Providing Traceability for Neuroimaging Analyses
release_nqg4d2mojnfovbfcascyktqpaa
by
R. McClatchey, A. Branson, A. Anjum, P. Bloodsworth, I. Habib, K.
Munir, J. Shamdasani, K. Soomro, the neuGRID Consortium
2014
Abstract
With the increasingly digital nature of biomedical data and as the complexity
of analyses in medical research increases, the need for accurate information
capture, traceability and accessibility has become crucial to medical
researchers in the pursuance of their research goals. Grid- or Cloud-based
technologies, often based on so-called Service Oriented Architectures (SOA),
are increasingly being seen as viable solutions for managing distributed data
and algorithms in the bio-medical domain. For neuroscientific analyses,
especially those centred on complex image analysis, traceability of processes
and datasets is essential but up to now this has not been captured in a manner
that facilitates collaborative study. Over the past decade, we have been
working with mammographers, paediatricians and neuroscientists in three
generations of projects to provide the data management and provenance services
now required for 21st century medical research. This paper outlines the finding
of a requirements study and a resulting system architecture for the production
of services to support neuroscientific studies of biomarkers for Alzheimers
Disease. The paper proposes a software infrastructure and services that provide
the foundation for such support. It introduces the use of the CRISTAL software
to provide provenance management as one of a number of services delivered on a
SOA, deployed to manage neuroimaging projects that have been studying
biomarkers for Alzheimers disease.
In text/plain
format
Archived Files and Locations
application/pdf 776.6 kB
file_fbfx3nk6hbflhnasjjjulq7rru
|
arxiv.org (repository) web.archive.org (webarchive) |
1402.5749v1
access all versions, variants, and formats of this works (eg, pre-prints)