Data-intensive architecture for scientific knowledge discovery

作者：Atkinson Malcolm; Liew Chee Sun^*; Galea Michelle; Martin Paul; Krause Amrey; Mouat Adrian; Corcho Oscar; Snelling David

来源：Distributed and Parallel Databases, 2012, 30(5-6): 307-324.

DOI：10.1007/s10619-012-7105-3

• Knowledge discovery
• Workflow management system

This paper presents a data-intensive architecture that demonstrates the ability to support applications from a wide range of application domains, and support the different types of users involved in defining, designing and executing data-intensive processing tasks. The prototype architecture is introduced, and the pivotal role of DISPEL as a canonical language is explained. The architecture promotes the exploration and exploitation of distributed and heterogeneous data and spans the complete knowledge discovery process, from data preparation, to analysis, to evaluation and reiteration. The architecture evaluation included large-scale applications from astronomy, cosmology, hydrology, functional genetics, imaging processing and seismology.

• 出版日期2012-10