T HE birth of big data, as a concept if not as a term, is usually
associated with a META Group report by Doug Laney
entitled “3-D Data Management: Controlling Data Volume,
Velocity, and Variety” published in 2001 [1]. Further developments
now suggest big data problems are identified by the
so-called “5V”: volume (quantity of data), variety (data from
different categories), velocity (fast generation of new data), veracity
(quality of the data), and value (in the data) [2].
For a long time the development of big data technologies was
inspired by business intelligence [3] and by big science (such
as the Large Hadron Collider at CERN) [4]. But when in 2009
Google Flu, simply by analyzing Google queries, predicted flulike
illness rates as accurately as the CDC’s enormously complex
and expensive monitoring network [5], some analysts started to
claim that all problems of modern healthcare could be solved
by big data [6].
In 2005, the term virtual physiological human (VPH) was
introduced to indicate “a framework of methods and technologies
that, once established, will make possible the collaborative