Big Data in science and healthcare: a review of recent literature and perspectives. Contribution of the IMIA Social Media Working Group

M. M. Hansen, T. Miron-Shatz, A. Y. S. Lau, C. Paton

Research output: Contribution to journalReview articlepeer-review

92 Citations (Scopus)
2 Downloads (Pure)


Objectives: 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.

Methods: 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.

Results: 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.

Original languageEnglish
Pages (from-to)21-26
Number of pages6
JournalYearbook of Medical Informatics
Publication statusPublished - 15 Aug 2014

Bibliographical note

Copyright the Publisher 2014. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.


  • analytics
  • big data
  • connectivism
  • healthcare
  • higher education
  • quantified self Introduction
  • Science


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