Biomedical Engineering Reference
In-Depth Information
for auto-searching against all new information being scanned by the
system and alerting a user if novel information is available for one or
more of the things in which they are interested.
Knowledge building through the sharing of knowledge maps is similar
to what is seen in wiki communities where users collaborate around the
development of pages of text that describe various topics. The difference
between shared map building and shared wiki page building is in the
structuring of the data which users are pulling from to create maps in the
fi rst place. TripleMap knowledge maps are effectively subnetworks of
structured, interlinked data describing things and the associations
between them. These subnetworks are portions of the entire master data
network integrated and continuously updated in the TripleMap GEM. In
the wiki scenario there is less structuring of the content generated and it
is more diffi cult to identify interrelationships between the things
mentioned in pages. Despite the differences between TripleMap and
wikis, there are valuable ways in which these two types of systems can be
linked together in order to provide a more comprehensive collaborative
platform for biomedical research. For example, integration of a system
like the Targetpedia (see Harland et al., Chapter 17) with TripleMap
allows users to interact with information about targets both as a text-
based wiki page and then also link out to knowledge maps related to each
target within one integrated system.
19.8 Comparison and integration with
third-party systems
When used in an enterprise context, TripleMap is not redundant with
general-purpose document search systems such as FAST or Google (both
are discussed above). Instead TripleMap provides a framework and
application for the semantic search that enhances the utility of enterprise
document search systems and can be used in conjunction with enterprise
search frameworks such as Google or the FAST search engine.
Additionally, TripleMap is not redundant with applications focused on
quantitative data analytics such as Spotfi re [21] or Tableau [22]. Instead
TripleMap provides an environment in which users can conduct semantic
searches across a large-scale shared master network of data in order to
identify and build 'bird's eye view' representations of what is known in a
given information space. Software bridges to specialized systems such as
Spotfi re or Tableau through available third-party API bridges are being
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