1. Providing traceability for neuroimaging analyses
- Author
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McClatchey, R., Branson, A., Anjum, A., Bloodsworth, P., Habib, I., Munir, K., Shamdasani, J., Soomro, K., and Consortium, the neuGRID
- Subjects
FOS: Computer and information sciences ,Service (systems architecture) ,Traceability ,Medical Informatics Computing ,computer.internet_protocol ,Computer science ,Data management ,Neuroimaging ,Health Informatics ,Cloud computing ,02 engineering and technology ,computer.software_genre ,Workflow ,Information capture ,Computer Science - Software Engineering ,Computer Systems ,0202 electrical engineering, electronic engineering, information engineering ,Humans ,Brain Mapping ,business.industry ,020207 software engineering ,Service-oriented architecture ,Data science ,Software Engineering (cs.SE) ,Grid computing ,020201 artificial intelligence & image processing ,business ,computer ,Algorithms ,Software - 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., Comment: 17 pages, 9 figures, 2 tables
- Published
- 2013