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  1. 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 that is of (...)
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  • Promoting Coherent Minimum Reporting Guidelines for Biological and Biomedical Investigations: The MIBBI Project.Chris F. Taylor, Dawn Field, Susanna-Assunta Sansone, Jan Aerts, Rolf Apweiler, Michael Ashburner, Catherine A. Ball, Pierre-Alain Binz, Molly Bogue, Tim Booth, Alvis Brazma, Ryan R. Brinkman, Adam Michael Clark, Eric W. Deutsch, Oliver Fiehn, Jennifer Fostel, Peter Ghazal, Frank Gibson, Tanya Gray, Graeme Grimes, John M. Hancock, Nigel W. Hardy, Henning Hermjakob, Randall K. Julian, Matthew Kane, Carsten Kettner, Christopher Kinsinger, Eugene Kolker, Martin Kuiper, Nicolas Le Novere, Jim Leebens-Mack, Suzanna E. Lewis, Phillip Lord, Ann-Marie Mallon, Nishanth Marthandan, Hiroshi Masuya, Ruth McNally, Alexander Mehrle, Norman Morrison, Sandra Orchard, John Quackenbush, James M. Reecy, Donald G. Robertson, Philippe Rocca-Serra, Henry Rodriguez, Heiko Rosenfelder, Javier Santoyo-Lopez, Richard H. Scheuermann, Daniel Schober, Barry Smith & Jason Snape - 2008 - Nature Biotechnology 26 (8):889-896.
    Throughout the biological and biomedical sciences there is a growing need for, prescriptive ‘minimum information’ (MI) checklists specifying the key information to include when reporting experimental results are beginning to find favor with experimentalists, analysts, publishers and funders alike. Such checklists aim to ensure that methods, data, analyses and results are described to a level sufficient to support the unambiguous interpretation, sophisticated search, reanalysis and experimental corroboration and reuse of data sets, facilitating the extraction of maximum value from data sets (...)
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  • OBCS: The Ontology of Biological and Clinical Statistics.Jie Zheng, Marcelline R. Harris, Anna Maria Masci, Yu Lin, Alfred Hero, Barry Smith & Yongqun He - 2014 - Proceedings of the Fifth International Conference on Biomedical Ontology 1327:65.
    Statistics play a critical role in biological and clinical research. To promote logically consistent representation and classification of statistical entities, we have developed the Ontology of Biological and Clinical Statistics (OBCS). OBCS extends the Ontology of Biomedical Investigations (OBI), an OBO Foundry ontology supported by some 20 communities. Currently, OBCS contains 686 terms, including 381 classes imported from OBI and 147 classes specific to OBCS. The goal of this paper is to present OBCS for community critique and to describe a (...)
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  • MIREOT: The Minimum Information to Reference an External Ontology Term.Mélanie Courtot, Frank Gibson, Allyson L. Lister, James Malone, Daniel Schober, Ryan R. Brinkman & Alan Ruttenberg - 2011 - Applied Ontology 6 (1):23-33.
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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 & Others - 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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  • 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 groups who develop and use ontologies and (...)
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