Multiresolution data aggregation for analytical exploration of large relational data

Mustafa Sanver; Li Yang

doi:10.1117/12.812092

20 January 2009 Multiresolution data aggregation for analytical exploration of large relational data

Mustafa Sanver, Li Yang

Proceedings Volume 7243, Visualization and Data Analysis 2009; 72430M (2009) https://doi.org/10.1117/12.812092
Event: IS&T/SPIE Electronic Imaging, 2009, San Jose, California, United States

Abstract

Analytical exploration of large data sets poses fundamental challenges to both database and data visualization. This paper introduces multiresolution data aggregation as an efficient representation of large relational data for interactive data exploration. Such a multiresolution data representation has build-in support of data scalability. Data aggregated at multiple resolutions are stored in internal nodes of a partition-based high dimensional tree index. Such a piggyback ride of aggregated data efficiently supports resolution-based data access patterns such as overview-and-drill-down. A software tool is developed to demonstrate the feasibility and effectiveness of this technique for multiresolution visual exploration of general purpose relational data sets.

Citation Download Citation

Mustafa Sanver and Li Yang "Multiresolution data aggregation for analytical exploration of large relational data", Proc. SPIE 7243, Visualization and Data Analysis 2009, 72430M (20 January 2009); https://doi.org/10.1117/12.812092

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