Modeling controlled vocabularies using OODBs and multilevel area diagrams

Abstract

A Controlled Vocabulary (CV) is a software system of domain knowledge that consolidates and unifies the terminology of a large application domain. With a common, centralized CV, costly and time-consuming translations can be eliminated between pairs of organizations and pairs of software systems. Unfortunately, the more knowledge we put into a CV, the harder it is to understand and maintain it. In this dissertation, a comprehensive theoretical methodology for modeling CVs using Object-Oriented Database (OODB) technology is presented. We present two methods for representing a semantic network CV as an equivalent OODB, which we call an Object-Oriented Vocabulary Repository (OOVR). The first method, based on a structural analysis and partitioning of the CV, yields an OODB with a very concise schema, referred to as the OOVR schema. Due to its compact size, the schema can be displayed on one or a few computer screens and serves as an aid for comprehending and maintaining the CV. A program called the Object-Oriented Vocabulary Repository Generator (OOVR Generator) has been built to automatically generate an OOVR for a given semantic network CV. Our second methodology results in a larger schema, which, however, serves as an important tool for browsing and navigation through a CV. The OODB schemas created by both methodologies provide important abstract views of CVs. We have also defined a new type of semantic relationships called IS-A\u27 in the context of an OOVR representation. The IS-A\u27 relationships are defined on OOVR schemas to reflect certain important IS-A relationships in the underlying CV. The two OOVR representations exhibit several interesting theoretical characteristics which are formally proven in this dissertation. To provide an environment with several abstract views of a CV, we also define a paradigm called Multilevel Area Diagrams (MLADs). A MLAD is a collection of different partitions of increasing detail and decreasing abstraction derived from a CV. Users can browse at one level and then switch to another level to continue their navigation. Examples of browsing sessions are presented to show that the MLAD paradigm provides processing capabilities beyond those of a traditional object-oriented representation of a vocabulary

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