A scalable cyberinfrastructure solution to support big data management and multivariate visualization of time-series sensor observation data

WenWen Li, Sheng Wu, Miaomiao Song, Xiran Zhou

Research output: Contribution to journalArticle

8 Scopus citations

Abstract

This paper reports our research in developing a cyberinfrastructure platform to support multivariate visualization of data collected from distributed sensor network. Three new techniques were introduced in this platform: (1) a hybrid data caching strategy that takes advantages of a scalable and distributed time series database, OpenTSDB, to realize efficient data retrieval; (2) a hyper-dimensional data cube is established to map and translate multivariate and heterogeneous sensor data into a common data structure to support location-aware visual analysis; and (3) a data-driven visualization module is implemented to support interactive and dynamic visualization on a simulated virtual globe. A series of experiments were conducted to demonstrate the good runtime performance of the proposed system. We expect this work to make a major contribution to both the visualization building block development in cyberinfrastructure research and the advancement of visual presentation and analysis of sensor data in domain sciences.

Original languageEnglish (US)
Pages (from-to)449-464
Number of pages16
JournalEarth Science Informatics
Volume9
Issue number4
DOIs
StatePublished - Nov 1 2016

Keywords

  • Big data
  • Distributed computing
  • Hadoop
  • Hyper-dimensional data cube
  • Location-aware visualization
  • OpenTSDB

ASJC Scopus subject areas

  • Earth and Planetary Sciences(all)

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