Bridging the data integration gap

Abstract

The integration of multiple autonomous and heterogeneous data sources (both across the web and via a company intranet) has received much attention throughout the years, particularly due to its many applications in the fields of Artificial Intelligence and medical research data sharing. Data integration systems embody this work and have come very far in the past twenty years. The problem of designing such systems is characterized by a number of issues that are interesting from a theoretical point of view: answering queries using logical views, query containment and completeness, automatic integration of existing data sources via schema mapping tools, etc. In this work we discuss these issues, compare and contrast various proposed solutions (federated database systems and data warehouses), and finally propose a novel extension of the MVC (model, view, controller) web-based framework that allows for the rapid development and implementation of data integration systems solutions suitable for use on the web.