Using cross-lingual information to cope with underspecification in formal ontologies

Description logics and other formal devices are frequently used as means for preventing or detecting mistakes in ontologies. Some of these devices are also capable of inferring the existence of inter-concept relationships that have not been explicitly entered into an ontology. A prerequisite, however, is that this information can be derived from those formal definitions of concepts and relationships which are included within the ontology. In this paper, we present a novel algorithm that is able to suggest relationships among existing concepts in a formal ontology that are not derivable from such formal definitions. The algorithm exploits cross-lingual information that is implicitly present in the collection of terms used in various languages to denote the concepts and relationships at issue. By using a specific experimental design, we are able to quantify the impact of cross-lingual information in coping with underspecification in formal ontologies

Formal ontology for biomedical knowledge systems integration

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 move beyond the level of controlled vocabularies to yield an ontology with the ability to support reasoning applications

Ontology-assisted database integration to support natural language processing and biomedical data-mining

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

Ontology and medical terminology: Why description logics are not enough

Ontology is currently perceived as the solution of first resort for all problems related to biomedical terminology, and the use of description logics is seen as a minimal requirement on adequate ontology-based systems. Contrary to common conceptions, however, description logics alone are not able to prevent incorrect representations; this is because they do not come with a theory indicating what is computed by using them, just as classical arithmetic does not tell us anything about the entities that are added or subtracted. In this paper we shall show that ontology is indeed an essential part of any solution to the problems of medical terminology – but only if it is understood in the right sort of way. Ontological engineering, we shall argue, should in every case go hand in hand with a sound ontological theory

Ontological theory for ontological engineering: Biomedical systems information integration

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 will become correspondingly difficult to maintain. While descriptive semantic representations are certainly a necessary component to any adequate ontology-based system, so long as ontology engineers rely solely on semantic information, without a sound ontological theory informing their modeling decisions, this goal will surely remain out of reach. In this paper we describe how Language and Computing nv (L&C), along with The Institute for Formal Ontology and Medical Information Sciences (IFOMIS), are working towards developing and implementing just such a theory, combining the open software architecture of L&C’s LinkSuiteTM with the philosophical rigor of IFOMIS’s Basic Formal Ontology. In this way we aim to move beyond the more or less simple controlled vocabularies that have dominated the industry to date

Mistakes in medical ontologies: Where do they come from and how can they be detected?

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

Was die philosophische Ontologie zur biomedizinischen Informatik beitragen kann

Die biomedizinische Forschung hat ein Kommunikationsproblem. Um die Ergebnisse ihrer Arbeit darzustellen, greifen einzelne Forschergruppen auf unterschiedliche und oft inkompatible Terminologien zurück. Für den Fortschritt der modernen Biomedizin ist die Integration dieser Ergebnisse jedoch unabdingbar

Verso una filosofia al servizio dell' industria: l'utilità dell' ontologia analitica per l'informatica medica

La ricerca medica è afflitta da un problema di comunicazione. Comunità distinte di ricercatori si servono di terminologie diverse e spesso incompatibili per esprimere i risultati del loro lavoro, generando in questo modo problemi di integrazione tra database ogniqualvolta si presenti la necessità di inserire i dati medici nei computer. In un primo momento i problemi di integrazione tra database venivano risolti caso per caso, in seguito si è fatta strada l’idea di realizzare un’unica tassonomia di riferimento in cui tradurre, una volta soltanto, tutti i vari sistemi di classificazione. Funzionando come una sorta di lingua franca, questa tassonomia di riferimento avrebbe automaticamente garantito ad ogni database calibrato su di essa la compatibilità con tutti gli altri. È curioso come gli informatici abbiano chiamato il sistema centrale di classificazione che stavano proponendo un’ontologia, riconoscendo così l’esistenza di più di un’affinità tra il lavoro di costruzione che un simile sistema comportava e la vecchia metafisica. Il presente articolo descrive un tentativo di sfruttare le risorse della filosofia per risolvere problemi che sorgono, in particolar modo, nel campo dell’integrazione delle terminologie mediche. Vengono delineati in particolare i contorni di un’iniziativa che è il frutto della collaborazione tra l’Istituto di Ontologia Formale e Informatica Medica e la società di software belga Language and Computing, iniziativa che prevede la messa alla prova di un’ontologia fondata su solidi principi filosofici nel contesto di potenti strumenti software per l’elaborazione di testo medico