A tool for filtering large conceptual schemas

Abstract

The wealth of knowledge the conceptual schemas of many real-world information systems contain makes them very useful to their potential target audience. However, the sheer size of those schemas makes it difficult to extract knowledge from them. There are many information system development activities in which people needs to get a piece of the knowledge contained in a large conceptual schema. We present an information filtering tool in which a user focuses on one or more entity types of interest for her task at hand, and the tool automatically filters the schema in order to obtain a reduced conceptual schema including a set of entity and relationship types (and other knowledge) relevant to that task. © 2011 Springer-Verlag.