Biomedical Engineering Reference
In-Depth Information
synthesised, essentially detailing their hypotheses and the data that led
them there. As one would expect, the scientists used lab note books to
record experiments, data mining tools to analyse data and read many
scientifi c papers. However, like many organisations, the only place in
which each 'story' was brought together was in a slide deck, driven by the
need to present coherent arguments to the group members and
management. Of course, this is not optimal with these fi les (including
revisions and variants) quickly becoming scattered through hard drives
and document management systems. Furthermore, they often lack
clear links to data supporting conclusions and have no capability to link
shared biology across different projects. This latter point can be
especially critical in a group running a number of concurrent investigations;
staying abreast of the major elements of each project and their
interdependencies can be diffi cult. Therefore, the IDU and the
computational sciences group began an experiment to develop tools to
move disease knowledge management away from slides and into a more
fi t for purpose environment.
17.2.1 Design choices
Any piece of software that allows users to enter content could fall into
the category of 'knowledge management'. However, there are a number
of tools that allow users to represent coherent stories in an electronic
representation. These range from notebook-style applications [32] to
general mind-mapping software (e.g. [33]) and more specialised variants
such as the Compendium platform for idea management [34]. A
particularly relevant example is the I2 Analysts Notebook [35], an
application used throughout law enforcement, intelligence and insurance
agencies to represent complex stories in semi-graphical form. Although
we had previously explored this for knowledge representation [2] and
were impressed with its usability and relationship management, its lack
of 'tuning' to the biomedical domain was a major limiting factor.
A further type of system considered was one very tuned to disease
modelling, such as the Biological Expression Language (BEL) Framework
produced by Selventa [36]. This approach describes individual molecular
entities in a causal network, allowing computer modelling and simulation
to be performed to understand the effects of any form of perturbation.
Although this is an important technology, it works at a very different
level to the needs of the IDU. Indeed, our aim was not to try to create a
mathematical or causal model of the disease, but to provide somewhere
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