Terminologia Anatomica; Considered from the Perspective of Next-Generation Knowledge Sources

This report examines the semantic structure of Terminologia Anatomica, taking one randomly selected page as an example. The focus of analysis is the meaning imparted to an anatomical term by virtue of its location within the structured list. Terminologia’s structure expressed through hierarchies of headings, varied typographical styles, indentations and an alphanumeric code implies specific relationships between the terms embedded in the list. Together, terms and relationships can potentially capture essential elements of anatomical knowledge. The analysis focuses on these knowledge elements and evaluates the consistency and logic in their representation. Most critical of these elements are class inclusion and part-whole relationships, which are implied, rather than explicitly modeled by Terminologia. This limits the use of the term list to those who have some knowledge of anatomy and excludes computer programs from navigating through the terminology. Assuring consistency in the explicit representation of anatomical relationships would facilitate adoption of Terminologia as the anatomical standard by the various controlled medical terminology (CMT) projects. These projects are motivated by the need for computerizing the patient record, and their aim is to generate machineunderstandable representations of biomedical concepts, including anatomy. Because of the lack of a consistent and explicit representation of anatomy, each of these CMTs has generated it own anatomy model. None of these models is compatible with each other, yet each is consistent with textbook descriptions of anatomy. The analysis of the semantic structure of Terminologia Anatomica leads to some suggestions for enhancing the term list in ways that would facilitate its adoption as the standard for anatomical knowledge representation in biomedical informatics

The Role of Foundational Relations in the Alignment of Biomedical Ontologies

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 partof 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

Imaging Informatics and the Human Brain Project: the Role of Structure, Review

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Knowledge Base Version Reintegration

Given two versions of a knowledge base (KB), independently modified, we investigated the problem of incorporating changes made to one KB version into the other. We have implemented a system that will perform such a reintegration, autonomously, using predetermined user preferences. This effort has lead to a greater insight into the version reintegration problem and has highlighted those areas where user intervention would be the most beneficial in a semi-autonomous system

Symbolic modeling of structural relationships in the Foundational Model of Anatomy

The need for a sharable resource that can provide deep anatomical knowledge and support inference for biomedical applications has recently been the driving force in the creation of biomedical ontologies. Previous attempts at the symbolic representation of anatomical relationships necessary for such ontologies have been largely limited to general partonomy and class subsumption. We propose an ontology of anatomical relationships beyond class assignments and generic part-whole relations and illustrate the inheritance of structural attributes in the Digital Anatomist Foundational Model of Anatomy. Our purpose is to generate a symbolic model that accommodates all structural relationships and physical properties required to comprehensively and explicitly describe the physical organization of the human body

The Potential of the Digital Anatomist Foundational Model for Assuring Consistency in UMLS Sources

Inconsistent anatomical concept representation can be identified in anatomy textbooks and hard copy term lists, as well as in UMLS source vocabularies and other controlled medical terminologies. In this report we select some examples of inconsistent representations of anatomical concepts, and illustrate how these inconsistencies can be explained and reconciled by the Digital Anatomist Foundational Model1. We use this process for gaining a measure of the validity of the logic-based Model

A formal theory for spatial representation and reasoning in biomedical ontologies

Objective: 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. Method and Materials: 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 BIT+Cl (Basic Inclusion Theory for Classes). 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. Results: 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. Conclusion: 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 is along these lines is required

The Foundational Model of Anatomy Ontology

Anatomy is the structure of biological organisms. The term also denotes the scientific discipline devoted to the study of anatomical entities and the structural and developmental relations that obtain among these entities during the lifespan of an organism. Anatomical entities are the independent continuants of biomedical reality on which physiological and disease processes depend, and which, in response to etiological agents, can transform themselves into pathological entities. For these reasons, hard copy and in silico information resources in virtually all fields of biology and medicine, as a rule, make extensive reference to anatomical entities. Because of the lack of a generalizable, computable representation of anatomy, developers of computable terminologies and ontologies in clinical medicine and biomedical research represented anatomy from their own more or less divergent viewpoints. The resulting heterogeneity presents a formidable impediment to correlating human anatomy not only across computational resources but also with the anatomy of model organisms used in biomedical experimentation. The Foundational Model of Anatomy (FMA) is being developed to fill the need for a generalizable anatomy ontology, which can be used and adapted by any computer-based application that requires anatomical information. Moreover it is evolving into a standard reference for divergent views of anatomy and a template for representing the anatomy of animals. A distinction is made between the FMA ontology as a theory of anatomy and the implementation of this theory as the FMA artifact. In either sense of the term, the FMA is a spatial-structural ontology of the entities and relations which together form the phenotypic structure of the human organism at all biologically salient levels of granularity. Making use of explicit ontological principles and sound methods, it is designed to be understandable by human beings and navigable by computers. The FMA’s ontological structure provides for machine-based inference, enabling powerful computational tools of the future to reason with biomedical data

Profile of On-Line Anatomy Information Resources: Design and Instructional Implications

This study is based on a review of 40 on-line anatomy web resources compiled from sites selected from our own searches as well as sites reviewed and published by an external group (Voiglio et al., 1999, Surg. Radiol. Anat. 21:65-68; Frasca et al., 2000, Surg. Radiol. Anat. 22:107-110). The purpose of our survey was to propose criteria by which anatomy educators could judge the characteristics of the currently available web-based resources for incorporation into the courses they teach. Each site was reviewed and scored based on a survey matrix that included four main categories: 1). site background information, 2). content components, 3). interactivity features, and 4). user interface design components. The average score of the reviewed sites was 3.3 of the total possible score of 10, indicating the limited use of computer-based design features by the majority of sites. We found, however, a number of programs in each of the survey categories that could serve as prototypes for designing future on-line anatomy resources. From the survey we conclude that various design features are less important than the comprehensiveness, depth, and logical organization of content. We suggest that the content should be sufficient for supporting explicitly defined educational objectives, which should target specific end-user populations. The majority of anatomy programs currently accessible on-line fall short of these requirements. There is a need for a coordinated and synergistic effort to generate a comprehensive anatomical information resource that is of sufficient quality and depth to support higher levels of learning beyond the memorization of structure names. Such a resource is a prerequisite for meaningful on-line anatomy education

An Intuitive Graphical Query Interface for Protégé Knowledge Bases

Emily is a graphical query engine for Protégé knowledge bases that was developed by the Structural Informatics Group (SIG) at the University of Washington. Currently this application is adapted for a specific knowledge model, the Foundational Model of Anatomy (FMA) [1], but it could readily be generalized for use with other Protégé knowledge bases. In developing the Emily query interface, our intent was to provide a tool that was simple and intuitive to use, like the Queries tab provided with Protégé, but with improved information retrieval capabilities. Although some more advanced query mechanisms exist, currently they are too complicated for non-expert end users. The Algernon tab [2], for example, provides extensive Protégé query capabilities but requires users to learn a query scripting language. We sought to develop a query interface that was intuitive enough for end users to operate, with only minor instruction, yet was powerful enough to gather interesting information from a knowledge base that was not easily attained by browsing alone