Immersive Analytics of Anomalies in Multivariate Time Series Data with Proxy Interaction

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In industry and science, sensor data play a vital role in research, optimisation, monitoring, testing and many other use cases. When performing tests with repeated cycles of similar behaviour, e.g., durability tests, it is often important to find anomalous sensor behaviour that deviates from regular patterns in the data. We here explore the design space of VRbased immersive analytics for time series data, for use e.g., in engineering contexts where an underlying application is also given in VR. The use of 3D visualisation for time series exploration is a much-discussed topic and careful consideration for its use must be taken. With the rise of immersive environments, we re-visit the classic problem of 3D time series visualisation and introduce an immersive walk-up usable interaction proxy that supports efficient navigation of otherwise possibly occluded time series views. The proxy indicates anomalies in the data for easy access and provides efficient zooming and filtering controls, among other effective interaction possibilities. This approach is combined with suitable data analysis techniques, providing an environment for effective and efficient immersive anomaly detection and comparative data analysis that we call WaveCharts. We demonstrate the applicability of our approach by two real-world use cases, and we discuss the necessary tools it provides to aid the analysis process of large sensor data.
Original languageEnglish
Title of host publicationProceedings - 2020 International Conference on Cyberworlds, CW 2020
EditorsAlexei Sourin, Christophe Charier, Christophe Rosenberger, Olga Sourina
PublisherInstitute of Electrical and Electronics Engineers
Pages94-101
Number of pages8
ISBN (Electronic)978-1-7281-6497-7
DOIs
Publication statusPublished - Sep 2020
Event19th International Conference on Cyberworlds: CW 2020 - Virtual, Caen, France
Duration: 29 Sep 20201 Oct 2020
https://cyberworlds2020.sciencesconf.org/

Conference

Conference19th International Conference on Cyberworlds
Abbreviated titleCW2020
CountryFrance
CityVirtual, Caen
Period29/09/201/10/20
Internet address

Keywords

  • Anomaly Search
  • Immersive Analytics
  • Multivariate Time Series
  • Virtual Reality

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Media Technology
  • Modelling and Simulation

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