pax

Data available on-line today is spread over heterogeneous data sources like traditional databases or sources of various forms containing unstructured and semistructured data. Obviously, the ``technical'' availability alone is not at all sufficient for making meaningful use of the existing information, and thus the problem of effectively and efficiently accessing and querying heterogeneous data is an important research issue. One main approach is to integrate the data sources and offer users an a priori defined global schema. Alternatively, there are approaches which implement tools for giving users the possibility to define the global schema themselves. In this thesis, we propose a new approach where heterogeneous sources can be queried through a unified interface, and underlying sources are integrated by means of a query language only. Firstly, we give a taxonomy for querying and integrating heterogeneous data sources. Secondly, we design SINGAPORE, a system for querying and integrating structural heterogeneous data sources, i.e. structured, semistructured and unstructured data sources. The system allows the formulation of a full range of queries, from exact to fuzzy ones, and is extensible at runtime, i.e. the number of underlying sources is able to increase or decrease at runtime. Thirdly, we define a measure called query explorativeness which characterizes the work of query systems for mapping input queries into more precise, so called target queries. We show that this measure is important today, since systems with a high query explorativeness are suitable when users information need is not well defined. Fourthly, we present the way query explorativeness is implemented in our system, by combining techniques form information retrieval and database systems. Finally, we present the prototypical implementation of SINGAPORE.

A query based approach for integrating heterogeneous data s...

A query based approach for integrating heterogeneous data sources

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