32WWW.IWR.CO.UK/ACADEMIC
inspire ideas and emergent projects. It does so by dynamically harvesting
offers useful and efficient ways of and indexing all repositories,
searching for academic research output, irrespective of their format or level of
as well as identifying academics, experts quality relating to metadata.
and commercial partner interests who The IDOL approach brings
can help in different fields. meaning to unstructured content
Faster discovery of relevant across a raft of formats, geographical
knowledge and contextually relevant locations and languages, and enables
information from the widest range of organisations to automatically index,
repositories speeds up discovery in tag and classify data where metadata
the early and labour-intensive part of is poor or non-existent in addition to
the research cycle: the literature search. allowing them to capitalise on any
Enabling more rapid and relevant existing metadata investments.
discovery of key information at this The project partners also developed
point speeds up the overall research a metadata aggregation facility and
and innovation-to-discovery lifecycle. explored parallel development using
The UK Institutional Repository open source technology via the
Search project has provided a National Centre for Text Mining.
computing power of the UK
Institutional Repository Search
Overlaying a dynamic search and discovery
demonstrator (web address at end of
article). The demonstrator is manual intervention by individual
capability on institutional and related repositories fundamentally different from Google. repository administrators.
can inspire both ideas and emergent projects
It utilises subject-specific metadata Susan re-enters her initial natural
where it exists at artefact level in UK language query (“stem cells and
institutional repositories to identify spectroscopy”). The meaning-based
key documents, as well as using a engine returns 836 bibliographic
demonstrator service to show how SUSAN’S SAVIOUR keyword to text-mine artefacts that articles from across the 106 UK
meaning-based computing can So how does all this help Susan? its neural-network algorithms think institutional repositories it is
leverage knowledge and information After rejecting Google Search’s might be conceptually related. It also harvesting. Furthermore, it has
assets within UK (and global) 50,000-strong context-insensitive hit text-mines repository areas that clustered the results in a dynamic
research and teaching communities. It list, she goes to the meaning-based Google Scholar cannot access without and machine-driven browse list that
Knowledge is
no longer shelved
The Cambridge Journals Digital Archive
contains more than 160 journals, more than
3 million pages and more than 8 million linked
references. Knowledge is now more visible
and more searchable than ever.
journals.cambridge.org/archives
INFORMATION WORLD REVIEW DECEMBER 2009/JANUARY 2010 WWW.IWR.CO.UK
FT_Launch_Advert_IWR.indd 1 02/11/2009 11:56:32
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