Hansen M M, Miron-Shatz T, Lau A Y S, Paton C
Margaret Hansen, School of Nursing and Health Professions, University of San Francisco, San Francisco, California, USA, E-mail:
Yearb Med Inform. 2014 Aug 15;9(1):21-6. doi: 10.15265/IY-2014-0004.
As technology continues to evolve and rise in various industries, such as healthcare, science, education, and gaming, a sophisticated concept known as Big Data is surfacing. The concept of analytics aims to understand data. We set out to portray and discuss perspectives of the evolving use of Big Data in science and healthcare and, to examine some of the opportunities and challenges.
A literature review was conducted to highlight the implications associated with the use of Big Data in scientific research and healthcare innovations, both on a large and small scale.
Scientists and health-care providers may learn from one another when it comes to understanding the value of Big Data and analytics. Small data, derived by patients and consumers, also requires analytics to become actionable. Connectivism provides a framework for the use of Big Data and analytics in the areas of science and healthcare. This theory assists individuals to recognize and synthesize how human connections are driving the increase in data. Despite the volume and velocity of Big Data, it is truly about technology connecting humans and assisting them to construct knowledge in new ways. Concluding Thoughts: The concept of Big Data and associated analytics are to be taken seriously when approaching the use of vast volumes of both structured and unstructured data in science and health-care. Future exploration of issues surrounding data privacy, confidentiality, and education are needed. A greater focus on data from social media, the quantified self-movement, and the application of analytics to "small data" would also be useful.
随着技术在医疗保健、科学、教育和游戏等各个行业不断发展和兴起，一个被称为大数据的复杂概念正在浮现。分析的概念旨在理解数据。我们着手描绘和讨论大数据在科学和医疗保健领域不断演变的应用前景，并审视其中的一些机遇和挑战。
进行了一项文献综述，以突出大数据在大规模和小规模科学研究及医疗创新中的应用所带来的影响。
在理解大数据和分析的价值方面，科学家和医疗保健提供者可以相互学习。患者和消费者产生的小数据也需要分析才能发挥作用。连接主义为大数据和分析在科学和医疗保健领域的应用提供了一个框架。该理论帮助个人认识和综合人类联系如何推动数据增长。尽管大数据的数量和速度惊人，但它实际上是关于技术将人类连接起来并帮助他们以新的方式构建知识。结论：在科学和医疗保健领域处理大量结构化和非结构化数据时，大数据及相关分析的概念应得到认真对待。未来需要对数据隐私、保密性和教育等问题进行探索。更多关注来自社交媒体的数据、自我量化运动以及将分析应用于“小数据”也会很有帮助。
