Semantic Decision Tables: Self-organizing and Reorganizable Decision Tables

A Semantic Decision Table (SDT) provides a means to captureand examinedecision makers' concepts, as well as a tool for refiningtheir decision knowledge and facilitating knowledgesharingin a scalablemanner. One challenge SDT faces is to organize decision resources represented in a tabular format based on the user's needs at different levels. It is important to make it self organizedand automatically reorganizedwhen the requirements are updated. This paper describes the ongoing research on SDT and its tool that supports the self organizations and automatic reorganization of decision tables. We argue that simplicity, precision, and flexibilityare the key issues to respond to the paper challenge. We propose a novel combination of the principles of Decision Support and Database Modeling, together with the modern technologies in Ontology Engineering, in the adaptive s elf- o rganization and a utomatic r eorganization procedures (SOAR).