Big Data Analytics in Ageing Propulation and Reproductive Health:Science Data Center as an Example
This paper defines big data analytics and its characteristics, comments on its economic value, opportunities and challenges in health care, and provides recommendations to stakeholders on next steps.This revolutionary paradigm shift comes with challenges in terms of data transfer, storage, computation, and analysis of big population.health data.Cloud computing is a service model sharing a pool of configurable resources, which is a suitable workbench to address these challenges.From the medical or biological perspective, providing computing power and storage is the most attractive feature of cloud computing in handling the ever increasing biological data.As data increases in size, many research organizations start to experience the lack of computing power, which becomes a major hurdle in achieving research goals.In this paper, we review the features of publically available population and reproductive health cloud systems in terms of graphical user interface, external data integration, security and extenslbllity of features.We then discuss about issues and limitations of current cloud systems ud conclude with suggestion of a biological cloud environment concept, which can be defined as a total workbench environment assembling computational tools and databases for analyzing demographic /medical big data in particular application domains.
Health informatics Cloud computing Big data Workflow User interface Data integration Analysis Security
Hua Yu Weihong Zhang Ying Su Yuri Demchenko
National Research Institute for Family Planning Beijing, China WHO Collaborating Center for Research School of Public Health Université Libre de Bruxelles B-1070 Bruxelles, Belgique Resource Sharing Promotion Center Institute of Scientific and Technical Information of China, Beijin Department of System and Network Engineering University of Amsterdam Amsterdam, Netherlands
国际会议
武汉
英文
180-186
2013-10-25（万方平台首次上网日期，不代表论文的发表时间）