The panel of experts cloud pattern
Proceedings of the third international workshop on Cloud data management
Achieving reproducibility by combining provenance with service and workflow versioning
Proceedings of the 6th workshop on Workflows in support of large-scale science
Cloud computing for fast prediction of chemical activity
Future Generation Computer Systems
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Scientists face many severe challenges in extracting value from the increasingly large volumes of data they generate. In this paper we describe the requirements we have derived from working across a wide range of e-science projects. In particular, the CARMEN neuroinformatics project has exposed a range of challenges due to a need to analyse and share large volumes of data. We have identified the four key activities required by scientists with whom we work, and designed an integrated system—e-Science Central—to provide them. This exploits three emerging technologies: software as a service to avoid the need for users to deploy and maintain any of their own software; social networking to allow users to collaborate by sharing data, services and workflows in a controlled manner and Cloud computing to provide scalable compute resources. The system can not only be used through any web browser, but also provides an API so that applications can build on the core functionality. We describe the requirements, and the design that flows from them. This includes data storage with in-built versioning and signing, an in-browser workflow editor and a job scheduling system that allows workflows to be run both on local ‘private’ clouds and the Microsoft Azure Cloud. Copyright © 2010 John Wiley & Sons, Ltd.