Biomedical Engineering Reference
In-Depth Information
article. Then, a new copy of the PDF is automatically downloaded via
the company's digital delivery service, allowing copyright to be
respected and usage/access metrics to be accurately maintained.
15.4 History and future of Utopia
Documents
Utopia Documents was originally developed in collaboration with
Portland Press Ltd, who have been using the software since December
2009 to enhance the content of their fl agship publication, the
Biochemical
Journal
[16]. A publishers' version of the software allows the journal's
editorial team to 'endorse' annotations, confi rming the validity of specifi c
associations between terms in articles and particular database entries.
This has allowed thorough but rapid markup (typically, 10-15 minutes
per article, depending on its suitability for annotation) as part of the
normal publishing process. To date, around 1000 articles have been
annotated in this way as part of the
Semantic Biochemical Journal
(
http://
www.biochemj.org
). More recently, the publications of the Royal Society
of Chemistry [17] have been augmented by automatically generated
annotations on the chemical compounds mentioned in articles, and a
plug-in to highlight these in Utopia Documents is included in the latest
releases (covering around 50 000 articles, at the time of writing). Other
extensions include linking articles automatically to their Altmetric [18]
statistics (giving an indication of the popularity of an article based on its
citation in blogs, tweets, and other social media), and to online data
repositories such as Dryad [19].
Recently, we have engaged in projects with pharmaceutical companies
to install the system within an enterprise environment. Utopia consists of
two main components, the PDF viewer installed on any user's PC, and a
server, which holds the annotations, fi ngerprints, and other essential
meta-data. Installation of this server behind the corporate fi rewall
provides the security and privacy often required by commercial
organizations. In addition, the system will then have access to secure
in-house text-mining and data services. Ultimately, this allows commercial
entities to use the software without fear of their activities being tracked
by competitors, or their sensitive in-house knowledge 'leaking' into the
public domain. We have explored two major approaches to this
confi guration: the traditional single installation on a company server, and
a cloud-based approach. For the latter, a service provider hosts a secure,
tailored instance of the server to which only users from a specifi c company
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