Project profile: SHIWA and outGRID
Agnes Szeberényi introduces an international collaboration against Alzheimer’s disease
Scientists know that the thickness of the grey matter of Alzheimer’s disease patients is a clinical marker related to the progress of the disease.
Now, a successful worldwide co-operation between the two EU FP7 projects – outGRID and SHIWA – and the LINGA application to compute cortical thickness, will help to develop drugs for Alzheimer’s disease by combining heterogeneous Distributed Computing Infrastructure (DCI) technologies.
SHIWA
The SHIWA project – short for Sharing Interoperable Workflows for large-scale scientific simulations on Available DCIs – focuses on the interoperability of many different European workflow systems (such as Moteur, P-Grade, Askalon or Gwes) with the help of coarse-grained and fine-grained approaches.
The coarse-grained (CG) approach allows the combination of workflows written in different languages, in order to reuse existing applications. The CG approach treats existing workflows as black box systems that can be incorporated into other workflow applications as workflow nodes.
On the other hand, the fine-grained approach addresses language inter-operability by defining an intermediate representation to be used for translation of workflows across various workflow systems.
SHIWA develops, deploys and operates the SHIWA Simulation Platform to offer production-level services supporting workflow interoperability following both approaches. As part of the Simulation Platform the SHIWA Repository facilitates publishing and sharing workflows, and the SHIWA Portal enables their actual deployment. Use cases targeting various scientific domains will serve to drive and evaluate this platform from a user's perspective. SHIWA supports major grid infrastructure systems used in Europe (such as gLite, UNICORE, ARC or BOINC).
outGRID
The outGRID project aims to consolidate the three existing e-infrastructures for computational neuroscience into one unique worldwide facility. In Europe, neuGRID provides large sets of brain images paired with grid-based computationally intensive algorithms for studies of neurodegenerative diseases. The CBRAIN centre at McGill in Montreal, Canada and LONI at University of California, Los Angeles offer computational resources and algorithm pipelines.
LINGA, tying it all together
The LINGA (LInked Neuroscientific Grand chAllenge) is the first large-scale neuroscientific experiment that involves the three globally separated neuroscientific infrastructures within outGRID and EGI.
The LINGA workflow analyses the patient’s cortical thickness through a demanding image processing pipeline using data sources hosted and processed by the three neuroscience DCIs involved in outGRID. Once the analysis is finished, the outputs are sent back to the European Grid Infrastructure and statistically compared with selected meaningful criteria, and used to produce the graphs neuroscientists will then base their interpretations on.
Porting the LINGA workflow with SHIWA technologies speeds up (up to seven times) the database analysis time of the thousands of brain scan images from Alzheimer’s patients. This allows the available data to be statistically organised and used for further research activities.
The framework developed by the SHIWA consortium enables orchestration between the heterogeneous infrastructures, which is a huge step forward in neuroscience. •
