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28 Aug 2015 00:00
Academic information solutions providers such as Elsevier sit on
vast databases of high-quality
scientific, technical and medical
research content that has been
collected, curated, aggregated, disseminated and published for over
With the transformational
changes brought on by the digital
age, our role as an academic publisher has expanded.
The convergence of cloud
computing, big data and social
networking is creating new
expectations, possibilities and
opportunities for publishers and
the researcher community.
While providing high-quality
content will always be crucial, it is
no longer enough.
Our job doesn’t end with publishing articles in journals; it actually begins there.
Today we must leverage big data
applications to add value to that
content and develop better, faster,
more efficient tools and solutions.
A significant part of a publisher’s
role now is to provide the right
content, to the right audience, in
the right context, when and how
they want it.
Elsevier has embraced the evolution of technology by building the
necessary digital infrastructure for
effective management and facilitation of scientific research.
New capture, search, discovery
and analysis tools such as Scopus
can, thanks to big data, now draw
insight from the increasing pools
of unstructured data.
It is a now a necessary responsibility for those of us in scholarly
publishing to help researchers
find relevant data quickly through
smart collection tools, recommended reading lists and data
banks that offer a variety of sort-and-search applications.
Scholarly publishing is also
not just about giving our customers what they want; it’s also
about anticipating their needs.
Today, Elsevier is able to recommend articles to researchers
they might otherwise not have
Through big data predictive
analytics, we now have the ability
to proactively play “matchmaker”
by recommending and promoting relevant research and related
information from a broad range of
Examples of where big data is
used to drive science research
innovation at Elsevier include:
1. Enhanced content: We are
adding enhanced functionality to static content with our
Article of the Future, to provide
a dynamic and interactive reading experience by incorporating
tagged and searchable audio
files, videos, interactive images
and figures, embedded maps,
downloadable tables and sharing capabilities.
Re-use of content: allows
users to interact with content in
new, insightful ways. One example
of how we’re re-using content lies
in text and data mining (TDM).
We offer application programming interfaces (APIs) that allow
researchers to explore patterns
across large content databases
and derive meaningful analyses
from these correlations.
3. Solutions content is tailored
content that helps researchers find what they’re looking for
more quickly by delivering not
just information, but answers.
We are creating digital solutions
such SciVal that take advantage
of big data, allowing researchers
to easily discover evidence-based
insights from massive data sets
in ways that were not previously
As with all new technology, we
do not and cannot know what can
be fully achieved with big data
As the century advances, one
thing’s certain: big data is truly
entrenched in transforming academic publishing processes for
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