications. In contextualized vital sign representation, the measurement result is presented in conjunction with salient measurement context metadata. We present an automated annotation system for vital sign measurements that uses ontologies from the Open Biomedical Ontology Foundry (OBO Foundry) to represent the patient’s kinetic state at the time of measurement. The annotation system (...)
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  39. The Protein Ontology: A structured representation of protein forms and complexes.Darren Natale, Cecilia N. Arighi, Winona C. Barker, Judith A. Blake, Carol J. Bult, Michael Caudy, Harold J. Drabkin, Peter D’Eustachio, Alexei V. Evsikov, Hongzhan Huang, Jules Nchoutmboube, Natalia V. Roberts, Barry Smith, Jian Zhang & Cathy H. Wu - 2011 - Nucleic Acids Research 39 (1):D539-D545.
    The Protein Ontology (PRO) provides a formal, logically-based classification of specific protein classes including structured representations of protein isoforms, variants and modified forms. Initially focused on proteins found in human, mouse and Escherichia coli, PRO now includes representations of protein complexes. The PRO Consortium works in concert with the developers of other biomedical ontologies and protein knowledge bases to provide the ability to formally organize and integrate representations of precise protein forms so as to enhance accessibility to results (...)
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  40. Context-based task ontologies for clinical guidelines.Anand Kumar, Paolo Ciccarese, Barry Smith & Matteo Piazza - 2004 - In Pisanelli D. (ed.), Ontologies in Medicine: Proceedings of the Workshop on Medical Ontologies, Rome October 2003 (Studies in Health and Technology Informatics, 102). IOS Press. pp. 81-94.
    Evidence-based medicine relies on the execution of clinical practice guidelines and protocols. A great deal of of effort has been invested in the development of various tools which automate the representation and execution of the recommendations contained within such guidelines and protocols by creating Computer Interpretable Guideline Models (CIGMs). Context-based task ontologies (CTOs), based on standard terminology systems like UMLS, form one of the core components of such a model. We have created DAML+OIL-based CTOs for the tasks mentioned in the (...)
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  41. Framework for a protein ontology.Darren A. Natale, Cecilia N. Arighi, Winona Barker, Judith Blake, Ti-Cheng Chang, Zhangzhi Hu, Hongfang Liu, Barry Smith & Cathy H. Wu - 2007 - BMC Bioinformatics 8 (Suppl 9):S1.
    Biomedical ontologies are emerging as critical tools in genomic and proteomic research where complex data in disparate resources need to be integrated. A number of ontologies exist that describe the properties that can be attributed to proteins; for example, protein functions are described by Gene Ontology, while human diseases are described by Disease Ontology. There is, however, a gap in the current set of ontologies—one that describes the protein entities themselves and their relationships. We have designed a (...)
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  42. Toll-like receptor signaling in vertebrates: Testing the integration of protein, complex, and pathway data in the Protein Ontology framework.Cecilia Arighi, Veronica Shamovsky, Anna Maria Masci, Alan Ruttenberg, Barry Smith, Darren Natale, Cathy Wu & Peter D’Eustachio - 2015 - PLoS ONE 10 (4):e0122978.
    The Protein Ontology provides terms for and supports annotation of species-specific protein complexes in an ontology framework that relates them both to their components and to species-independent families of complexes. Comprehensive curation of experimentally known forms and annotations thereof is expected to expose discrepancies, differences, and gaps in our knowledge. We have annotated the early events of innate immune signaling mediated by Toll-Like Receptor 3 and 4 complexes in human, mouse, and chicken. The resulting ontology and annotation (...)
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  43. Coordinating Coronavirus Research: The COVID-19 Infectious Disease Ontology.John Beverley, Shane Babcock, Barry Smith, Yongqun He, Eric Merrell, Lindsay Cowell, Regina Hurley & Sebastian Duesing - 2022 - Proceedings of the International Conference on Biomedical Ontologies.
    The COVID-19 pandemic prompted immense work on the investigation of the SARS-CoV-2 virus. Ontologies – structured, controlled, vocabularies – are designed to support consistency of interpretation, and thereby to prevent the development of data silos. This paper describes how ontologies are serving this purpose in the virus research domain, following the principles of the Open Biological and Biomedical Ontology (OBO) Foundry and drawing on the resources of the Infectious Disease Ontology (IDO) Core. We report the development of (...)
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  44. Six questions on the construction of ontologies in biomedicine.Anand Kumar, A. Burgun, W. Ceusters, J. Cimino, J. Davis, P. Elkin, I. Kalet, A. Rector, J. Rice, J. Rogers, Barry Smith & Others - 2005 - Report of the AMIA Working Group on Formal Biomedical Knowledge Representation 1.
