Graham, Martin (2001) Visualising multiple overlapping classification hierarchies. PhD thesis, Napier University.
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The revision or reorganisation of hierarchical data sets can result in many possible hierarchical classifications composed of the same or overlapping data sets existing in parallel with each other. These data sets are difficult for people to handle and conceptualise, as they try
to reconcile the different perspectives and structures that such data represents. One area where this situation occurs is the study of botanical taxonomy, essentially the classification and naming of plants. Revisions, new discoveries and new dimensions for classifying plants lead to a proliferation of classifications over the same set of plant data. Taxonomists would like a method of exploring these multiple overlapping hierarchies for interesting information, correlations, or anomalies.
The application and extension of Information Visualisation (IV) techniques, the graphical display of abstract information, is put forward as a solution to this problem. Displaying the multiple classification hierarchies in a visually appealing manner along with powerful interaction mechanisms for examination and exploration of the data allows taxonomists to unearth previously hidden information. This visualisation gives detail that previous visualisations and statistical overviews cannot offer.
This thesis work has extended previous IV work in several respects to achieve this goal. Compact, yet full and unambiguous, hierarchy visualisations have been developed. Linking and brushing techniques have been extended to work on a higher class of structure, namely overlapping trees and hierarchies. Focus and context techniques have been pushed to achieve new effects across the visually distinct representations of these multiple hierarchies.
Other data types, such as multidimensional data and large cluster hierarchies have also been displayed using the final version of the visualisation.
|Item Type:||Thesis (PhD)|
|Uncontrolled Keywords:||Taxonomy; Hierarchical classification; Overlapping data sets; Information Visualisation; Multidimensional data; Large cluster hierarchies;|
|University Divisions/Research Centres:||Faculty of Engineering, Computing and Creative Industries > School of Engineering and the Built Environment|
|Dewey Decimal Subjects:||500 Science > 570 Life sciences; biology > 578 Natural history of organisms|
000 Computer science, information & general works > 000 Computer science, knowledge & systems > 004 Data processing & computer science
|Library of Congress Subjects:||Q Science > QH Natural history > QH301 Biology|
Q Science > QA Mathematics > QA76 Computer software
|Depositing User:||Users 10 not found.|
|Date Deposited:||02 Oct 2008 17:48|
|Last Modified:||12 Jan 2011 04:49|
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