STORM: Spatio-Temporal Online Reasoning and Management of Large Spatio-Temporal Data
Summary: STORM enables online reasoning and management of large spatio-temporal data. Novel spatial online sampling fuels interactive spatio-temporal analytics; online aggregates with quality guarantees yield immediate approximations, tightening as execution progresses. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Robert Christensen (University of Utah)
- 2. Lu Wang (Hong Kong University of Science and Technology)
- 3. Feifei Li (University of Utah)
- 4. Ke Yi (Hong Kong University of Science and Technology)
- 5. Jun Tang (University of Utah)
- 6. Natalee Villa (University of Utah)
BibTeX Citation
@inproceedings{christensen_sigmod15,
title = {{STORM: Spatio-Temporal Online Reasoning and Management of Large Spatio-Temporal Data}},
author = {Christensen, Robert and Wang, Lu and Li, Feifei and Yi, Ke and Tang, Jun and Villa, Natalee},
series = {{SIGMOD} '15},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/2723372.2735373},
url = {https://dl.acm.org/doi/10.1145/2723372.2735373},
year = {2015}
}
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