A Knowledge-Based Approach for Selecting Information Sources
  Through the Internet and the World-Wide Web, a vast number of information
sources has become available, which offer information on various subjects by
different providers, often in heterogeneous formats. This calls for tools and
methods for building an advanced information-processing infrastructure. One
issue in this area is the selection of suitable information sources in query
answering. In this paper, we present a knowledge-based approach to this
problem, in the setting where one among a set of information sources
(prototypically, data repositories) should be selected for evaluating a user
query. We use extended logic programs (ELPs) to represent rich descriptions of
the information sources, an underlying domain theory, and user queries in a
formal query language (here, XML-QL, but other languages can be handled as
well). Moreover, we use ELPs for declarative query analysis and generation of a
query description. Central to our approach are declarative source-selection
programs, for which we define syntax and semantics. Due to the structured
nature of the considered data items, the semantics of such programs must
carefully respect implicit context information in source-selection rules, and
furthermore combine it with possible user preferences. A prototype
implementation of our approach has been realized exploiting the DLV KR system
and its plp front-end for prioritized ELPs. We describe a representative
example involving specific movie databases, and report about experimental
results.
