NDLI: ABSTRACT Query, Analysis, and Visualization of Hierarchically Structured Data using Polaris

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ABSTRACT Query, Analysis, and Visualization of Hierarchically Structured Data using Polaris

Content Provider	CiteSeerX
Author	Stolte, Chris
Abstract	In the last several years, large OLAP databases have become common in a variety of applications such as corporate data warehouses and scientific computing. To support interac-tive analysis, many of these databases are augmented with hierarchical structures that provide meaningful levels of ab-straction that can be leveraged by both the computer and analyst. This hierarchical structure generates many chal-lenges and opportunities in the design of systems for the query ~ analysis, and visualization of these databases. In this paper, we present an interactive visual exploration tool that facilitates exploratory analysis of data warehouses with rich hierarchical structure, such as might be stored in data cubes. We base this tool on Polaris, a system for rapidly constructing table-based graphical displays of multidimen-sional databases. Polaris builds visualizations using an alge-braic formalism derived from the interface and interpreted as a set of queries to a database. We extend the user inter-face, algebraic formalism, and generation of data queries in Polaris to expose and take advantage of hierarchical struc-ture. In the resulting system, analysts can navigate through the hierarchical projections of a database, rapidly and incre-mentally generating visualizations for each projection. 1.
File Format	PDF
Access Restriction	Open
Subject Keyword	Hierarchically Structured Data Abstract Query Hierarchical Structure Interac-tive Analysis Interactive Visual Exploration Tool Exploratory Analysis Hierarchical Struc-ture Generating Visualization Rich Hierarchical Structure Query Analysis Data Cube Meaningful Level Scientific Computing User Inter-face Corporate Data Warehouse Data Warehouse Multidimen-sional Database Data Query Table-based Graphical Display Algebraic Formalism Hierarchical Projection Last Several Year Many Chal-lenges Alge-braic Formalism Large Olap Database
Content Type	Text

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