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Visualisation and Exploration of Scientific Data Using Graphs

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Data Mining

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3755))

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Abstract

We present a prototype application for graph-based exploration and mining of online databases, with particular emphasis on scientific data. The application builds structured graphs that allow the user to explore patterns in a data set, including clusters, trends, outliers, and relationships. A number of different graphs can be rapidly generated, giving complementary insights into a given data set. The application has a Flash-based graphical interface and uses semantic information from the data sources to keep this interface as intuitive as possible. Data can be accessed from local and remote databases and files. Graphs can be explored using an interactive visual browser, or graph-analytic algorithms. We demonstrate the approach using marine sediment data, and show that differences in benthic species compositions in two Antarctic bays are related to heavy metal contamination.

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Author information

Authors and Affiliations

  1. Department of the Environment and Heritage, Australian Antarctic Division, Channel Highway, Australian Government, Kingston, 7050, Australia

    Ben Raymond & Lee Belbin

Authors
  1. Ben Raymond
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  2. Lee Belbin
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Editor information

Editors and Affiliations

  1. The Australian Taxation Office,  

    Graham J. Williams

  2. School of Computing and Mathematics, University of Western Sydney, Sydney, NSW, Australia

    Simeon J. Simoff

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© 2006 Springer-Verlag Berlin Heidelberg

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Raymond, B., Belbin, L. (2006). Visualisation and Exploration of Scientific Data Using Graphs. In: Williams, G.J., Simoff, S.J. (eds) Data Mining. Lecture Notes in Computer Science(), vol 3755. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11677437_2

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  • DOI: https://doi.org/10.1007/11677437_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-32547-5

  • Online ISBN: 978-3-540-32548-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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