Big Data for Disease Control: Interdisciplinary approaches to data linkage and management

Abstract

The source of tremendous promise and unsettling surveillance alike, the term ‘Big Data’ has attracted substantial public attention in recent years, garnering widespread press coverage and debate in equal measure. In reality it is like any other complex social phenomena; a number of varied resources and means deployed in multiple ways toward meeting diverse ends. Generally accepted by most to be a poor term, ‘Big Data’ has traditionally been understood in terms of its “volume, variety and velocity”, however the sheer enormity of this phenomenon is not its defining characteristic, and what classifies examples of big data lies beyond its sheer scale or method of analysis. Big data is fundamentally networked, and notable not only in terms of its size, but predominantly in its ‘relationality’ to other data. Its value is derived from the patterns and connections that can be drawn between pieces of information - about individuals, their relation to others, from international organizations to microscopic organisms, or even simply about the structure of a network itself.

Infectious Disease Epidemiology is just one of the fields that has branched out in tandem with this explosion of data. With unprecedented datasets, computational power and analytical tools available, the door has been opened on a whole world of new research questions