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Multi-scale analysis of linear data in a two-dimensional space

Yi Qiang UGent, Seyed Hossein Chavoshi, Steven Logghe, Philippe De Maeyer UGent and Nico Van de Weghe UGent (2014) INFORMATION VISUALIZATION. 13(3). p.248-265
abstract
Many disciplines are faced with the problem of handling time-series data. This study introduces an innovative visual representation for time series, namely the continuous triangular model. In the continuous triangular model, all subintervals of a time series can be represented in a two-dimensional continuous field, where every point represents a subinterval of the time series, and the value at the point is derived through a certain function (e. g. average or summation) of the time series within the subinterval. The continuous triangular model thus provides an explicit overview of time series at all different scales. In addition to time series, the continuous triangular model can be applied to a broader sense of linear data, such as traffic along a road. This study shows how the continuous triangular model can facilitate the visual analysis of different types of linear data. We also show how the coordinate interval space in the continuous triangular model can support the analysis of multiple time series through spatial analysis methods, including map algebra and cartographic modelling. Real-world datasets and scenarios are employed to demonstrate the usefulness of this approach.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
information, GIS, time intervals, decision-making, triangular model, multi-criteria analysis, information visualization, multi-scale analysis, Time series, linear data
journal title
INFORMATION VISUALIZATION
Inf. Vis.
volume
13
issue
3
pages
248 - 265
Web of Science type
Article
Web of Science id
000337711400005
JCR category
COMPUTER SCIENCE, SOFTWARE ENGINEERING
JCR impact factor
0.541 (2014)
JCR rank
84/104 (2014)
JCR quartile
4 (2014)
ISSN
1473-8716
DOI
10.1177/1473871613477853
language
English
UGent publication?
yes
classification
A1
copyright statement
I have transferred the copyright for this publication to the publisher
id
5908674
handle
http://hdl.handle.net/1854/LU-5908674
date created
2015-03-23 10:32:49
date last changed
2016-12-19 15:38:42
@article{5908674,
  abstract     = {Many disciplines are faced with the problem of handling time-series data. This study introduces an innovative visual representation for time series, namely the continuous triangular model. In the continuous triangular model, all subintervals of a time series can be represented in a two-dimensional continuous field, where every point represents a subinterval of the time series, and the value at the point is derived through a certain function (e. g. average or summation) of the time series within the subinterval. The continuous triangular model thus provides an explicit overview of time series at all different scales. In addition to time series, the continuous triangular model can be applied to a broader sense of linear data, such as traffic along a road. This study shows how the continuous triangular model can facilitate the visual analysis of different types of linear data. We also show how the coordinate interval space in the continuous triangular model can support the analysis of multiple time series through spatial analysis methods, including map algebra and cartographic modelling. Real-world datasets and scenarios are employed to demonstrate the usefulness of this approach.},
  author       = {Qiang, Yi and Chavoshi, Seyed Hossein and Logghe, Steven and De Maeyer, Philippe and Van de Weghe, Nico},
  issn         = {1473-8716},
  journal      = {INFORMATION VISUALIZATION},
  keyword      = {information,GIS,time intervals,decision-making,triangular model,multi-criteria analysis,information visualization,multi-scale analysis,Time series,linear data},
  language     = {eng},
  number       = {3},
  pages        = {248--265},
  title        = {Multi-scale analysis of linear data in a two-dimensional space},
  url          = {http://dx.doi.org/10.1177/1473871613477853},
  volume       = {13},
  year         = {2014},
}

Chicago
Qiang, Yi, Seyed Hossein Chavoshi, Steven Logghe, Philippe De Maeyer, and Nico Van de Weghe. 2014. “Multi-scale Analysis of Linear Data in a Two-dimensional Space.” Information Visualization 13 (3): 248–265.
APA
Qiang, Yi, Chavoshi, S. H., Logghe, S., De Maeyer, P., & Van de Weghe, N. (2014). Multi-scale analysis of linear data in a two-dimensional space. INFORMATION VISUALIZATION, 13(3), 248–265.
Vancouver
1.
Qiang Y, Chavoshi SH, Logghe S, De Maeyer P, Van de Weghe N. Multi-scale analysis of linear data in a two-dimensional space. INFORMATION VISUALIZATION. 2014;13(3):248–65.
MLA
Qiang, Yi, Seyed Hossein Chavoshi, Steven Logghe, et al. “Multi-scale Analysis of Linear Data in a Two-dimensional Space.” INFORMATION VISUALIZATION 13.3 (2014): 248–265. Print.