OM3: An Ordered Multi-level Min-Max Representation for Interactive Progressive Visualization of Time Series

Author:

Wang Yunhai1ORCID,Wang Yuchun1ORCID,Chen Xin1ORCID,Zhao Yue1ORCID,Zhang Fan2ORCID,Wu Eugene3ORCID,Fu Chi-Wing4ORCID,Yu Xiaohui5ORCID

Affiliation:

1. Shandong University, Qingdao, China

2. Shandong Technology and Business University, Yantai, China

3. Columbia University, New York City, NY, Canada

4. Chinese University of Hong Kong, Sha Tin, Hong Kong

5. York University, Toronto, Canada

Abstract

We present a novel multi-level representation of time series called OM3 that facilitates efficient interactive progressive visualization of large data stored in a database and supports various interactions such as resizing, panning, zooming, and visual query. Based on our proposed line-segment aggregation, this representation can produce error-free line visualizations that preserve the shape of a time series in windows of arbitrary sizes. To reduce the interaction latency, we develop an incremental tree-based query strategy to support progressive visualizations, allowing a finer control on the accuracy-time tradeoff. We quantitatively compare OM3 with state-of-the-art methods, including a method implemented on a leading time-series database InfluxDB, in two settings with databases residing either in the local area network or on the cloud. Results show that OM^3 maintains a low latency within 300~ms on the web browser and a high data reduction ratio regardless of the data size (ranging from millions to billions of records), achieving around 1,000 times faster than the state-of-the-art methods on the largest dataset experimented with.

Publisher

Association for Computing Machinery (ACM)

Reference34 articles.

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1. Visualization-Aware Time Series Min-Max Caching with Error Bound Guarantees;Proceedings of the VLDB Endowment;2024-04

2. A Survey on Progressive Visualization;IEEE Transactions on Visualization and Computer Graphics;2023

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