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Adapting geospatial business intelligence for regional infrastructure planning

Conference Paper


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Abstract


  • Business Intelligence (BI) has traditionally been used in organizations as a strategic tool to

    maximize profit. When coupled with Geographic Information Systems, however, BI can be transformed into

    a cutting edge decision support system for planning local and regional areas, as we demonstrate in this paper.

    Local and regional governments often face a major challenge in terms of developing a holistic view upon

    disjointedly operated utility services in their jurisdictions due to data silos. This limitation has become a

    serious impediment to infrastructure planning and regional adaptation to changes. Geo-BI provides tools to

    manage data coming from multiple and disparate sources, and visualize them through online interactive userinterfaces.

    The SMART Infrastructure Dashboard (SID) is an innovative Geo-BI solution that includes an

    open-source ETL (Extract, Transform and Load) toolkit to handle various datasets, a spatially-enabled data

    warehouse hosted in PostgreSQL/PostGIS and proprietary BI software for creating and administering

    analytical reports and dashboards. SID allows planners and policy makers to analyze the interplay between

    the use of infrastructure services, demographics and weather parameters across multiple spatial and temporal

    scales. Furthermore, SID enables planners to run various what-if scenarios related to projected consumption

    patterns, service vulnerability of utility networks, and transportation demand management. Future research

    involves enabling the analysis of networks of networks through SID to understand the propagation of

    cascading failures and benefits in interconnected utility networks.

Publication Date


  • 2013

Citation


  • Wickramasuriya Denagamage, R. C., Perez, P., Ma, J. & Berryman, M. J. (2013). Adapting geospatial business intelligence for regional infrastructure planning. In J. Piantadosi, R. S. Anderssen & J. Boland (Eds.), 20th International Congress on Modelling and Simulation (pp. 1-7). Australia: The Modelling and Simulation Society of Australia and New Zealand Inc.

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=1140&context=smartpapers

Ro Metadata Url


  • http://ro.uow.edu.au/smartpapers/113

Start Page


  • 1

End Page


  • 7

Abstract


  • Business Intelligence (BI) has traditionally been used in organizations as a strategic tool to

    maximize profit. When coupled with Geographic Information Systems, however, BI can be transformed into

    a cutting edge decision support system for planning local and regional areas, as we demonstrate in this paper.

    Local and regional governments often face a major challenge in terms of developing a holistic view upon

    disjointedly operated utility services in their jurisdictions due to data silos. This limitation has become a

    serious impediment to infrastructure planning and regional adaptation to changes. Geo-BI provides tools to

    manage data coming from multiple and disparate sources, and visualize them through online interactive userinterfaces.

    The SMART Infrastructure Dashboard (SID) is an innovative Geo-BI solution that includes an

    open-source ETL (Extract, Transform and Load) toolkit to handle various datasets, a spatially-enabled data

    warehouse hosted in PostgreSQL/PostGIS and proprietary BI software for creating and administering

    analytical reports and dashboards. SID allows planners and policy makers to analyze the interplay between

    the use of infrastructure services, demographics and weather parameters across multiple spatial and temporal

    scales. Furthermore, SID enables planners to run various what-if scenarios related to projected consumption

    patterns, service vulnerability of utility networks, and transportation demand management. Future research

    involves enabling the analysis of networks of networks through SID to understand the propagation of

    cascading failures and benefits in interconnected utility networks.

Publication Date


  • 2013

Citation


  • Wickramasuriya Denagamage, R. C., Perez, P., Ma, J. & Berryman, M. J. (2013). Adapting geospatial business intelligence for regional infrastructure planning. In J. Piantadosi, R. S. Anderssen & J. Boland (Eds.), 20th International Congress on Modelling and Simulation (pp. 1-7). Australia: The Modelling and Simulation Society of Australia and New Zealand Inc.

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=1140&context=smartpapers

Ro Metadata Url


  • http://ro.uow.edu.au/smartpapers/113

Start Page


  • 1

End Page


  • 7