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Title:
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EXTENDING COLLABORATIVE TAGGING FOR USE WITH SCIENTIFIC DATA |
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Author(s):
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Philip Mcdermott , Steve Pettifer |
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ISBN:
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978-972-8924-78-2 |
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Editors:
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Piet Kommers and Pedro Isaías |
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Year:
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2009 |
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Edition:
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1 |
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Keywords:
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Collaborative Tagging, Hierarchical Tagging, Ontology, eScience, Web 2.0, Bioinformatics |
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Type:
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Full Paper |
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First Page:
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34 |
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Last Page:
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42 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Collaborative tagging has proved a useful classification technique on the web. We describe the technique and its variants,
what it means to tag data and the benefits, under some circumstances, over more traditional classification systems.
Scientific data sets have the necessary properties for tagging, but are often too complex to be categorised using a flat
structure, and are generally organised using formal taxonomies or ontologies. We describe an extension and
implementation to the collaborative tagging technique that enables an ad-hoc hierarchical classification structure to be
generated in order to overcome this shortfall. We posit that using this technique alongside a formal ontology, information
sharing between the structures will elicit a powerful but flexible classification system that can be used on sets of scientific
data previously thought too complex for the tagging technique. |
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