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Using Philosophy to Improve the Coherence and Interoperability of Applications Ontologies: A Field Report on the Collaboration of IFOMIS and L&C.
... Una distinción similar a la de objetos y procesos, bajo las denominaciones de "endurants" y "perdurants", se encuentra enBittner & Smith (2004);Simon & Smith (2004);Smith (2005bSmith ( , 2005a. ...
Los fenómenos que suelen asociarse con los sistemas complejos, como la emergencia o la autorregulación, parecen estar envueltos en cierta oscuridad. En primer lugar, las definiciones ofrecidas tienden a ser demasiado generales e inclusivas. En segundo lugar, no se suele aclarar el estatuto de este tipo de fenómenos: si son enteramente debidos al sujeto, o si poseen partes esenciales no reducibles a ningún otro fenómeno. El presente artículo analiza, desde el punto de vista de los sistemas complejos, las nociones de emergencia y autorregulación. Se discuten los principales problemas que estas presentan y se perfilan algunas soluciones que podrían usarse de cara a elaborar una ontología de los sistemas complejos. Haciendo uso de estas soluciones, se proponen algunas definiciones de los principales fenómenos que componen un sistema complejo para, finalmente, ofrecer una definición de este tipo de sistema. Estas definiciones y soluciones se elaboran mediante el uso de herramientas filosóficas tales como la mereología o la teoría de la fundamentación.
... The semantic problems relating to biomedical terminology (polysemy, synonymy, cross-mapping of terminologies, and so forth), too, are well understood – at least in the community of specialized researchers. Now, however, it is time to solve these problems by using the theories and tools that have been developed so far, and that have been tested under laboratory conditions (Simon et al. 2004). This means using the right sort of ontology, i.e. an ontology that is able explicitly and unambiguously to relate coding systems, biomedical terminologies and electronic health care records (including their architecture) to the corresponding instances in reality. ...
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 the naming of genes, proteins, and other molecular structures, considerable efforts are under way to reduce the effects of the different naming conventions which have been spawned by different groups of researchers. Electronic patient records, too, increasingly involve the use of standardized terminologies, and tremendous efforts are currently being devoted to the creation of terminology resources that can meet the needs of a future era of personalized medicine, in which genomic and clinical data can be aligned in such a way that the corresponding information systems become interoperable. Unfortunately, however, these efforts are hampered by a constellation of social, psychological legal and other forces, whose countervailing effects are magnified by constant increases in available data and computing power. Patients, hospitals and governments are reluctant to share data; physicians are reluctant to use computerized forms in preparing patient reports; nurses, physicians and medical researchers in different specialities each insist on using their own terminologies, addressing needs which are rarely consistent with the needs of information integration.
... Examples are: 'no other complications of gastro-esophageal reflux disease'. With the introduction of the new lacks relations – an expanded version of the rationale for which is provided in [9] – we defend, in effect, the thesis that negation is outside the realm of ontology but belongs rather to the domains of logic [10], language [11] and epistemology [12]. Denial of this thesis is symptomatic of what Smith has called 'fantology', i.e. the false belief that the structures of logic, language and information are mirrors of the structure of reality [13]. ...
The paradigm of referent tracking is based on a realist presupposition which rejects so-called negative entities (congenital absent nipple, and the like) as spurious. How, then, can a referent tracking-based Electronic Health Record deal with what are standardly called 'negative findings'? To answer this question we carried out an analysis of some 748 sentences drawn from patient charts and containing some form of negation. Our analysis shows that to deal with these sentences we need to introduce a new ontological relationship between a particular and a universal, which holds when no instance of the universal has a specific qualified ontological relation with the particular. This relation is found to be able to accommodate nearly all occurrences of negative findings in the examined sample, in ways which involve no reference to negative entities.
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 the purposes of making computers understand medical natural language.
We discuss the interplay between applied ontology and the use of web resources in scientific and other domains, and provide an account of how ontologies are implemented computationally. We provide an introduction to the Protégé Ontology Editor, the Semantic Web, the Resource Description Framework (RDF) and the Web Ontology Language (OWL). We illustrated how BFO is used to provide the common architecture for specific domain ontologies, including the Ontology for General Medical Science (OGMS), the Infectious Disease Ontology (IDO), the Information Artifact Ontology (IAO), and the Emotion Ontology (MFO-EM). Before terms and relations provide the starting point for the creation of definition trees in such ontologies according to the Aristotelian strategy for authoring of definitions outlined in Chapter 4. We conclude with a discussion of the role of a top-level ontology such as BFO in facilitating semantic interoperability.
