e-Science

Abstract: This presentation will set out the eScience agenda by explaining the current scientific data deluge and the case for a “Fourth Paradigm” for scientific exploration. Examples of data intensive science will be used to illustrate the explosion of data and the associated new challenges for data capture, curation, analysis, and sharing. The role of cloud computing, collaboration services, and research repositories will be discussed.

Abstract: From the Publisher: Grid computing is applying the resources of many computers in a network to a single problem at the same time Grid computing appears to be a promising trend for three reasons: (1) Its ability to make more cost-effective use of a given amount of computer resources, (2) As a way to solve problems that can't be approached without an enormous amount of computing power (3) Because it suggests that the resources of many computers can be cooperatively and perhaps synergistically harnessed and managed as a collaboration toward a common objective. A number of corporations, professional groups, university consortiums, and other groups have developed or are developing frameworks and software for managing grid computing projects. The European Community (EU) is sponsoring a project for a grid for high-energy physics, earth observation, and biology applications. In the United States, the National Technology Grid is prototyping a computational grid for infrastructure and an access grid for people. Sun Microsystems offers Grid Engine software. Described as a distributed resource management tool, Grid Engine allows engineers at companies like Sony and Synopsys to pool the computer cycles on up to 80 workstations at a time. "the Grid" is a very hot topic generating broad interest from research and industry (e.g. IBM, Platform, Avaki, Entropia, Sun, HP) Grid architecture enables very popular e-Science projects like the Genome project which demand global interaction and networking In recent surveys over 500f Chief Information Officers are expected to use Grid technology this year Grid Computing: Features contributions from the major players in the field Covers all aspects of grid technology from motivation to applications Provides an extensive state-of-the-art guide in grid computing This is essential reading for researchers in Computing and Engineering, physicists, statisticians, engineers and mathematicians and IT policy makers.

Abstract: Data management is growing in complexity as large-scale applications take advantage of the loosely coupled resources brought together by grid middleware and by abundant storage capacity. Metadata describing the data products used in and generated by these applications is essential to disambiguate the data and enable reuse. Data provenance, one kind of metadata, pertains to the derivation history of a data product starting from its original sources.In this paper we create a taxonomy of data provenance characteristics and apply it to current research efforts in e-science, focusing primarily on scientific workflow approaches. The main aspect of our taxonomy categorizes provenance systems based on why they record provenance, what they describe, how they represent and store provenance, and ways to disseminate it. The survey culminates with an identification of open research problems in the field.

Abstract: This is a timely book presenting an overview of the current state-of-the-art within established projects, presenting many different aspects of workflow from users to tool builders. It provides an overview of active research, from a number of different perspectives. It includes theoretical aspects of workflow and deals with workflow for e-Science as opposed to e-Commerce. The topics covered will be of interest to a wide range of practitioners.