Rex M. Jakobovits

Motivation and Organizational Principles for Anatomical Knowledge Representation: The Digital Anatomist Symbolic Knowledge Base

OBJECTIVE Conceptualization of the physical objects and spaces that constitute the human body at the macroscopic level of organization, specified as a machine-parseable ontology that, in its human-readable form, is comprehensible to both expert and novice users of anatomical information. DESIGN Conceived as an anatomical enhancement of the UMLS Semantic Network and Metathesaurus, the anatomical ontology was formulated by specifying defining attributes and differentia for classes and subclasses of physical anatomical entities based on their partitive and spatial relationships. The validity of the classification was assessed by instantiating the ontology for the thorax. Several transitive relationships were used for symbolically modeling aspects of the physical organization of the thorax. RESULTS By declaring Organ as the macroscopic organizational unit of the body, and defining the entities that constitute organs and higher level entities constituted by organs, all anatomical entities could be assigned to one of three top level classes (Anatomical structure, Anatomical spatial entity and Body substance). The ontology accommodates both the systemic and regional (topographical) views of anatomy, as well as diverse clinical naming conventions of anatomical entities. CONCLUSIONS The ontology formulated for the thorax is extendible to microscopic and cellular levels, as well as to other body parts, in that its classes subsume essentially all anatomical entities that constitute the body. Explicit definitions of these entities and their relationships provide the first requirement for standards in anatomical concept representation. Conceived from an anatomical viewpoint, the ontology can be generalized and mapped to other biomedical domains and problem solving tasks that require anatomical knowledge.

WIRM: An Open Source Toolkit for Building Biomedical Web Applications

This article describes an innovative software toolkit that allows the creation of web applications that facilitate the acquisition, integration, and dissemination of multimedia biomedical data over the web, thereby reducing the cost of knowledge sharing. There is a lack of high-level web application development tools suitable for use by researchers, clinicians, and educators who are not skilled programmers. Our Web Interfacing Repository Manager (WIRM) is a software toolkit that reduces the complexity of building custom biomedical web applications. WIRMs visual modeling tools enable domain experts to describe the structure of their knowledge, from which WIRM automatically generates full-featured, customizable content management systems.

A Visual Database Environment for Scientific Research

Abstract This paper describes a visual database environment designed to be used for scientific research in the imaging sciences. It provides hierarchical relational structures that allow the user to model data as entities possessing properties, parts and relationships, and it supports multi-level queries on these structures. A schema constructor interface allows users to define for each structure, not only its components, but also its visualization, which is built from its components using graphical primitives. Finally, an experiment management subsystem allows users to construct and run computational experiments that apply imaging operators to data from the database. The experiment management system keeps track of the experimental procedures developed by the user and the results generated by executing these procedures.

Implementing multilevel queries in a database environment for vision research

The database environment for vision research (DEVR) is an entity-oriented scientific database system based on a hierarchical relational data model (HRS). This paper describes the design and implementation of the data definition language, the application programmers interface, and the query mechanism of the DEVR system. DEVR provides a dynamic data definition language for modeling image and vision data, which can be integrated with existing image processing and vision applications. Schema definitions can be fully interleaved with data manipulation, without requiring recompilation. In addition, DEVR provides a powerful application programmers interface that regulates data access and schema definition, maintains indexes, and enforces type safety and data integrity. The system supports multi-level queries based on recursive constraint trees. A set of HRS entities of a given type is filtered through a network of constraints corresponding to the parts, properties, and relations of that type. Queries can be constructed interactively with a menu-drive interface, or they can be dynamically generated within a vision application using the programmers interface. Query objects are persistent and reusable. Users may keep libraries of query templates, which can be built incrementally, tested separately, cloned, and linked together to form more complex queries.