    (Report assembled for the Workshop of the AMIA Working Group on Formal Biomedical Knowledge Representation in connection with AMIA Symposium, Washington DC, 2005.) Best practices in ontology building for biomedicine have been frequently discussed in recent years. However there is a range of seemingly disparate views represented by experts in the field. These views not only reflect the different uses to which ontologies are put, but also the experiences and disciplinary background of these experts themselves. We asked six (...)
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  45. Establishing and Harmonizing Ontologies in an Interdisciplinary Health Care and Clinical Research Environment.Barry Smith & Mathias Brochhausen - 2008 - Studies in Health, Technology and Informatics 134:219-234.
    Ontologies are being ever more commonly used in biomedical informatics and we provide a survey of some of these uses, and of the relations between ontologies and other terminology resources. In order for ontologies to become truly useful, two objectives must be met. First, ways must be found for the transparent evaluation of ontologies. Second, existing ontologies need to be harmonised. We argue that one key foundation for both ontology evaluation and harmonisation is the adoption of a realist (...)
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  46. Ontological realism: A methodology for coordinated evolution of scientific ontologies.Barry Smith & Werner Ceusters - 2010 - Applied ontology 5 (3):139-188.
    Since 2002 we have been testing and refining a methodology for ontology development that is now being used by multiple groups of researchers in different life science domains. Gary Merrill, in a recent paper in this journal, describes some of the reasons why this methodology has been found attractive by researchers in the biological and biomedical sciences. At the same time he assails the methodology on philosophical grounds, focusing specifically on our recommendation that ontologies developed for scientific purposes (...)
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  47. The Plant Ontology: A common reference ontology for plants.L. Walls Ramona, D. Cooper Laurel, Elser Justin, W. Stevenson Dennis, Barry Smith, Mungall Chris, A. Gandolfo Maria & Jaiswal Pankaj - 2010 - In Walls Ramona L., Cooper Laurel D., Justin Elser, Stevenson Dennis W., Smith Barry, Chris Mungall, Gandolfo Maria A. & Pankaj Jaiswal (eds.), Proceedings of the Workshop on Bio-Ontologies, ISMB, Boston, July, 2010.
    The Plant Ontology (PO) (http://www.plantontology.org) (Jaiswal et al., 2005; Avraham et al., 2008) was designed to facilitate cross-database querying and to foster consistent use of plant-specific terminology in annotation. As new data are generated from the ever-expanding list of plant genome projects, the need for a consistent, cross-taxon vocabulary has grown. To meet this need, the PO is being expanded to represent all plants. This is the first ontology designed to encompass anatomical structures as well as growth and (...)
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  48. Molecular Interactions. On the Ambiguity of Ordinary Statements in Biomedical Literature.Stefan Schulz & Ludger Jansen - 2009 - Applied ontology (4):21-34.
    Statements about the behavior of biochemical entities (e.g., about the interaction between two proteins) abound in the literature on molecular biology and are increasingly becoming the targets of information extraction and text mining techniques. We show that an accurate analysis of the semantics of such statements reveals a number of ambiguities that have to be taken into account in the practice of biomedical ontology engineering: Such statements can not only be understood as event reporting statements, but also as (...)
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  49. The Infectious Disease Ontology in the Age of COVID-19.Shane Babcock, Lindsay G. Cowell, John Beverley & Barry Smith - 2021 - Journal of Biomedical Semantics 12 (13).
    The Infectious Disease Ontology (IDO) is a suite of interoperable ontology modules that aims to provide coverage of all aspects of the infectious disease domain, including biomedical research, clinical care, and public health. IDO Core is designed to be a disease and pathogen neutral ontology, covering just those types of entities and relations that are relevant to infectious diseases generally. IDO Core is then extended by a collection of ontology modules focusing on specific diseases and (...)
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  50. The Neurological Disease Ontology.Mark Jensen, Alexander P. Cox, Naveed Chaudhry, Marcus Ng, Donat Sule, William Duncan, Patrick Ray, Bianca Weinstock-Guttman, Barry Smith, Alan Ruttenberg, Kinga Szigeti & Alexander D. Diehl - 2013 - Journal of Biomedical Semantics 4 (42):42.
    We are developing the Neurological Disease Ontology (ND) to provide a framework to enable representation of aspects of neurological diseases that are relevant to their treatment and study. ND is a representational tool that addresses the need for unambiguous annotation, storage, and retrieval of data associated with the treatment and study of neurological diseases. ND is being developed in compliance with the Open Biomedical Ontology Foundry principles and builds upon the paradigm established by the Ontology for (...)
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