A model-based mediator system for scientific data management

Bertram Ludäscher, Amarnath Gupta, Maryann E. Martone

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

A database mediator system combines information from multiple existing source databases and creates a new virtual, mediated database that comprises the integrated entities and their relationships. When mediating scientific data, the technically challenging problem of mediator query processing is further complicated by the complexity of the source data and the relationships between them. In particular, one is often confronted with complex multiple-world scenarios in which the semantics of individual sources, as well as the knowledge to link them, require a deeper modeling than is offered by current database mediator systems. This chapter describes an extension called model-based mediation (MBM) based on experiences with federation data. In MBM, data sources export raw data and schema information as well as conceptual models (CMs), including domain semantics to the mediator, effectively lifting data sources to knowledge sources. This allows a mediation engineer to define integrated views based on (1) the local CMs of registered sources and (2) auxiliary domain knowledge sources called domain maps (DMs) and process maps (PMs), which act as sources of glue knowledge. The chapter illustrates the challenges using real-world examples from a complex neuroscience integration problem and presents the methodology and some tools-in particular, the knowledge-based integration of neuroscience data (KIND) mediator prototype for MBM of scientific data.

Original languageEnglish (US)
Title of host publicationBioinformatics
Subtitle of host publicationManaging Scientific Data
PublisherElsevier Inc.
Pages335-370
Number of pages36
ISBN (Electronic)9780080527987
ISBN (Print)155860829X, 9781558608290
DOIs
StatePublished - Jul 18 2003
Externally publishedYes

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)

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