Neuroimaging is a field that benefits from distributed computing infrastructures (DCIs) to perform data- and compute-intensive processing and analysis. Using grid workflow systems not only automates the processing pipelines, but also enables domain researchers to implement their expertise on how to best process neuroimaging data. To share this expertise and to promote collaborative research in neurosciences, ways to facilitate the exchange, re-use, and interoperability of workflow applications between different groups are required. The SHIWA project (SHaring Interoperable Workflows for large-scale scientific simulations on Available DCIs) is specifically addressing such use-cases, building a generic platform to facilitate workflow exchange and execution environments interoperability. The goal is to facilitate the dissemination and execution of workflows by diverse workflow management systems on multiple DCIs. This platform enables researchers to gain access to a variety of ready-to-use workflows, to reuse workflows developed by collaborators, to publish their own workflows to be used by others, and to use additional resources from external DCIs to run workflows.

In this demonstration we present how the SHIWA platform is used to implement various usage scenarios in which workflow exchange supports collaboration in neuroscience. The SHIWA platform and the implemented solutions are presented from the user perspective, in this case the workflow developers and the neuroscientists. These workflow interoperability solutions aim to facilitate and enable more advanced and large-scale research in neuroscience.

The demonstration will focus on usage scenarios currently employed to exchange, combine and interoperate neuroimaging workflows between Academic Medical Center, Amsterdam, the Charite Universittsmedizin, Berlin and the outGrid infrastructure. These workflows are developed for the analysis of neuroimaging data, in particular Magnetic Resonance Images (MRI) and Diffusion Tensor Imaging (DTI). Each group has ported workflows with complementary and overlapping functions to its Grid infrastructure using different workflow systems, so the goal is to combine and share them across the boundaries of the original DCIs.

The following usage scenarios will be addressed in the demonstration:

• Preparing the workflow for sharing with others (VO, workflow management system dependencies);

• Using the SHIWA repository for publishing workflows to share a new workflow with other potential users;

• Finding a workflow in the SHIWA repository and testing it with sample data;

• Running the workflow found in the repository with own data using the SHIWA simulation platform;

• Combining complementary workflows into a meta-workflow to implement additional functionality or combining different implementations of the same workflow to compute on different DCIs simultaneously

The shown solution includes neuroimaging workflows using the GWES, MOTEUR, LONI pipeline and P-GRADE workflow engines submitting jobs to the German MediGRID, the Dutch BiG Grid, the European EGI, and the international outGrid infrastructures. Data to be accessed might be stored locally, on an iRODS data management system, in the LFC file catalog and on gridFTP-enabled sites. The user-interfaces are web-based and include a Liferay-based Grid portal and a P-GRADE workflow editor implemented as webstart application. The neuroimaging applications include self-developed tools for preprocessing DTI data and widely used methods from the ITK and the FSL toolboxes.