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Visual Exploration of Time Series Anomalies with Metro-Viz

Summary: Metro-Viz is visualization-driven exploration tool for time-series anomaly results, enabling comparison and what-if reasoning. It offers workload-aware data-management and demonstrates applicability across multiple time-series datasets and detectors. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5817
Venue
SIGMOD
Year
2019
Pagerank
5.4388258e-05
Overall Rank
8,377 | 42.53%
DOI
10.1145/3299869.3320247

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{eichmann_sigmod19,
        title = {{Visual Exploration of Time Series Anomalies with Metro-Viz}},
        author = {Eichmann, Philipp and Solleza, Franco and Tatbul, Nesime and Zdonik, Stan},
        series = {{SIGMOD} '19},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3299869.3320247},
        url = {https://dl.acm.org/doi/10.1145/3299869.3320247},
        year = {2019}
}

Incoming Citations (Sorted by Pagerank)

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Outgoing Citations (Sorted by Pagerank)

Showing 5 of 5 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
3,322 RINSE: Interactive Data Series Exploration with ADS+ 2015 VLDB 7.5213802e-05
3,968 Qetch: Time Series Querying with Expressive Sketches 2018 SIGMOD 6.9840567e-05
4,362 Interactive Time Series Analytics Powered by ONEX 2017 SIGMOD 6.7440799e-05
6,004 Data Ingestion for the Connected World 2017 CIDR 6.0124846e-05
7,772 Querying and Exploring Polygamous Relationships in Urban Spatio-Temporal Data Sets 2017 SIGMOD 5.5468715e-05
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