Title :
SEE: a Spatial Exploration Environment based on a direct-manipulation paradigm
Author :
Kaushik, Sudhir R. ; Rundensteiner, Elke A.
Author_Institution :
Oracle Corp., Redwood Shores, CA, USA
Abstract :
The need to provide effective tools for analyzing and querying spatial data is becoming increasingly important with the explosion of data in applications such as geographic information systems, image databases, CAD, and remote sensing. The SEE (Spatial Exploration Environment) is the first effort at applying direct-manipulation visual information seeking (VIS) techniques to spatial data analysis by visually querying as well as browsing spatial data and reviewing the visual results for trend analysis. The SEE system incorporates a visual query language (SVIQUEL) that allows users to specify the relative spatial position (both topology and direction) between objects using direct manipulation. The quantitative SVIQVEL sliders (S-sliders) are complemented by the qualitative active-picture-for-querying (APIQ) interface that allows the user to specify qualitative relative position queries. APIQ provides qualitative visual representations of the quantitative query specified by the S-sliders. This increases the utility of the system for spatial browsing and spatial trend discovery with no particular query in mind. The SVIQUEL queries are processed using a k-Bucket index structure specifically tuned for incremental processing of the multidimensional range queries that represent the class of queries that can be expressed by SVIQUEL. We have also designed a tightly integrated map visualization that helps to preserve the spatial context and a bar visualization that provides a qualitative abstraction of aggregates
Keywords :
data analysis; image retrieval; query languages; visual databases; visual languages; CAD; S-sliders; SEE; Spatial Exploration Environment; aggregates; bar visualization; browsing; direct manipulation paradigm; direct manipulation visual information seeking techniques; geographic information systems; image databases; incremental processing; k-Bucket index structure; map visualization; multidimensional range queries; qualitative abstraction; qualitative active-picture-for-querying interface; relative spatial position; remote sensing; spatial data analysis; spatial data querying; trend analysis; visual query language; Data analysis; Database languages; Explosions; Geographic Information Systems; Image analysis; Image databases; Information analysis; Remote sensing; Topology; Visualization;
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on