Marviq: Quality-Aware Geospatial Visualization of Range-Selection Queries Using Materialization

Dong, Liming; Bai, Qiushi; Kim, Taewoo; Chen, Taiji; Liu, Weidong; Li, Chen

doi:10.1145/3318464.3389730

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Cited by 3 publications

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“…Funke and Weitbrecht [32] presented a theoretical result on the number of triangles in a Delaunay triangulation for an arbitrary point set in random order which implies that the α-structure has an expected size in O(n log n), where n is the number of events. Furthermore, Dong et al [21] recently considered SQL queries with ad-hoc range conditions on numerical attributes supporting time-window queries for spatial visualizations.…”

Section: Related Workmentioning

confidence: 99%

A Time-Windowed Data Structure for Spatial Density Maps

Bonerath

Niedermann

Diederich

et al. 2020

Proceedings of the 28th International Conference on Advances in Geographic Information Systems

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Section: Related Workmentioning

confidence: 99%

A Time-Windowed Data Structure for Spatial Density Maps

Bonerath

Niedermann

Diederich

et al. 2020

Proceedings of the 28th International Conference on Advances in Geographic Information Systems

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Less is More: How Fewer Results Improve Progressive Join Query Processing

Zhang,

Eldawy

2023

35th International Conference on Scientific and Statistical Database Management

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Choi

et al. 2021

Proc. VLDB Endow.

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Kernel density visualization (KDV) has been the de facto method in many spatial analysis tasks, including ecological modeling, crime hotspot detection, traffic accident hotspot detection, and disease outbreak detection. In these tasks, domain experts usually generate multiple KDVs with different bandwidth values. However, generating a single KDV, let alone multiple KDVs, is time-consuming. In this paper, we develop a share-and-aggregate framework, namely SAFE, to reduce the time complexity of generating multiple KDVs given a set of bandwidth values. On the other hand, domain experts can specify bandwidth values on the fly. To tackle this issue, we further extend SAFE and develop the exact method SAFE all and the 2-approximation method SAFE exp which reduce the time complexity under this setting. Experimental results on four large-scale datasets (up to 4.33M data points) show that these three methods achieve at least one-order-of-magnitude speedup for generating multiple KDVs in most of the cases without degrading the visualization quality.

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Marviq: Quality-Aware Geospatial Visualization of Range-Selection Queries Using Materialization

Cited by 3 publications

References 39 publications

A Time-Windowed Data Structure for Spatial Density Maps

A Time-Windowed Data Structure for Spatial Density Maps

Less is More: How Fewer Results Improve Progressive Join Query Processing

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