of some of the disciplines it is related with. As it was
discussed previously, the close relationship between
the exposome and toxicogenomics brought the use
of different “omics” technologies and with them as
well a high relevance of bioinformatics approaches
and solutions for data analysis and management.
Additionally, exposome approaches are taking
advantage of the latest advances in systems biology
methodologies and are incorporating and making
extensive use of them. This intensive use of
bioinformatics serves as a link between the
exposome and biomedical informatics. This is so
because bioinformatics approaches related with
health are considered under the umbrella of
biomedical informatics nowadays and due to the
increasing interest in the role of the exposome in
health, the role of bioinformatics applications in this
area should be considered as well. An example of
the high relevance of informatics for the exposome
approaches can be found in the existence of one or
several work packages exclusively devoted to
informatics related aspects in the four major
international exposome projects. (Table 1).
Table 1: Major international projects involving the study
of the Exposome and containing significant informatics
work packages.
Project Name
HELIX - The Human Early Life Exposome. It is a
European funded project focused in the development of
new tools to integrate exposome and childrens’ health
data
http://www.projecthelix.eu/
EXPOSOMICS. It is a European funded projects aiming
to predict individual risk related to the environment.
http://www.exposomicsproject.eu/
HEALS – Health and Environment-wide Associations
based on Large population Surveys. It is a European
funded project.
http://www.heals-eu.eu/
HERCULES – Health and Exposome Research Center:
Understanding Lifetime Exposures. It is an US funded
project.
http://emoryhercules.com/
3.1 The Exposome, Big Data and Small
Data
As it has been previously described one of the most
relevant characteristics of the exposome is that it is
an area where several scientific disciplines converge
and intersect with each other. From a data and
information point of view, this convergence of
multiple disciplines could be translated into a large
diversity of data types and sources of interest that
must be dealt with in the analysis of the exposome.
The different data types that are involved in the
analysis of the exposome range form molecular data
associated either with genomic or pollutant data to
geographical locations. Additionally large data sets
are used in the analysis, coming from a broad variety
of sources (again using as an example the integration
of population scale “omics” studies and large
environmental data sets) that need to be combined.
This combination of large volumes and a large
variety of data types confers exposome data the
category of big data which could be generally
characterised by the four “V’s” (Volume, Variety,
Velocity and Veracity) (A. McAfee et al. 2012)
Even though as it has been discussed before the
exposome is a life-long set of exposures (data)
implying that this is a temporal data collection, The
third V from the big data definition (Velocity) could
be arguably considered as well as part of the
exposome data characteristics due to the continuity
of the measurements that are made during with
many of the devices.
On the other hand the individual and
participatory component of the exposome related
with another increasingly popular topic from an
informatics perspective that is “Small Data”. In
contrast with Big Data, small data come from the
individual digital traces that are created or left
continuously in the use of technology (D. Estrin.
2014). These “Small data” are generated as a
consequence of the use of the portable devices and
self-monitoring practices that could be used to
quantify the individual exposures.
Therefore the exposome represents a multilevel
challenge for the current biomedical informatics
discipline. On one hand the inclusion and
development of exposome data as another element
of biomedical informatics means an extension of an
already existing problem in terms of the needs and
requirements to work in “Big Data” environments
for data analysis and management. In this regard, the
current solutions and approaches would need to be
extended to incorporate these new data sources, and
many of the solutions already in place would just
need to be expanded to accommodate exposome
data.
On the other hand dealing with “Small Data”
represents a new challenge that its starting to be
tackled by biomedical informatics experts. It means
a mutual interest area and therefore it represents a
common area of development where exposome data
should be considered as another source of health
related data and therefore should be incorporated
into future health information systems. The
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