Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

6-2018

Abstract

In this seminar, we will explore how processing rich spatial data is not the only practical (and research-wise promising) application domain for traditional spatial database techniques. An equally promising direction, possibly with low-hanging fruits for research innovation, may be to apply the spatial data management expertise of our community to non-spatial types of queries, and to extend standard, more theoretical operators to large scale datasets with the objective of practical solutions (as opposed to favorable asymptotic complexity alone). As a case study, we will review spatial database work on top-k-related operators (i.e., non-spatial problems) and how it integrates fundamental computational geometric operators with spatial indexing/pruning to produce efficient solutions to practical problems.

Keywords

Database systems, Information management, Asymptotic complexity, Computational geometric, Large-scale datasets, Practical problems, Practical solutions, Spatial data management, Spatial database, Spatial problems, Data handling

Discipline

Databases and Information Systems

Research Areas

Data Science and Engineering

Publication

Proceedings of 5th International ACM SIGMOD Workshop on Managing and Mining Enriched Geo-Spatial Data, GeoRich 2018, Houston, United States, 2018 June 10-15

First Page

25

Last Page

26

ISBN

9781450358323

Identifier

10.1145/3210272.3226094

Publisher

Association for Computing Machinery, Inc

City or Country

Houston, United States

Additional URL

https://doi.org/10.1145/3210272.3226094

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