A framework for using self-organising maps to analyse spatiotemporal patterns, exemplified by analysis of mobile phone usage

Gennady Andrienko, Natalia Andrienko, Peter Bak, Sebastian Bremm, Daniel Keim, Tatiana von Landesberger, Christian Pölitz, Tobias Schreck

Research output: Contribution to journalArticlepeer-review

30 Scopus citations

Abstract

We suggest a visual analytics framework for the exploration and analysis of spatially and temporally referenced values of numeric attributes. The framework supports two complementary perspectives on spatio-temporal data: as a temporal sequence of spatial distributions of attribute values (called spatial situations) and as a set of spatially referenced time series of attribute values representing local temporal variations. To handle a large amount of data, we use the self-organising map (SOM) method, which groups objects and arranges them according to similarity of relevant data features. We apply the SOM approach to spatial situations and to local temporal variations and obtain two types of SOM outcomes, called spacein- time SOM and time-in-space SOM, respectively. The examination and interpretation of both types of SOM outcomes are supported by appropriate visualisation and interaction techniques. This article describes the use of the framework by an example scenario of data analysis. We also discuss how the framework can be extended from supporting explorative analysis to building predictive models of the spatio-temporal variation of attribute values. We apply our approach to phone call data showing its usefulness in real-world analytic scenarios.

Original languageEnglish
Pages (from-to)200-221
Number of pages22
JournalJournal of Location Based Services
Volume4
Issue number3
DOIs
StatePublished - 1 Sep 2010
Externally publishedYes

Keywords

  • Geovisualisation
  • Spatio-temporal data
  • Visual cluster analysis

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'A framework for using self-organising maps to analyse spatiotemporal patterns, exemplified by analysis of mobile phone usage'. Together they form a unique fingerprint.

Cite this