We describe the ontology engineering processes and their supporting technologies at L&C, a company developing intelligent
medical applications based on ontologies. We describe the principal tasks that the modellers of our ontology have to execute,
how they are supported and guided by some specifically ontology-focused management practices, and how (semi-)automated technology
can also aid in their support and guidance, so as to produce a higher quality and quantity of ontology product. The ontology
processes include the development of new structures of concepts and relations, the integration of other ontologies and terminologies,
the integration of the ontology to natural language applications, and the reforming of the current ontology’s formal structure.
The automated supports we talk about include OntoClean, a principled methodology for analyzing ontological properties and
their constraints. We finally note how far we think our ontology technology comes to some proposed desiderata recently given
for “enterprise standard” ontology environments.
Formal principles governing best practices in classification and definition have for too long been neglected in the construction of biomedical ontologies, in ways which have important negative consequences for data integration and ontology alignment. We argue that the use of such principles in ontology construction can serve as a valuable tool in error-detection and also in supporting reliable manual curation. We argue also that such principles are a prerequisite for the successful application of advanced data integration techniques such as ontology-based multi-database querying, automated ontology alignment and ontology-based text-mining. These theses are illustrated by means of a case study of the Gene Ontology, a project of increasing importance within the field of biomedical data integration.
The paper is a contribution to formal ontology. It seeks to use topological means in order to derive ontological laws pertaining to the boundaries and interiors of wholes, to relations of contact and connectedness, to the concepts of surface, point, neighbourhood, and so on. The basis of the theory is mereology, the formal theory of part and whole, a theory which is shown to have a number of advantages, for ontological purposes, over standard treatments of topology in set-theoretic terms. One central goal of the paper is to provide a rigorous formulation of Brentano's thesis to the effect that a boundary can exist as a matter of necessity only as part of a whole of higher dimension of which it is the boundary. It concludes with a brief survey of current applications of mereotopology in areas such as natural-language analysis, geographic information systems, machine vision, naive physics, and database and knowledge engineering.
The rapidly increasing wealth of genomic data has driven the development of tools to assist in the task of representing and processing information about genes, their products and their functions. One of the most important of these tools is the Gene Ontology (GO), which is being developed in tandem with work on a variety of bioinformatics databases. An examination of the structure of GO, however, reveals a number of problems, which we believe can be resolved by taking account of certain organizing principles drawn from philosophical ontology. We shall explore the results of applying such principles to GO with a view to improving GO's consistency and coherence and thus its future applicability in the automated processing of biological data.
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 on the basis of explicit definitions. This scheme also provides a template for modeling pathology, physiological function and genotype-phenotype correlations, and it can thus 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 of these relations and show how these errors can be avoided through adoption of the formalism we describe. We then illustrate how a consistently applied formal treatment of taxonomy and partonomy can support the alignment of ontologies.
We present the details of a methodology for quality assurance in large medical terminologies and describe three algorithms that can help terminology developers and users to identify potential mistakes. The methodology is based in part on linguistic criteria and in part on logical and ontological principles governing sound classifications. We conclude by outlining the results of applying the methodology in the form of a taxonomy different types of errors and potential errors detected in SNOMED-CT.
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. We argue here, however, that its organization manifests certain structural problems, and we describe revisions which we believe are needed if the network is to be maximally successful in realizing its goals of supporting terminology integration.
INTRODUCTION One of the most important tools for the representation and processing of information about gene products and functions is the Gene Ontology (GO). GO is being developed in tandem with work on a variety of biological databases within the framework of the umbrella project OBO (for: open biological ontologies) . It provides a controlled vocabulary for the description of cellular components, molecular functions, and biological processes. Representatives from a number of groups working on model organism databases, including FlyBase (Drosophila), the Saccharomyces Genome Database (SGD) and the Mouse Genome Database (MGD), initiated the Gene Ontology project in 1998 in order to provide a common reference framework for the associated controlled vocabularies. As of June 19, 2003 GO contains 1297 component, 5396 function and 7290 process terms. The total number of GO informal term definitions is 11020. Terms are organized in parent-child hierarchies, indicating either that
KIF Axiomatization of BFO
- W Anderson
- P Grenon
Anderson, W. and Grenon, P.: KIF Axiomatization of BFO. IFOMIS Report 01/04,
http://www.ifomis.uni-leipzig.de (2004)
Revising the UMLS Semantic Network
- A Kumar
- S Schulze-Kremer
Kumar, A., Schulze-Kremer, S.: Revising the UMLS Semantic Network. Proceedings of MedInfo,
September 7-11 2004. forthcoming