Conferences and Themes

HealthGrid 2010 (http://paris2010.healthgrid.org) is the eighth meeting of this open forum for the integration of grid technologies, e-science and e-health methods and their applications in the biomedical and healthcare domains. The principal objective of the HealthGrid conference and of the HealthGrid Association is the exchange and debate of ideas, technologies, solutions and requirements that interest the grid and the life-science communities and are likely to promote the integration of grids into biomedical research and health in the broadest sense. Participation is encouraged for grid middle-ware and healthgrid application developers, biomedical and health informatics users, ethicists and security experts, and policy makers to participate in a set of multidisciplinary sessions with a common focus on bringing healthgrids closer to real application in the health domain.

HealthGrid conferences have been organized on an annual basis. The first conference, held in 2003 in Lyon (http://lyon2003.healthgrid.org), reflected the need to involve all actors – physicians, scientists and technologists – who might play a role in the application of grid technology to health, whether healthcare or biomedical research. The second conference, held in Clermont-Ferrand in January 2004 (http://clermont2004.healthgrid.org) reported on the earliest efforts in research, mainly work in progress, from a large number of projects. The third conference in Oxford (http://oxford2005.healthgrid.org) had a major focus on first results and exploration of deployment strategies in healthcare. The fourth conference in Valencia (http://valencia2006.healthgrid.org) aimed at consolidating the collaboration among biologists, healthcare professionals and grid technology experts. The fifth conference in Geneva (http://geneva2007.healthgrid.org) focused on the five domains defined by the European Commission as application areas for ‘vertical integration’ through grids in the biomedical field: molecules, cells, organs, individuals, and populations. For each of these five domains, an invited speaker gave a state of the art address followed by concrete projects. This was a loud signal to the community that the usefulness of grids to potential application domains could be demonstrated at least at the prototype level. This theme was also evident at the sixth conference in Chicago (http://chicago2008.healthgrid.org), which proclaimed its focus as ‘e-Science Meets Biomedical Informatics’. The sixth conference was also a landmark in the history of the organisation HealthGrid – and its newly established affiliate HealthGrid.US – as the first conference to be organised outside Europe. As we put it at the time, this was a celebration of similarities and differences, a moment to validate models and principles beyond one's familiar shores. The seventh conference returned to Europe, taking place for the first time in Germany in Berlin (http://berlin2009.healthgrid.org). While most themes touched on in earlier conferences continued to be present, certain other themes came to the fore perhaps more clearly than ever before: accessibility, the fraught challenge of usability, and the question of a business case for healthgrids. Ethical, legal, social and economic issues are sometimes encapsulated in the acronym ELSE, with the wry joke that we would like “someone else” to take care of them; perhaps more clearly than before, the Berlin conference embraced and debated these issues directly. Along with these, a hint of ‘cloud’ also hovered over the discussion of core technologies — and a less metaphorical cloud burst over the open-air conference dinner to refresh participants.

While the desire to promote healthgrid applications to real healthcare settings remains central to the community's ambitions, it is also true that the majority of adopters work in academic environments where research is their principal preoccupation. Judging from the full range of papers submitted this year, cloud computing appears set to make an impact, just when healthcare informatics appears readier to adopt that paradigm, perhaps in preference to grids. So it may turn out that grids will remain the infrastructure of choice for research and clouds for (the business of) healthcare.

Conference at Orsay, Paris, 2010

The call for papers issued in January resulted in 42 submissions; after a review process in which all papers were read by two independent reviewers as well as at least one, sometimes two members of the Steering Committee, 19 papers were accepted for full presentation. In addition, several papers described work that is still at an early stage and not yet ready for presentation as a full paper, or presented work of considerable scientific merit but which had not yet been fully implemented in a grid. These were considered worthy of inclusion in the conference as posters and, in a shorter form, in the proceedings.

Section One — Socio-Economic Aspects and Accessibility

Xin Zhou et al. conducted an extensive survey of opinion about grids in the public sector. Among the significant findings were discrepancies between expectations of users and administrators, hinting at an inherent tension in the concept of grids as a means of full exploitation of resources.

Hanene Rahmouni's report of semi-automated compliance checking, extending her earlier work on the SHARE project, leads to an optimistic picture suggesting that technology and the dread ‘ELSE’ issues are not entirely at odds.

Yassene Mohammed and colleagues consider the means of technology and knowledge transfer in the grid world. They discuss the players, problems and media at work in the process of technology adoption among life scientists. Their analysis examines in particular the medium of exchange (including, e.g., newly trained user experts) and explores various explanatory paradigms of technology transfer.

Femida Gawdry-Sridhar and Silvia Olabarriaga with co-authors compare developments in Canada and in the Netherlands in the light of the vision of the HealthGrid ‘white paper’ broad road maps of the SHARE project. They find grounds for optimism but also identify similar obstacles and resistances on both sides.

