Exploratory analysis of spatial and temporal data - a systematic approach

  title={Exploratory analysis of spatial and temporal data - a systematic approach},
  author={Natalia V. Andrienko and Gennady L. Andrienko},
Exploratory data analysis (EDA) is about detecting and describing patterns, trends, and relations in data, motivated by certain purposes of investigation. [] Key Method They start by developing a general view of data structures and characteristics and then build on top of this a general task typology, distinguishing between elementary and synoptic tasks.

Visual Data Exploration : Tools , Principles , Problems

The author's research interests became very close to those of the Commission on Visualisation of the International Cartographic Association, and the community of researchers in geovisualisation clustering around the Commission enthusiastically accepted their work and adopted them as its integral part.

A framework for exploratory space-time analysis of economic data

A novel way to generalize the characteristics and the structure of space-time data sets, using regional economic data as the example and can be applied to other data sets that are also measured for areal units at multiple points in time.

A framework for exploratory space-time analysis of economic data

  • X. YeS. Rey
  • Economics
    The Annals of Regional Science
  • 2011
The development of exploratory spatial data analysis methods is an active research domain in the field of geographic information science (GIS). At the same time, the coupled space-time attributes of

From Exploratory Data Analysis to Exploratory Spatial Data Analysis

The Exploratory Data Analysis raised by Tuckey [19] has been used in multiple research in many areas but, especially, in the area of the social sciences. This technique searches behavioral patterns

Supporting the Process of Exploring and Interpreting Space–Time Multivariate Patterns: The Visual Inquiry Toolkit

A visual analytics approach that leverages human expertise with visual, computational, and cartographic methods to support the application of visual analytics to relatively large spatio-temporal, multivariate data sets is developed.

Designing Visual Analytics Methods for Massive Collections of Movement Data

This study focuses on data describing movements of multiple discrete entities that change their positions in space while preserving their integrity and identity, and defines the possible types of patterns in such movement data on the basis of an abstract model of the data as a mathematical function that maps entities and times onto spatial positions.

Exploring geo-temporal differences using GTdiff

GTdiff provides a visual approach to representing differences in the data within user-defined spatial and temporal limits, illustrating when and where increases and/or decreases have occurred.

Describing Temporal Correlation Spatially in a Visual Analytics Environment

An interactive visual analytics system for exploring temporal linear correlations across a variety of spatial aggregations and the statistical significance of each linear correlation value is calculated and regions in which the correlation value falls within the 95% confidence interval are highlighted.

A 3D Visualization of Multiple Time Series on Maps

A pictorial representation based on the standard space-time cube metaphor is developed that provides in a single display the overview and details of a large number of time-varying quantities and can be plotted on a geographic map to expose interesting spatio-temporal distributions of the data.



Vikin g Sh ip s A t Su n rise M agic Tree H o u se

    Tiger Tales DK Read ers