Visual Querying with Ontologies for Distributed Statistical Databases

In this paper we describe a visual, ontology-based query paradigm. It has two novel features: visually specifying aggregate table queries and table layout in a single process, and providing users with an ontology guide for formulating statistical data analysis tasks as table queries which are composed of the terms defined in ontologies. We describe the role of the fundamental concept of ontology in the content representation of distributed databases with large numbers of multi-valued attributes, along with the methods and techniques developed for representing and manipulating ontologies, and for understanding semantics of database contents and query formulation and processing.

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