Biomedical Engineering Reference
In-Depth Information
19.1 The challenge of Big Data
In recent decades computationally based technologies including the
internet, mobile devices, inexpensive high-performance workstations,
and digital imaging have catalyzed entirely new ways for humans to
generate, access, share, and visualize information. As a result, humanity
now produces quantities of digital data on an annual basis that far exceed
the amount of non-digital data previously generated over the entire span
of human history. For example, it is estimated that in 2011 the amount
of digital information generated will be 1 800 000 petabytes (PB) or 1.8
zettabytes (ZB) [3]. In comparison:
■
5 MB would contain the complete works of Shakespeare [4];
■
10 TB represents the entire printed collection of the US Library of
Congress [4];
■
200 PB contains all printed material ever generated by humanity [4].
In other words, in 2011 alone, humanity will generate 9000 times
more digital information than all of the information ever printed in
physical books, magazines, and newspapers. Furthermore, humanity's
ability to generate and handle digital data through advances in the
means of its generation, transmission, and storage is increasing at an
exponential rate [5].
This mind-boggling scale of data is commonly referred to as 'Big Data'.
The phrase 'Big Data' is not meant to denote a specifi c data scale such as
'petabytes' or 'exabytes' (10
15
and 10
18
bytes, respectively), but instead to
be indicative of the ever-increasing sea of data available to humans and
the challenges associated with attempting to make sense of it all [6]. The
Big Data explosion in the biomedical research sector has been further
catalyzed by the completion of the human genome sequencing project
[7], the sequencing of genomes from a number of species, and the
emergence of a range of correlated, omics and next-generation
technologies (e.g. microarrays, next-generation sequencing approaches)
as discussed in a number of other chapters in this topic.
The availability of Big Data presents humans with tremendous
capabilities to 'see the big picture' and gain a 'bird's eye' view of patterns,
trends, and interrelationships under consideration and it stands to reason
that individuals, teams, and organizations that are able to harness Big
Data for searching, analyzing, collaborating, and identifying patterns
will be able to make faster and more effective decisions. In fact a new
class of workers, often referred to as 'data scientists' or 'knowledge
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