There are many aspects to e-Science Central, and publications focusing on them are described in the sections below. However, good places to start are:

H. Hiden, S. Woodman, P. Watson, J. Cala. Developing cloud applications using the e-science central platformRoyal Society of London. Philosophical Transactions A. Mathematical, Physical and Engineering Sciences 2013,371(1983), 20120085.

S. Woodman, H. Hiden, P.Watson. Applications of provenance in performance prediction and data storage optimisation. Future Generation Computer Systems, Elsevier, January 2017.


To cite the provenance capture, storage and visualisation, please use one of the following

P. Missier, S. Woodman,  H. Hiden, P. Watson. Provenance and data differencing for workflow reproducibility analysisConcurrency and Computation: Practice & Experience, March 2013.

S. Woodman, H. Hiden, P. Watson,  P. Missier Achieving Reproducibility by Combining Provenance with Service and Workflow VersioningIn: The 6th Workshop on Workflows in Support of Large-Scale Science. 2011, Seattle


Details of our work on security, workflow partitioning and executing workflows between cloud providers

P. Watson, A Multi-Level Security Model for Partitioning Workflows over Federated Clouds, IEEE CloudCom 2011 (3rd International Conference on Cloud Computing technology and Science)

An extended version was published in: Journal of Cloud Computing: Advances, Systems and Applications 2012, 1:15


Much of our work has focussed on the scalability of cloud applications applications

J. Cała, H. Hiden, P. Watson, S. Woodman. Cloud Computing for Fast Prediction of Chemical Activity. Future Generation Computer Systems, (2013).

H. Hiden, S. Woodman, P. Watson, M. Catt, M. Trenell and S. Zhang. Improving the scalability of movement monitoring workflows: An architecture for the integration of the Hadoop File System into e-Science Central. Proceedings of 1st Conference on Digital Research, Oxford, September 2012.

J. Cała, H. Hiden, S. Woodman, P.Watson. Fast Exploration of the QSAR Model Space with e-Science Central and Windows AzureMicrosoft Cloud Futures, Berkeley, May 2012.

 J. Cała, H.Hiden, P.Watson, S.Woodman. Cloud Computing for Fast Prediction of Chemical Activity. 2nd International Workshop on Cloud Computing and Scientific Applications (CCSA). Ottawa, May 2012


Other miscellaneous papers

H. Hiden, S.Woodman, P.Watson. Prediction of workflow execution time using provenance traces: Practical applications in medical data processing. 12th International IEEE Conference on e-Science. Baltimore, ML. October 2016.

S. Woodman, H. Hiden, P. Watson Workflow Provenance: An Analysis of Long Term Storage Costs. In: WORKS ’15 Proceedings of the 10th Workshop on Workflows in Support of Large-Scale Science. 2015, Austin, Texas: ACM.

S. Woodman, H.Hiden, M. Turner, S. Dowsland, P.Watson. Monitoring of Upper Limb Rehabilitation and Recovery after Stroke: an Architecture for a Cloud-based Therapy Platform. In: 2015 IEEE 11th International Conference on eScience. 2015, Munich: IEEE.

H. Hiden, S. Woodman, P.Watson. A framework for dynamically generating predictive models of workflow execution. In: WORKS ’13 Proceedings of the 8th Workshop on Workflows in Support of Large-Scale Science. 2013, Denver, CO: ACM Digital Library.

S. Woodman, H. Hiden, P. Watson, J. Cała. Drug Design Experiments in the Cloud.  Microsoft e-Science Workshop, Dec 2011, Stockholm. [slides]

S. Woodman, H. Hiden, P. Watston, J Cała. Developing Applications using the e-Science Central APIIn: UK e-Science All Hands Meeting. 2011, York.

P. Watson, H. Hiden, S. Woodman. e-Science Central for CARMEN: Science as a Service. Concurrency and Computation: Practice and Experience, Volume 22, Issue 17, pages 2369-2380, 10 December, 2010.

H. Hiden, P. Watson, S. Woodman and D. Leahy. e-Science Central: Cloud-based e-Science and its application to chemical property modelling. Technical Report: CS-TR-1227, School of Comp. Sci., Newcastle University, 2011.

P. Watson, D. Leahy, J. Cała, H. Hiden, D. Searson, V. Sykora and S. Woodman. Accelerating Chemical Property Prediction with Cloud Computing. In proceedings of The Microsoft e-Science Workshop, October 2010, Berkeley, CA, USA [slides]

P. Watson, H. Hiden, S. Woodman, D. Leahy, J. Cała. e-Science Central: e-Science on the Web, powered by Clouds. UK e-Science All Hands Meeting 2010

A. Gemmell, J. Blower, K. Haines, S. Pascoe, P. Kershaw, B. Lawrence, S. Woodman and H. Hiden. The MashMyData project – Combining and comparing environmental science data on the web. UK e-Science All Hands Meeting 2010

P. Watson, D. Leahy, J. Cała, V. Sykora, H. Hiden, S. Woodman, M. Taylor, D. Searson. Cloud Computing for Chemical Property Prediction [slides]. Microsoft Cloud Futures 2010 Conference

H. Hiden. Presentation at Microsoft External Research Symposium: Project JUNIOR: Drug Discovery using Azure.

S. Woodman. Presentation at The Influence and Impact of Web 2.0 on Various Applications: Cloud Computing for Chemical Property Prediction.

J. Cała, P. Watson. Automatic Deployment in the Azure Cloud. In proceedings of DAIS’10 conference. June 2010, Amsterdam, Netherlands.

S. Woodman, H. Hiden, P. Watson, J. Cała.Workflows and Applications in e-Science CentralAll Hands Meeting, December 2009, Oxford, UK.

P. Watson, H. Hiden, S. Woodman, J. Cała, D. Leahy. Drug Discovery on the Azure Cloud. Poster presentation. Microsoft e-Science Conference. October 2009, Seattle, USA.