http://precedings.nature.com/tags/Basic%20Formal%20Ontology Recently posted documents tagged with 'Basic Formal Ontology' Nature Publishing Group en Nature Precedings http://precedings.nature.com/images/header_logo.gif http://precedings.nature.com http://dx.doi.org/10.1038/npre.2009.4001.1 The syntax of LBFO represents the initial step toward the creation of a rigorously characterized, recursively defined, artificial language for the sole purpose of ontology development. The underlying idea is that maximally fruitful application of ontology requires accurate representation of reality in accordance with current textbook science. Hence, creating a robust, accurate representation of reality is a fundamental concern. An ontology represents general types of entities and relations between them. A domain ontology represents the general types and relations for a given domain of research. A top-level ontology represents the general types of entities in any domain of research. Ontologies serve many purposes in computerized collection, management, and storage of data. These applications include enhancement of storage and retrieval in a data system, integration of diverse systems, integration of semantic content on the web, and annotation of publications in a library setting.Successful application of ontologies has led to the creation of languages with the special purpose of implementing ontologies. A formalized ontology is an ontology expressed in accordance with the grammatical formation rules of an artificial language. Some existing ontology languages have been developed in order to serve specific functions that require expressibility limitations and expression of information in a manner that contributes to human misunderstanding and error. The most potentially detrimental effect is risked when an ontology is constructed in a language designed exclusively for computerized implementation. The result is a skewed representation of salient features of reality. An ontology development language has two purposes: one is to represent reality as accurately and completely as possible, the other is to achieve this in a manner that facilitates computerized implementation: these goals conflict. Validation requires expert human consensus, hence, an ontology should be developed in a language that is understandable to domain experts. However, such a language must be computer tractable, i.e., there must be a correspondence between the information expressed with a sentence and its grammatical structure such that information can be processed on the basis of syntax alone. LBFO will facilitate providing definitions and characterizations of features of reality in a way conformant with Basic Formal Ontology (BFO) thus ensuring maximal rigor and clarity. Since LBFO is a multi-sorted language, LBFO has resources to represent the ontological categories found in BFO and the universals defined in their terms in an economical and at the same time user-friendly way. BFO is a realist ontology in that it recognizes universals as an part of the world. BFO also recognizes the existence of both processes and continuants. A continuant is an individual that exists in full at each point in time in which it exists, a process is an individual that exists in stages and happens through time. Unlike a continuant, a process cannot be identified with any single stage at which it exists at a specific point in time. Capitalized variables range over universals, while lower-case variables range over individuals. Universal constants are upper-case. Individual constants are lower-case. The syntax of LBFO also distinguishes in a straightforward manner between variables for continuants, processes, and times. The syntax of LBFO contains precisely expressed grammatical-formation rules, so that its variables cannot be combined in a manner that results in category errors. The predicates of LBFO are such that the ontological category from which terms representing entities can be taken as arguments is specified in advance. Sentences which express category errors are not grammatically correct in LBFO.Since the demand for implementation often outstrips the demand for accurate representation, stand-alone ontologies are often left by the wayside. LBFO can serve as a bridge between domain experts, knowledge engineers, and implementation languages. The semantic apparatus of an FOL system serves as the basis for the models developed for implementation languages such as OWL and RDF. FOL is also a segregated dialect of Common Logic so there is a link to that international standard; hence, there is potential to develop middle-ware that maps LBFO to the variety of implementation languages that exist both now and in the future. Though there is much work to be done in perfecting LBFO, this first step in the process provides hope for achieving the goal of facilitating maximally accurate, rigorous representations of general features of reality. http://dx.doi.org/10.1038/npre.2009.4001.1 Mon, 23 Nov 2009 15:36:02 UTC LBFO: toward an artificial language for ontology development doi:10.1038/npre.2009.4001.1 2009-11-23 Leonard F. Jacuzzo Nature Precedings 2009-11-23T15:36:02Z Poster Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2009.3960.1 Definitive diagnosis of malaria requires the demonstration through laboratory tests of the presence within the patient of malaria parasites or their components. Since malaria parasites can be present even in the absence of malaria, and since symptoms of malaria can be manifested even in the absence of malaria parasites, malaria diagnosis raises important issues for the adequate understanding of disease, etiology and diagnosis. One approach to the resolution of these issues adopts a realist view, according to which the needed clarifications will be derived from a careful representation of the entities on the side of the patient which form the ultimate truthmakers for clinical statements. We address a challenge to this realist approach relating to the diagnosis of malaria, and show how this challenge can be resolved by appeal to Basic Formal Ontology (BFO) and to the Ontology for General Medical Science (OGMS) constructed in its terms. http://dx.doi.org/10.1038/npre.2009.3960.1 Mon, 09 Nov 2009 10:30:10 UTC Malaria Diagnosis and the Plasmodium Life Cycle: the BFO Perspective doi:10.1038/npre.2009.3960.1 2009-11-09 Werner Ceusters Nature Precedings 2009-11-09T10:30:10Z Manuscript Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2008.2373.1 Effective translational research requires automated analysis of large datasets collected by multiple researchers working at multiple locations. Reliable, machine interpretation of-—and reasoning with—-large datasets assembled at different times and places by different researchers requires standard representations of data. These representations are controlled, structured vocabularies also known as ontologies. By far, the most successful ontology is the Gene Ontology (GO), used by bioinformatics researchers to annotate genomics data. However, to address the phenotype side of translational research will require annotation of electronic medical record data and clinical research data with a clinical-phenotype ontology analogous to GO. One leading candidate for this ontology is SNOMED-CT (SNCT). However, GO and SNCT are incompatible representations. GO is based on an upper level ontology called Basic Formal Ontology (BFO). In this work, we aligned the upper level of SNCT with BFO to enhance its suitability for translational research. Most (14/19 or 74%) of the top-level concepts of SNCT can be fitted into the framework of BFO, but only after significant reorganization. An important concept that does not align is Clinical Finding, which is intended to comprehend diseases and signs and symptoms of disease. However, a finding of disease (epistemology) is not the same thing as a disease (ontology). This discrepancy between SNCT and BFO is important to consider further. Another key result is that children of the top-level concepts do not necessarily follow their parents into BFO, and thus one must align each SNCT concept independently. Future work is to align the next level of SNCT (345 concepts) with BFO. http://dx.doi.org/10.1038/npre.2008.2373.1 Wed, 08 Oct 2008 09:20:06 UTC Aligning the top-level of SNOMED-CT with Basic Formal Ontology doi:10.1038/npre.2008.2373.1 2008-10-08 William Hogan Nature Precedings 2008-10-08T09:20:06Z Poster Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://precedings.nature.com/documents/1941/version/1 Numerous research groups are now utilizing Basic Formal Ontology (BFO) as an upper-level framework to assist in the organization and integration of biomedical information. This paper provides elucidation of the three BFO categories of function, role, and disposition, and considers two proposed sub-categories of artifactual function and bio-logical function. The motivation is to help advance the coherent treatment of functions, roles, and dispositions, to help provide the potential for more detailed classification, and to shed light on BFO’s general structure and use. http://precedings.nature.com/documents/1941/version/1 Tue, 03 Jun 2008 09:33:06 UTC Function, Role, and Disposition in Basic Formal Ontology hdl:10101/npre.2008.1941.1 2008-06-03 Robert Arp Nature Precedings 2008-06-03T09:33:06Z Manuscript Bioinformatics http://creativecommons.org/licenses/by/3.0/