Visualisation to Aid Biodiversity Studies through Accurate Taxonomic Reconciliation.

Graham, Martin, Craig, Paul and Kennedy, Jessie (2008) Visualisation to Aid Biodiversity Studies through Accurate Taxonomic Reconciliation. In: Proceedings of British National Conference on Database Systems: Sharing Data, Information and Knowledge. Lecture Notes in Computer Science, 5071 . Springer-Verlag Berlin, Heidelberg, pp. 280-291. ISBN 978-3-540-70503-1

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All aspects of organismal biology rely on the accurate identification
of specimens described and observed. This is particularly important for
ecological surveys of biodiversity, where organisms must be identified and
labelled, both for the purposes of the original research, but also to allow
reinterpretation or reuse of collected data by subsequent research projects. Yet
it is now clear that biological names in isolation are unsuitable as unique
identifiers for organisms. Much modern research in ecology is based on the
integration (and re-use) of multiple datasets which are inherently complex,
reflecting any of the many spatial and temporal environmental factors and
organismal interactions that contribute to a given ecosystem. We describe
visualization tools that aid in the process of building concept relations between
related classifications and then in understanding the effects of using these
relations to match across sets of classifications.

Item Type: Book Section
Print ISSN: 0302-9743
ISBN: 978-3-540-70503-1
Electronic ISSN: 1611-3349
Additional Information: Paper delivered at Cardiff on 10th July 2008 in Session 2 of the British National Conference on Databases (BNCOD) Workshop 2008, "Biodiversity informatics: challenges in modelling and managing biodiversity knowledge".
Uncontrolled Keywords: Multiple datasets; Classification; Taxonomy; Biodiversity; Biology; Computer programming; Visualisation;
University Divisions/Research Centres: Faculty of Engineering, Computing and Creative Industries > School of Computing
Dewey Decimal Subjects: 000 Computer science, information & general works > 000 Computer science, knowledge & systems > 004 Data processing & computer science
500 Science > 570 Life sciences; biology
Library of Congress Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QH Natural history
Item ID: 3037
Depositing User: Computing Research
Date Deposited: 26 Oct 2009 11:49
Last Modified: 15 Oct 2014 10:26

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