Data Driven e-Science

Abstract

Nowadays science is highly multidisciplinary and requires innovative research environments. Such research environments, also known as Virtual Research Environments , should be powerful and flexible enough to help researchers in all disciplines to manage the complex range of tasks involved in carrying out eScience activities. Such research environments should support computationallyintensive, data-intensive and collaboration-intensive tasks on both small and large scale. The community to be served by a specific research environment is expected to be potentially distributed across multiple organizational domains and institutions. This paper discusses the approach put in place in the context of the D4Science EU project to enable on-demand production of Virtual Research Environments by relying on an innovative, grid-based Infrastructure. In particular, the foundational principles, the enabling technology and the concrete experience resulting from developing i a production Infrastructure and ii a Virtual Research Environment for generating predictive species distribution maps are described.