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Bibliographic Details
Main Authors: Jin, Duosi, Xu, Jianqiu, Zhang, Guidong
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2601.01361
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author Jin, Duosi
Xu, Jianqiu
Zhang, Guidong
author_facet Jin, Duosi
Xu, Jianqiu
Zhang, Guidong
contents Large-scale time series visualization often suffers from excessive visual clutter and redundant patterns, making it difficult for users to understand the main temporal trends. To address this challenge, we present VARTS, an interactive visual analytics tool for representative time series selection and visualization. Building upon our previous work M4-Greedy, VARTS integrates M4-based sampling, DTW-based similarity computation, and greedy selection into a unified workflow for the identification and visualization of representative series. The tool provides a responsive graphical interface that allows users to import time series datasets, perform representative selection, and visualize both raw and reduced data through multiple coordinated views. By reducing redundancy while preserving essential data patterns, VARTS effectively enhances visual clarity and interpretability for large-scale time series analysis. The demo video is available at https://youtu.be/mS9f12Rf0jo.
format Preprint
id arxiv_https___arxiv_org_abs_2601_01361
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle VARTS: A Tool for the Visualization and Analysis of Representative Time Series Data
Jin, Duosi
Xu, Jianqiu
Zhang, Guidong
Graphics
Databases
Software Engineering
Large-scale time series visualization often suffers from excessive visual clutter and redundant patterns, making it difficult for users to understand the main temporal trends. To address this challenge, we present VARTS, an interactive visual analytics tool for representative time series selection and visualization. Building upon our previous work M4-Greedy, VARTS integrates M4-based sampling, DTW-based similarity computation, and greedy selection into a unified workflow for the identification and visualization of representative series. The tool provides a responsive graphical interface that allows users to import time series datasets, perform representative selection, and visualize both raw and reduced data through multiple coordinated views. By reducing redundancy while preserving essential data patterns, VARTS effectively enhances visual clarity and interpretability for large-scale time series analysis. The demo video is available at https://youtu.be/mS9f12Rf0jo.
title VARTS: A Tool for the Visualization and Analysis of Representative Time Series Data
topic Graphics
Databases
Software Engineering
url https://arxiv.org/abs/2601.01361