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    Data warehouse structuring methodologies for efficient mining of Western Australian petroleum data sources

    19356_downloaded_stream_448.pdf (505.4Kb)
    Access Status
    Open access
    Authors
    Nimmagadda, Shastri
    Dreher, Heinz
    Rudra, Amit
    Date
    2005
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Nimmagadda, Shastri L. and Dreher, Heinz and Rudra, Amit. 2005. Data warehouse structuring methodologies for efficient mining of Western Australian petroleum data sources, in Chang, E. and Dillon, T. and Yu, X. (ed), 3rd IEEE International Conference on Industrial Informatics (INDIN), Aug 10-12 2005, pp. 611-616. Perth, WA: IEEE.
    Source Title
    3rd IEEE International Conference on Industrial Informatics (INDIN 2005)
    Source Conference
    3rd IEEE International Conference on Industrial Informatics (INDIN 2005)
    DOI
    10.1109/INDIN.2005.1560446
    Faculty
    Curtin Business School
    School of Information Systems
    School
    Centre for Extended Enterprises and Business Intelligence
    Remarks

    Copyright 2005 IEEE

    This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Curtin University of Technology's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org.

    By choosing to view this document, you agree to all provisions of the copyright laws protecting it.

    URI
    http://hdl.handle.net/20.500.11937/10682
    Collection
    • Curtin Research Publications
    Abstract

    Representing the knowledge domain of a petroleum system is a complex problem. In the present study, logical modelling of shared attributes of resources industry entities (dimensions or objects) has been used for construction of a dynamic and time-variant metadata model. This work demonstrates effectiveness of multidimensional data modelling for petroleum industry, which will be further investigated for fine-grain data presentation and interpretation for quality knowledge discovery.

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