Section Two — Future of Grids, Core Technologies & Data Integration

Adam Kraut and colleagues compared clouds vs clusters in an ‘embarrassingly parallel’ biomedical application. This is justified on the grounds of compute-intensity of the application, but judged on usability and performance. This should certainly be a good challenge for the cloud paradigm; the results are somewhat unfavourable.

TRENCADIS, which will be familiar to readers of this series, was originally built with a Service-Oriented Architecture. It has now been ported by Ignacio Blanquer et al. to gLite using features of DICOM Structured Reports and ontologies to integrate data from diverse imaging and associated data.

Reporting from ACGT, Garcia, Karlsson and Trelles describe a catalog of service metadata to support discovery and integration of services. Their approach nicely highlights trade-offs between expressiveness and ease of discovery and composition.

Ashiq Anjum et al. explore the proposed reuse of a highly sophisticated database designed to track the construction of a CERN experiment as a provenance engine in the neuGRID project.

Benbelgacem, Niimaki and Abdennadher extend the work previously reported in 2008 on healthgrid adoption and adaptation of XtremWeb-CH and lead through these developments to the release of a new infrastructure, XWCH2.

A large collaboration from the NeuroLOG project report on its data management layer and their successful federation of neuroimaging data. This has allowed them to achieve semantically tight integration of data from diverse, loosely coupled sources.

The Décrypthon project has established a grid infrastructure for biomedical applications. Although the authors' focus was on the technology (middleware, query language) they illustrate it with a valuable application to neuromuscular disorders.

Paul de Vlieger et al. report on an application that was foreseen even in the HealthGrid ‘white paper’ as one of the founding challenges for healthgrids. The idea is to integrate diverse, geographically distributed databases so as to be able to derive meaningful epidemiological information from the base data, in this case from various cancer screening programmes.

Finally in this section, David Ritchie et al report on the use of special processors for certain biomedical tasks. In particular, the already efficient Hex protein docking algorithm turns out to run significantly faster on graphics processor units. This has certain interesting implications for technology choices in specialist grids for biomedical research.

Section Three — Applications

A team from Charité – Universitätsmedizin Berlin report on the increasing need for imaging in liver disease. Segmentation of MRI images is sufficiently complex to justify use of a grid. The results are compared with an expert's segmentation. Lessons are also drawn for further innovation in healthgrids.

Hausmann, Knoch et al. describe GLOBE 3D Genome Platform an interactive collaboration grid platform for the analysis and visualization of results from their novel COMBO-FISH method of labelling genomic sequences.

Jason Haga and team from California and Japan began their work with the observation of inconsistencies in virtual screening using DOCK on a heterogeneous grid. They experimented with virtualization to overcome heterogeneity and show that variability in results is much reduced. This work again raises the issue of clouds.

Arun Datta and colleagues describe a grid-based epidemiological application integrating information for childhood obesity surveillance. This is an increasingly pressing problem in better off nations. Besides compliance with ethical and legal constraints, they demonstrate improved accuracy of vital data and a reduction in the workload of service providers.

A team from CNRS INSERM CREATIS, Lyon, report on the highly technical problem of parameter optimization in so-called ‘mean-shift’ kernel methods for multi-dimensional data analysis. They demonstrate the feasibility of using EGEE for this project, although they also indicate some gaps in usability.

Trung Tung Doan and colleagues from France and Vietnam illustrate an approach to combine phylogenetic data on a virus with the surveillance network concept already illustrated in other applications. This leads to a highly effective method of H1N1 influenza monitoring.

Section Four — Poster Extended Abstracts

Among many applications, Graham Billiau and colleagues discuss grid-based optimization of radiotherapy patient scheduling, a problem that has wider implications. Daniela Skrowny and team describe a novel information platform for new grid users in biomedicine. Mark Olive et al consider the use of care pathway records for research with assisted reproduction as a case study. Anthony Stell and colleagues discuss the compliance pressure in a project to integrate clinical and genomic data relating to patients with adrenal tumours. Eberhard Schmitt et al do some very sophisticated geometry with cell nucleus architecture to derive biologically meaningful information.

More traditional applications of healthgrids (is it not remarkable that we can already speak of ‘traditional’ applications) are closer to biomedicine than healthcare, though the distance between the two is perceptibly less than it was. Raul Isea and colleagues discuss bayesian models to characterize antigenic serotypes of the Dengue virus. Marta Loureiro and team present a grid-based selection process for models of nucleotide substitution. Aristotelis Chatziioannou and team describe GRISSOM, a microarray analysis application.

In the knowledge management dimension, we have two contributions. The first from Carl Taswell is an interesting ontology-based attempt to enhance data integration and interoperability for cross-domain retrieval and sharing of biomedical knowledge. In the second, Alfredo Tirado-Ramos and colleagues outline HIV-K which they describe as a ‘semantically integrative’ knowledge base for AIDS-related cancer data.

Tobias Knoch and his colleagues display a characteristic enthusiasm for their proposed resource-efficient grid architecture. I suspect it would be claimed by some to be ‘a cloud’, pending a precise definition of that term.

Tony Solomonides, 17th May 2010