OM3: An Ordered Multi-level Min-Max Representation for Interactive Progressive Visualization of Time Series
Summary: OM3 offers a min-max representation for time series enabling progressive visualization with error-free line rendering via line segments. Incremental tree-based query strategy yields sub-300 ms latency and up to 1,000x speedups vs InfluxDB baselines. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yunhai Wang (Shandong University)
- 2. Yuchun Wang (Shandong University)
- 3. Xin Chen (Shandong University)
- 4. Yue Zhao (Shandong University)
- 5. Fan Zhang (Shandong University)
- 6. Eugene Wu (Columbia University)
- 7. Chi-Wing Fu (Chinese University of Hong Kong)
- 8. Xiaohui Yu (York University)
BibTeX Citation
@inproceedings{wang_sigmod23,
title = {{OM3: An Ordered Multi-level Min-Max Representation for Interactive Progressive Visualization of Time Series}},
author = {Wang, Yunhai and Wang, Yuchun and Chen, Xin and Zhao, Yue and Zhang, Fan and Wu, Eugene and Fu, Chi-Wing and Yu, Xiaohui},
series = {{SIGMOD} '23},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3589290},
url = {https://dl.acm.org/doi/10.1145/3589290},
year = {2023}
}Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,180 | Visualization-aware Time Series Min-Max Caching with Error Bound Guarantees | 2024 | VLDB | 5.949572e-05 |
| 10,415 | Visualization-Oriented Progressive Time Series Transformation | 2026 | SIGMOD | 5.093636e-05 |
| 10,668 | Largest Triangle Sampling for Visualizing Time Series in Database | 2025 | SIGMOD | 5.093636e-05 |
| 11,107 | Representative Time Series Discovery for Data Exploration | 2025 | VLDB | 5.093636e-05 |
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 307 | Approximate Query Processing Using Wavelets | 2000 | VLDB | 0.00021792475 |
| 986 | Effortless Data Exploration with zenvisage: An Expressive and Interactive Visual Analytics System | 2017 | VLDB | 0.0001281777 |
| 1,472 | M4: A Visualization-Oriented Time Series Data Aggregation | 2014 | VLDB | 0.00010668946 |
| 1,634 | Rapid Sampling for Visualizations with Ordering Guarantees | 2015 | VLDB | 0.00010163938 |
| 3,288 | I've Seen "Enough": Incrementally Improving Visualizations to Support Rapid Decision Making | 2017 | VLDB | 7.5578177e-05 |
| 5,454 | ShapeSearch: A Flexible and Efficient System for Shape-based Exploration of Trendlines | 2020 | SIGMOD | 6.2134177e-05 |
| 7,178 | Continuous Prefetch for Interactive Data Applications | 2020 | SIGMOD | 5.6804618e-05 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 3,584 | Extreme Visualization: Squeezing a Billion Records into a Million Pixels | 2008 | SIGMOD |
| 2 | 4,883 | Indexing for Interactive Exploration of Big Data Series | 2014 | SIGMOD |
| 3 | 10,668 | Largest Triangle Sampling for Visualizing Time Series in Database | 2025 | SIGMOD |
| 4 | 3,288 | I've Seen "Enough": Incrementally Improving Visualizations to Support Rapid Decision Making | 2017 | VLDB |
| 5 | 9,034 | Fast and Adaptive Indexing of Multi-Dimensional Observational Data | 2016 | VLDB |
| 6 | 9,757 | Faster Visual Analytics through Pixel-Perfect Aggregation | 2014 | VLDB |
| 7 | 10,415 | Visualization-Oriented Progressive Time Series Transformation | 2026 | SIGMOD |
| 8 | 8,409 | Time Series Representation for Visualization in Apache IoTDB | 2024 | SIGMOD |
| 9 | 1,472 | M4: A Visualization-Oriented Time Series Data Aggregation | 2014 | VLDB |
| 10 | 6,180 | Visualization-aware Time Series Min-Max Caching with Error Bound Guarantees | 2024 | VLDB |