Ontology Focusing: Knowledge-enriched Databases on Demand

TL;DR

This paper introduces a framework called focusing that enables semi-automatic, knowledge-enriched database schema design from ontologies, formalizing the process and analyzing its computational complexity across different description logics.

Contribution

It formalizes the focusing process for ontology-based database schema design, analyzes computational problems, and instantiates the framework with various description logics.

Findings

Decidability and complexity results for focusing-related problems

Formalization of schema generation and query answering from ontologies

Solutions to classical decision problems in description logics

Abstract

We propose a novel framework to facilitate the on-demand design of data-centric systems by exploiting domain knowledge from an existing ontology. Its key ingredient is a process that we call focusing, which allows to obtain a schema for a (possibly knowledge-enriched) database semi-automatically, given an ontology and a specification of the scope of the desired system. We formalize the inputs and outputs of focusing, and identify relevant computational problems: finding a schema via focusing, testing its consistency, and answering queries in the knowledge-enriched databases it produces. These definitions are fully independent of the ontology language. We then instantiate the framework using selected description logics as ontology languages, and popular classes of queries for specifying the scope of the system. For several representative combinations, we study the decidability and complexity of the identified computational problems. As a by-product, we isolate (and solve) variants of classical decision problems in description logics, that are interesting in their own right.