6 found
  1. 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 as adding semantic expressivity to (...)
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  2. OBO Foundry in 2021: Operationalizing Open Data Principles to Evaluate Ontologies.Rebecca C. Jackson, Nicolas Matentzoglu, James A. Overton, Randi Vita, James P. Balhoff, Pier Luigi Buttigieg, Seth Carbon, Melanie Courtot, Alexander D. Diehl, Damion Dooley, William Duncan, Nomi L. Harris, Melissa A. Haendel, Suzanna E. Lewis, Darren A. Natale, David Osumi-Sutherland, Alan Ruttenberg, Lynn M. Schriml, Barry Smith, Christian J. Stoeckert, Nicole A. Vasilevsky, Ramona L. Walls, Jie Zheng, Christopher J. Mungall & Bjoern Peters - 2021 - BioaRxiv.
    Biological ontologies are used to organize, curate, and interpret the vast quantities of data arising from biological experiments. While this works well when using a single ontology, integrating multiple ontologies can be problematic, as they are developed independently, which can lead to incompatibilities. The Open Biological and Biomedical Ontologies Foundry was created to address this by facilitating the development, harmonization, application, and sharing of ontologies, guided by a set of overarching principles. One challenge in reaching these goals was that the (...)
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    “Explain” in scientific discourse.James A. Overton - 2013 - Synthese 190 (8):1383-1405.
    The philosophical literature on scientific explanation contains a striking diversity of accounts. I use novel empirical methods to address this fragmentation and assess the importance and generality of explanation in science. My evidence base is a set of 781 articles from one year of the journal Science, and I begin by applying text mining techniques to discover patterns in the usage of “explain” and other words of philosophical interest. I then use random sampling from the data set to develop and (...)
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    Mechanisms, Types, and Abstractions.James A. Overton - 2011 - Philosophy of Science 78 (5):941-954.
    Machamer, Darden, and Craver's account of the nature and role of mechanisms in the special sciences has been very influential. Unfortunately, a confusing array of ontic, epistemic, and pragmatic distinctions is required to individuate their mechanisms, mechanism schemata, and mechanism sketches. I diagnose this as a conflation of token-level causal relations with type-level relations. I propose instead that a mechanism is an abstraction that relates entity types and activity types on the model of a directed graph. Mechanisms have an ontic (...)
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    Open Biomedical Ontologies applied to prostate cancer.James A. Overton, Cesare Romagnoli & Rethy Chhem - 2011 - Applied ontology 6 (1):35-51.
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    Explanation in Science.James A. Overton - unknown
    Scientific explanation is an important goal of scientific practise. Philosophers have proposed a striking diversity of seemingly incompatible accounts of explanation, from deductive-nomological to statistical relevance, unification, pragmatic, causal-mechanical, mechanistic, causal intervention, asymptotic, and model-based accounts. In this dissertation I apply two novel methods to reexamine our evidence about scientific explanation in practise and thereby address the fragmentation of philosophical accounts. I start by collecting a data set of 781 articles from one year of the journal Science. Using automated text (...)
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