Using Grids for Exploiting the Abundance of Data in Science

Abstract

Digital data volumes are growing exponentially in all sciences. To
handle this abundance in data availability, scientists must use data
analysis techniques in their scientific practices and solving
environments to get the benefits coming from knowledge that can be
extracted from large data sources. When data is maintained over
geographically remote sites the computational power of distributed
and parallel systems can be exploited for knowledge discovery in
scientific data. In this scenario the Grid can provide an effective
computational support for distributed knowledge discovery on large
datasets. In particular, Grid services for data integration and
analysis can represent a primary component for e-science
applications involving distributed massive and complex data sets.
This paper describes some research activities in data-intensive Grid
computing. In particular we discuss the use of data mining models
and services on Grid systems for the analysis of large data
repositories.