Centre for Complex Cooperative Systems, CEMS Faculty, University of the West of England, Coldharbour Lane, Frenchay, Bristol BS16 1QY, United Kingdom.
Int J Med Inform. 2013 Sep;82(9):882-94. doi: 10.1016/j.ijmedinf.2013.05.005. Epub 2013 Jun 12.
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.
Few examples exist, of deployed medical systems based on Grids that provide the traceability of research data needed to facilitate complex analyses and none have been evaluated in practice. 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 Alzheimer's 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 Alzheimer's disease.
In the neuGRID and N4U projects a Provenance Service has been delivered that captures and reconstructs the workflow information needed to facilitate researchers in conducting neuroimaging analyses. The software enables neuroscientists to track the evolution of workflows and datasets. It also tracks the outcomes of various analyses and provides provenance traceability throughout the lifecycle of their studies. As the Provenance Service has been designed to be generic it can be applied across the medical domain as a reusable tool for supporting medical researchers thus providing communities of researchers for the first time with the necessary tools to conduct widely distributed collaborative programmes of medical analysis.
随着生物医学数据日益数字化，以及医学研究中分析的复杂性不断增加，准确捕捉、可追溯和可访问信息对于医学研究人员实现其研究目标变得至关重要。基于所谓的面向服务架构（SOA）的网格或云技术，越来越被视为管理生物医学领域分布式数据和算法的可行解决方案。对于神经科学分析，特别是以复杂图像分析为中心的分析，过程和数据集的可追溯性至关重要，但到目前为止，还没有以有利于协作研究的方式进行捕捉。
基于网格的医疗系统很少有实例可以提供复杂分析所需的研究数据的可追溯性，并且在实践中尚未对其进行评估。在过去的十年中，我们与乳腺科医生、儿科医生和神经科学家合作，在三代项目中提供了数据管理和现在 21 世纪医学研究所需的来源服务。本文概述了一项需求研究的结果和一个系统架构，用于生成支持神经科学研究阿尔茨海默病生物标志物的服务。
本文提出了一种软件基础架构和服务，为这种支持提供了基础。它介绍了使用 CRISTAL 软件提供来源管理作为 SOA 上提供的服务之一，该服务部署用于管理一直在研究阿尔茨海默病生物标志物的神经影像项目。
在 neuGRID 和 N4U 项目中，已经提供了一个 Provenance Service，该服务捕获并重建了促进神经成像分析的工作流信息。该软件使神经科学家能够跟踪工作流和数据集的演变。它还跟踪各种分析的结果，并在其研究的生命周期中提供来源可追溯性。由于 Provenance Service 被设计为通用服务，因此可以在整个医疗领域中作为支持医疗研究人员的可重复工具进行应用，从而首次为研究人员社区提供了进行广泛分布式合作医学分析计划所需的工具。
