Time Series Information Visualization -- A Review of Approaches and Tools
Evandro S. Ortigossa, F\'abio F. Dias, Diego C. Nascimento, Luis Gustavo Nonato

TL;DR
This paper reviews various techniques and tools for visualizing time series data, emphasizing their role in understanding complex, multi-feature temporal datasets and guiding future research in the field.
Contribution
It provides a comprehensive overview of existing visualization approaches, theoretical insights, and design guidelines for time series data with multiple features.
Findings
Highlights challenges in visualizing multi-feature time series
Provides design guidelines for effective visualization systems
Identifies future research directions in the field
Abstract
Time series data are prevalent across various domains and often encompass large datasets containing multiple time-dependent features in each sample. Exploring time-varying data is critical for data science practitioners aiming to understand dynamic behaviors and discover periodic patterns and trends. However, the analysis of such data often requires sophisticated procedures and tools. Information visualization is a communication channel that leverages human perceptual abilities to transform abstract data into visual representations. Visualization techniques have been successfully applied in the context of time series to enhance interpretability by graphically representing the temporal evolution of data. The challenge for information visualization developers lies in integrating a wide range of analytical tools into rich visualization systems that can summarize complex datasets while…
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