WWW.IWR.CO.UK/ACADEMIC31
Mining the mountain
UK universities are
uniquely placed to
re-energise the economy
by using their vast data
and knowledge assets to
drive innovation.
Vic Lyte and
Sophia Jones explain
how meaning-based
computing can help the
UK to harness the true
value of academic
bibliographic data and
expertise assets
M
eet Susan. She’s a of descriptive metadata quality is
researcher who highly variable across institutions. In
submits a proposal practice, a busy academic submitting
to study an area a digital asset to a repository or
relating to the use of archive is not concerned about the
spectroscopy to better understand associated metadata schemas needed article we’ll be going back to Susan to the aggregated results presents major
stem cells. She is trying to isolate the to retrieve their work from the widest see how meaning-based computing challenges to a federated higher-level
key variables underlying such studies. and unpredictable range of search and helped her. simple search facility.
So she goes to Google Scholar and discovery contexts. Led by Mimas (at the University of Rather than presenting the user
focuses her preliminary search on the The challenge for the universities is Manchester), in conjunction with with a very long list of aggregated
subject-specific terms “stem cells and how to exploit their vast data and UKOLN (at the University of Bath) articles and associated artefacts, a
spectroscopy”. Google Scholar knowledge assets – often funded by and SHERPA (at the Universities of retrieval facility is much more useful
returns with a daunting list of 50,400 public and commercial investment – Nottingham, Bristol and Heriot Watt), if it can reindex the sub-corpus for
artefacts ranked according to the to drive academic and commercial the Institutional Repository Search conceptual relevance to what the
number of contextually unrelated hits innovation. There has been project found that meaning-based, user is looking for. This requires a
rather than the focus of inquiry Susan substantial investment in exposing pattern-recognition and text-mining machine to understand the concepts
is seeking. these information assets to the technology offered a practical step- implicit within a given item-level
And that’s just the stuff that Google research community to accelerate the change in knowledge discovery. artefact and to be able to discover,
knows about. Far more is hidden discovery-to-innovation cycle. Using Autonomy’s IDOL cluster, prioritise and establish
within the UK’s 106 institutional (Intelligent Data Operating Layer) relationships within the overall sub-
university repositories, which hold DYNAMIC AND RESPONSIVE engine to take advantage of its corpus. It’s an idea that fits well with
over half a million artefacts. There is What Susan and the research robustness, scalability and current visions of the web, and
a vast quantity of information community need is a more dynamic adaptability, the project incorporated technological changes and
residing within UK universities and and responsive knowledge a variety of search and discovery developments relating to machine-
tapping it effectively is the toughest of infrastructure that will ultimately functionality: simple metadata search; assisted search and discovery, such as
full-text indexing of documents and the emerging Web 3.0.
associated digital artefacts; text-
There is a vast quantity of information residing
mining of full-text documents; A KNOWLEDGE ENGINE
automatic subject classification; Meaning-based computing is a key
within UK universities and tapping it
dynamic clustering and serendipitous driver here and will undoubtedly
effectively is the toughest of nuts to crack
browsing; term-based document have a major impact on current and
classification and visualisation next-generation search, discovery and
approaches to search results. knowledge infrastructures for current
The geographic dispersal and and future researchers and teachers.
nuts to crack. Susan’s frustration in allow them to translate hard-to-find variability in implementation of UK Ultimately, it relates to optimising
trying to find a needle in a haystack is information assets into innovation. university individual repositories research and scholarly enquiries and
shared by academics and researchers UK education research body JISC creates a major challenge for search translating them into new products,
all over the country. commissioned the UK Institutional and discovery services. A simple new ways of looking at social
With the exposure and citation of Repository Search project to address Google search box and a long list of infrastructures and new approaches
study outputs a key research driver, this core requirement. After a three- returned (keyword) artefacts are no to important global challenges such
deposition into university repositories year technology evaluation with the longer sufficient. as water and energy.
is growing exponentially. Some of academic and research community, In the latter case, each repository- Overlaying a dynamic search and
those repository contents are visible the project has demonstrated the level search engine returns lists whose discovery capability on existing
to search engines such as Google, but benefits of a meaning-based rankings relate to its individual default institutional and related repositories
many are not. Additionally the level computing approach. Later on in this or customised settings. Reorganising provides a knowledge engine that can
WWW.IWR.CO.UK INFORMATION WORLD REVIEW DECEMBER 2009/JANUARY 2010
Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36  |  Page 37  |  Page 38  |  Page 39  |  Page 40  |  Page 41  |  Page 42  |  Page 43  |  Page 44