Data audit and requirements analysis

One of the initial exercises to be conducted as part of the EIDCSR project was the audit and requirements analysis based on DAF to document the data practices and assets as well as to capture the requirements for tools and services of the research groups participating in the project. This exercise took place throughout the summer and the report describing the results will be available soon.

As I explained on a previous post, these research groups collaborate as part of a BBSRC grant to conduct research on ventricular architecture by using novel techniques such as Magnetic Resonance Imaging (MRI) and Diffusion Tensor MRI (DTMRI) and combine them with traditional histological techniques as well as with image processing with data registration and computational models for bio-mathematical simulation.

Their research workflow is well described by Gernot et. all (2009)* in the diagram below. It starts with the generation of complementary images stacks that are then processed in different ways to generate meshes that can be used for computational modelling of the heart.

The result of this complex process produces the following data outputs:

• Histology data: large high resolution images produced by microscopes in the lab representing sections of a heart.
• MRI and DTMRI data: stack of tiff images resulting from the raw data produced by the magnet in a lab.
• Segmentation data: outputs resulting from applying image segmentation techniques to the histology and MRI data.
• Mesh data: volumetric model produced from segmented data in a mesh generator.
• Simulations: electrophysiological simulation using the mesh data and other input files that define the models and the parameters.
• 3D heart atlas: representing an average representation of a heart ventricles obtained from the histology and MRI data.

And the research group requirements can be grouped under three themes:

• Secure storage: all the data outputs presented above are stored on a combination of desktop computers and a project NAS system and researchers realize the need to keep the data safe by having appropriate and resilient back-up procedures.
• Data transfer: the histology data are large and needs to be accessed by researchers within the groups and others.
• Metadata: currently the provenance metadata for some of the data presented above is recorded in printed lab-books. This information is crucial when making the data available to others and it is required when publishing articles based on the data. In addition to this, it may be helpful to improve searching within the NAS system.

*Gernot Plank, Rebecca A.B. Burton, Patrick Hales, Martin Bishop, Tahir Mansoori, Miguel O. Bernabeu, Alan Garny, Anton J. Prassl, Christian Bollensdorff, Fleur Mason, Fahd Mahmood, Blanca Rodriguez, Vicente Grau, Jürgen E. Schneider, David Gavaghan, and Peter Kohl Generation of histo-anatomically representative models of the individual heart: tools and application Phil Trans R Soc A 2009 367: 2257-2292.