Semantic Integration of Semistructured and Structured Data Sources

Providing an integrated access to multiple heterogeneous sources is a challenging issue in global information systems for cooperation and interoperability. In this context, two fundamental problems arise. First, how to determine if the sources contain semantically related information, that is, information related to the same or similar real-world concept(s). Second, how to handle semantic heterogeneity to support integration and uniform query interfaces. Complicating factors with respect to conventional view integration techniques are related to the fact that the sources to be integrated already exist and that semantic heterogeneity occurs on the large-scale, involving terminology, structure, and context of the involved sources, with respect to geographical, organizational, and functional aspects related to information use. Moreover, to meet the requirements of global, Internet-based information systems, it is important that tools developed for supporting these activities are semi-automatic and scalable as much as possible. The goal of this paper is to describe the MOMIS [4, 5] (Mediator envirOnment for Multiple Information Sources) approach to the integration and query of multiple, heterogeneous information sources, containing structured and semistructured data. MOMIS has been conceived as a joint collaboration between University of Milano and Modena in the framework of the INTERDATA national research project, aiming at providing methods and tools for data management in Internet-based information systems. Like other integration projects [1, 10, 14], MOMIS follows a “semantic approach” to information integration based on the conceptual schema, or metadata, of the information sources, and on the following architectural elements: i) a common object-oriented data model, defined according to the ODLI3 language, to describe source schemas for integration purposes. The data model and ODLI3 have been defined in MOMIS as subset of the ODMG-93 ones, following the proposal for a standard mediator language developed by the I3/POB working group [7]. In addition, ODLI3 introduces new constructors to support the semantic integration process [4, 5]; ii) one or more wrappers, to translate schema descriptions into the common ODLI3 representation; iii) a mediator and a query-processing component, based on two pre-existing tools, namely ARTEMIS [8] and ODB-Tools [3] (available on Internet at http://sparc20.dsi.unimo.it/), to provide an I3 architecture for integration and query optimization. In this paper, we focus on capturing and reasoning about semantic aspects of schema descriptions of heterogeneous information sources for supporting integration and query optimization. Both semistructured and structured data sources are taken into account [5]. A Common Thesaurus is constructed, which has the role of a shared ontology for the information sources. The Common Thesaurus is built by analyzing ODLI3 descriptions of the sources, by exploiting the Description Logics OLCD (Object Language with Complements allowing Descriptive cycles) [2, 6], derived from KL-ONE family [17]. The knowledge in the Common Thesaurus is then exploited for the identification of semantically related information in ODLI3 descriptions of different sources and for their integration at the global level. Mapping rules and integrity constraints are defined at the global level to express the relationships holding between the integrated description and the sources descriptions. ODB-Tools, supporting OLCD and description logic inference techniques, allows the analysis of sources descriptions for generating a consistent Common Thesaurus and provides support for semantic optimization of queries at the global level, based on defined mapping rules and integrity constraints.