CONCURRENCY AND COMPUTATION: PRACTICE AND EXPERIENCEConcurrency Computat.: Pract. Exper. 2008; 20:191–193Published online 24 October 2007 inWiley InterScience (www.interscience.wiley.com). DOI: 10.1002/cpe.1255

Special Issue

The 2005 U.K. e-Science All Hands Meeting was the fourth in the series, but had a markedlydifferent flavour to those that had gone before. The UK e-Science core programme began in 2001,under the leadership of Professor Tony Hey; hence by the 2005 meeting, many of the initialprojects had ended and delivered interesting results. These spanned not just the design of theunderlying computer infrastructure to support e-science, but often also the application scienceitself.The breadth of scientific domains had also broadened considerably by 2005. In the early days of

grid computing, there was an emphasis on the use of high-performance computing facilities to sup-port large computations—job-based grid computing was the dominant paradigm. However, the U.K.e-science programme invested heavily on applications and infrastructure to support information-driven science. Areas such as biology were facing a deluge of heterogeneous, complex data, andadvances in e-science were not just of academic interest, but were absolutely necessary if the in-herent value in this data was to be unlocked. By the 2005 meeting, the results of the first successfulprojects to achieve this were being published.One key aspect of the U.K. e-Science programme was its focus on collaboration. This was a

necessity if advances were to be made: the application scientists had computational needs that werebeyond the capabilities of the existing compute infrastructures, whilst computer scientists oftenhad ideas and prototypes, but needed applications to set the requirements and provide a way toevaluate their work. Even within the computing community, collaboration was encouraged, withprojects bringing together a set of sub-disciplines that had previously often only had a noddingacquaintance. A typical project might extract data from a set of databases based on some searchcriteria, combine and analyse the results, compare them against the existing knowledge, and thenvisualize any promising outputs. This required the collaboration of researchers with a diverseset of skills ranging across databases, data analysis, semantics, text mining, user interfaces andvisualization.In this special issue, we have selected eight papers from the 259 submissions to the conference.

They were chosen from those judged by the programme committee to be the best submissions,and we have tried to show something of the diversity of the work presented. They therefore spana set of application sciences, while the underlying infrastructure exploits a range of disciplineswithin computing science. They range from quantitative performance prediction in complex gridsystems, through projects engaging school children in biomedical research challenges, to worldwidegrid-enabled systems. We now explain why we picked each paper:

Copyright © 2007 John Wiley & Sons, Ltd.

192 EDITORIAL

Jarvis et al. [1] present some new predictive modelling to enable interactive scheduling of acomplex biomedical application where the runtime is highly variable and depends on data knownonly at the time of job submission.Fang et al. [2] analyse the scalability of the semantics-aware service discovery engine GRI-

MOIRES.An important and pressing challenge in science and engineering is to engage and nurture the

next generation of scientists, who are our future! Jeremy Frey leads a project described in Freyet al. [3], which aims at bringing the attention of 16–18-year-old school children to how computa-tional drug design works, motivated by the search for better drugs to combat Malaria.Cohen et al. [4] demonstrate how advances in Grid computing technologies coupled to innova-

tive charging models could provide a radical change in the provisioning and use of informationtechnology across academia, business and society.Preece et al. [5] demonstrate how information quality annotations for experimental data sets can

be computed and delivered using a web service by leveraging preferences provided by users againsta formal domain-specific ontology.Wood et al. [6] demonstrate how computational steering can be improved by enabling users

to manipulate and steer calculations by direct interaction with images or visualizations of theirsimulation rather than by the conventional means of varying input parameter sets. They also reporton preliminary user testing of their system.Lupu et al. [7] couple wireless health monitoring sensors to a grid with the aim of enabling a

patient to be monitored easily in a variety of settings. A key aspect of their system is to makeit self-configuring and self-managing to minimize the need for a patient to become a technologyexpert in order to get the benefits of using it. Perhaps, more technology should be designed withthis in mind!Grid systems are now becoming increasingly relied upon by scientists and business; if they fail

then the implications can be grave. As a result, researchers are investigating methods to increasethe tolerance of grid infrastructures to hardware and software failures. This makes the work of Xuet al. [8] very timely.We hope that you enjoy reading the selection of papers in this special edition and we thank the

authors for allowing us to present their work.

REFERENCES

1. Jarvis SA, Foley BP, Isitt PJ, Spooner DP, Rueckert D, Nudd GR. Performance prediction for a code with data-dependentruntimes. Concurrency and Computation: Practice and Experience 2007; DOI: 10.1002/cpe/1191.

2. Fang W, Miles S, Moreau L. Performance analysis of a semantics-enabled service registry. Concurrency and Computation:Practice and Experience 2007; DOI: 10.1002/cpe.1204.

3. Geldhill R, Kent S, Milsted A, Chapman R, Essex JW, Frey JG. e-Malaria: The schools Malaria project. Concurrencyand Computation: Practice and Experience 2007; DOI: 10.1002/cpe.1193.

4. Cohen J, Darlington J, Lee W. Payment and negotiation for the next generation Grid and Web. Concurrency andComputation: Practice and Experience 2007; DOI: 10.1002/cpe.1196.

5. Preece A, Missier P, Embury S, Jin B, Greenwood M. An ontology-based approach to handling information quality ine-Science. Concurrency and Computation: Practice and Experience 2007; DOI: 10.1002/cpe.1195.

6. Wood JD, Wright H. Steering via the image in local, distributed and collaborative settings. Concurrency and Computation:Practice and Experience 2007; DOI: 10.1002/cpe.1197.

Copyright q 2007 John Wiley & Sons, Ltd. Concurrency Computat.: Pract. Exper. 2008; 20:191–193DOI: 10.1002/cpe

EDITORIAL 193

7. Lupu E, Dulay N, Sloman M, Sventek J, Heeps S, Strowes S, Twidle K, Keoh S-L, Schaeffer-Filho A. AMUSE:Autonomic management of ubiquitous e-Health systems. Concurrency and Computation: Practice and Experience 2007;DOI: 10.1002/cpe.1194.

8. Xu J, Townend P, Looker N, Groth P. FT-Grid: a system for achieving fault tolerance in grids. Concurrency andComputation: Practice and Experience 2007; DOI: 10.1002/cpe.1266.

PAUL WATSON

Newcastle University,Newcastle Upon Tyne, U.K.

SIMON COX

Southampton University,Southampton, U.K.

Copyright q 2007 John Wiley & Sons, Ltd. Concurrency Computat.: Pract. Exper. 2008; 20:191–193DOI: 10.1002/cpe