Semantic Correspondence in Federated Life Science Data Integration Systems

Abstract

For execution of complex biological queries, data integration systems often use several intermediate data sources because the domain coverage of individual sources is limited. Quality of intermediate sources differs greatly based on the method used for curation, frequency of updates and breadth of domain coverage, which affects the quality of the results. Therefore, integration systems should provide data provenance; i.e. information about the path used to obtain every record in the result. Furthermore, since query capabilities of web-accessible sources are limited, integration systems need to support refinement queries of finer granularity issued over the integrated data. However, unlike the individual sources, integration systems have to handle the absence of data and conflicts in the integrated data caused by inconsistencies among the sources. This paper describes the solution proposed by BACIIS, the Biological and Chemical Information Integration System, for providing data provenance and for supporting refinement queries over integrated data. Semantic correspondence between records from different sources is defined based on the links connecting these data sources including cross-references. Two characteristics of semantic correspondence, namely degree and cardinality, are identified based on the closeness of the links that exist between data records and based on the mappings between domains of data records respectively. An algorithm based on semantic correspondence is presented to handle absence of data and conflicts in the integrated data.