Cluster Based Integration of Heterogeneous Biological Databases Using the AutoMed Toolkit

Abstract

Abstract. This paper presents an extensible architecture that can be used to support the integration of heterogeneous biological data sets. In our architecture, a clustering approach has been developed to support distributed biological data sources with inconsistent identi cation of biological objects. The architecture uses the AutoMed data integration toolkit to store the schemas of the data sources and the semiautomatically generated transformations from the source data into the data of an integrated warehouse. AutoMed supports bi-directional, extensible transformations which can be used to update the warehouse data as entities change, are added, or are deleted in the data sources.

Data Access and Integration in the ISPIDER Proteomics Grid

“…However, the population and maintenance of a centralised warehouse is often laborious, due to inconsistencies between different data sources, naming schemes, etc. However, where data is obtained from databases, these can use queries to populate the warehouse model, as in GAV, or make use of technologies such as AutoMed, as in BioMap [13].…”

BioFuice: Mapping-Based Data Integration in Bioinformatics

“…As discussed in the introduction, such a schema is hard to create and maintain due to the large number of relevant sources and their high degree of heterogeneity. Some approaches such as ALADIN [LN05], HumMer [Bi05], AutoMed Toolkit [Ma05], and ANNODA [PC05] try to address this problem by using automatic schema matching. Other approaches simply take the union of the local schemas as the global schema.…”