OutViz: Visualizing the Outliers of Multivariate Time Series

Jake Gonzalez, Tommy Dang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper proposes OutViz, a dual view framework for representing and filtering multivariate time series data to highlight abnormal patterns in a dataset. The first view of the proposed visualization incorporates a parallel coordinate chart that allows the user to analyze the scores of features extracted from a dimensionality reduction density-based clustering outlier detection algorithm to determine why a particular time series is predicted to be an outlier. Also included on the parallel coordinates chart is an outlier score rank axis that allows the user to select a range of time series data to be filtered and displayed on the second view of the framework. The second view of our proposed framework uses a multi-line chart to represent how each time series variable changes over a range of time. Each time series is represented as a line with the position on the horizontal axis representing a point in time, while the vertical axis encodes the data value. Use cases using real-world multivariate time series data are demonstrated to show the advantages of using the proposed framework for data analytics as well as some findings uncovered while using OutViz on life expectancy data from 236 countries between the year 1960 and 2018, and carbon dioxide emissions data from 210 countries between the year 1960 and 2016.

Original languageEnglish
Title of host publicationIAIT 2021 - 12th International Conference on Advances in Information Technology
Subtitle of host publicationIntelligence and Innovation for Digital Business and Society
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450390125
DOIs
StatePublished - Jun 29 2021
Event12th International Conference on Advances in Information Technology: Intelligence and Innovation for Digital Business and Society, IAIT 2021 - Virtual, Online, Thailand
Duration: Jun 29 2021Jul 1 2021

Publication series

NameACM International Conference Proceeding Series

Conference

Conference12th International Conference on Advances in Information Technology: Intelligence and Innovation for Digital Business and Society, IAIT 2021
Country/TerritoryThailand
CityVirtual, Online
Period06/29/2107/1/21

Keywords

  • Density-based Clustering
  • Dimensionality Reduction
  • Outlier Detection
  • Parallel Coordinates

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