Scientific data mining, integration, and visualization

Bob Mann, Roy Williams, Malcolm Atkinson, Ken Brodlie, Amos Storkey, Christopher K. I. Williams

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

This report summarises the workshop on Scientific Data Mining, Integration and Visualization (SDMIV) held at the e-Science Institute, Edinburgh (eSI[1] ) on 24-25 October 2002, and presents a set of recommendations arising from the discussion that took place there. The aims of the workshop were three-fold: (A) To inform researchers in the SDMIV communities of the infrastructural advances being made by computing initiatives, such as the Grid; (B) To feed back requirements from the SDMIV areas to those developing the computational infrastructure; and (C) To foster interaction among all these communities, since the coordinated efforts of all of them will be required to realise the potential for scientific knowledge extraction offered by e-science initiatives worldwide.
The workshop had about fifty participants, ranging from software engineers developing Grid infrastructure software, to computer scientists with expertise in data mining and visualization, to application specialists from a wide range of disciplines, including astronomy, atmospheric science, bioinformatics, chemistry, digital libraries, engineering, environmental science, experimental physics,
marine sciences, oceanography, and statistics. It was felt that further meetings should be held, to bring together the SDMIV community, or subsets thereof: the participants felt that the overlapping interests of the communities represented at the workshop made this group more than the sum of its parts, and that future interaction between these communities would be very beneficial. The workshop produced the following Recommendations, which are detailed in Section
Original languageEnglish
Title of host publicationReport of workshop held at the National e-Science Institute
Number of pages24
Publication statusPublished - 2002


Dive into the research topics of 'Scientific data mining, integration, and visualization'. Together they form a unique fingerprint.

Cite this