A formal theory for spatial representation and reasoning in biomedical ontologies

Department of Biological Structure, University of Washington Seattle, Seattle, Washington, United States
Artificial Intelligence in Medicine (Impact Factor: 2.02). 02/2006; 36(1):1-27. DOI: 10.1016/j.artmed.2005.07.004
Source: PubMed


The objective of this paper is to demonstrate how a formal spatial theory can be used as an important tool for disambiguating the spatial information embodied in biomedical ontologies and for enhancing their automatic reasoning capabilities.
This paper presents a formal theory of parthood and location relations among individuals, called Basic Inclusion Theory (BIT). Since biomedical ontologies are comprised of assertions about classes of individuals (rather than assertions about individuals), we define parthood and location relations among classes in the extended theory Basic Inclusion Theory for Classes (BIT+Cl). We then demonstrate the usefulness of this formal theory for making the logical structure of spatial information more precise in two ontologies concerned with human anatomy: the Foundational Model of Anatomy (FMA) and GALEN.
We find that in both the FMA and GALEN, class-level spatial relations with different logical properties are not always explicitly distinguished. As a result, the spatial information included in these biomedical ontologies is often ambiguous and the possibilities for implementing consistent automatic reasoning within or across ontologies are limited.
Precise formal characterizations of all spatial relations assumed by a biomedical ontology are necessary to ensure that the information embodied in the ontology can be fully and coherently utilized in a computational environment. This paper can be seen as an important beginning step toward achieving this goal, but much more work along these lines is required.

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Available from: Thomas Bittner, Sep 08, 2014
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    • "Because of their generality and significance, spatial relations have received particular attention. Work in this area includes that of Smith et al. (2005), Donnelly et al. (2006) and Bittner (2009). The work of Rosse et al. (2003) on the development of a Foundational Model of Anatomy (FMA) should also be mentioned. "

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    • "The spatial regions of these simultaneously existing instances of the same universal type may or may not overlap. Smith and Rosse (2004) and Donnelly et al. (2005) "
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    ABSTRACT: Introduction: Ontologies define the hierarchical structure and types of object and process entities and their properties, and reflect the nature of the spatial objects and regions involved in processes, relations among processes and spatial entities, and the temporal characteristics of the processes (e.g., Noy, 2004; Smith, 2003). Earth scientists study naturally, experimentally, or simulationally induced processes, and develop conceptual models to help them understand and simulate these processes in the laboratory. The metadata, i.e., information required to understand data, inherent in ontologies, can help the integration, reuse, and interoperability of these models, and enhancement of their functionality. Despite the fact that object, state, process, and event constitute the main ingredients of an ontology (Galton and Worboys, 2005), most ontologies in the earth sciences only focus on the static part of reality, i.e., on objects (e.g., fault, subduction zone) and their properties and relations, leaving the processes (e.g., faulting, subduction), which constitute the dynamic part of reality, out of the picture. In other words, these ontologies ignore change through time and the processes that materialize these changes, despite the fact that earth scientists continuously collect data about individual spatial objects and processes in their research. With the advent of the Web and sophisticated digital data acquisition equipments, which produce an immense volume of data in short periods of time, and cover spatial regions of variable scale, there is an emerging and urgent need for data and information storage and interchange through ontology-based knowledge bases.
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    • "There are some more specific relations (or location with additional conditions) that could be defined. Based on the Loc-In(x, y) and ~Oxy definitions (localization and overlapping relations) from [4] "
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    ABSTRACT: The most emphasized way of representing the knowledge from domains of real world is the ontology, which is undoubtedly the trend of current years. In medical applications such as breast cancer grading, formal ontological representation is of high relevance due to the importance of grading in the prognosis process and to the semantic gap. However, since the representation deals with histopathology images, a spatial representation and reasoning is required. We extend our breast cancer grading ontology with spatial representation and spatial reasoning support and we show how it helps in overcoming the inconsistencies and ambiguities. The ontology is integrated in a cognitive virtual microscope platform guiding the image exploration and assisting the grading process.
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