GeoBrick: exploration of spatiotemporal data

Ji Hwan Park; Saad Nadeem; Arie Kaufman

doi:10.1007/s00371-017-1461-y

GeoBrick: exploration of spatiotemporal data

Ji Hwan Park
, Saad Nadeem
, Arie Kaufman

Computer Science

Stony Brook University

Stony Brook University

Research output: Contribution to journal › Article › peer-review

9 Scopus citations

Abstract

We present GeoBrick, an interactive technique for exploring spatiotemporal data. In GeoBrick, each region is comprised of multivariate data, which is encoded into simple shapes with colors. Additionally, users can adjust the resolution of data values to get an overview as well as details of the data. GeoBrick allows users to (1) juxtapose data and spatial profiles of discontiguous regions, (2) identify temporal patterns of user-defined classes of regions, and (3) comparatively evaluate across distinct configurations of regions. We demonstrate the effectiveness and efficacy of GeoBrick using two case studies.

Original language	English
Pages (from-to)	191-204
Number of pages	14
Journal	Visual Computer
Volume	35
Issue number	2
DOIs	https://doi.org/10.1007/s00371-017-1461-y
State	Published - Feb 13 2019

Keywords

Interactive data analysis
Multivariate data
Spatiotemporal visualization
Visual analytics

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10.1007/s00371-017-1461-y

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title = "GeoBrick: exploration of spatiotemporal data",

abstract = "We present GeoBrick, an interactive technique for exploring spatiotemporal data. In GeoBrick, each region is comprised of multivariate data, which is encoded into simple shapes with colors. Additionally, users can adjust the resolution of data values to get an overview as well as details of the data. GeoBrick allows users to (1) juxtapose data and spatial profiles of discontiguous regions, (2) identify temporal patterns of user-defined classes of regions, and (3) comparatively evaluate across distinct configurations of regions. We demonstrate the effectiveness and efficacy of GeoBrick using two case studies.",

keywords = "Interactive data analysis, Multivariate data, Spatiotemporal visualization, Visual analytics",

author = "Park, \{Ji Hwan\} and Saad Nadeem and Arie Kaufman",

note = "Publisher Copyright: {\textcopyright} 2017, Springer-Verlag GmbH Germany, part of Springer Nature.",

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doi = "10.1007/s00371-017-1461-y",

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T2 - exploration of spatiotemporal data

AU - Park, Ji Hwan

AU - Nadeem, Saad

AU - Kaufman, Arie

PY - 2019/2/13

Y1 - 2019/2/13

N2 - We present GeoBrick, an interactive technique for exploring spatiotemporal data. In GeoBrick, each region is comprised of multivariate data, which is encoded into simple shapes with colors. Additionally, users can adjust the resolution of data values to get an overview as well as details of the data. GeoBrick allows users to (1) juxtapose data and spatial profiles of discontiguous regions, (2) identify temporal patterns of user-defined classes of regions, and (3) comparatively evaluate across distinct configurations of regions. We demonstrate the effectiveness and efficacy of GeoBrick using two case studies.

AB - We present GeoBrick, an interactive technique for exploring spatiotemporal data. In GeoBrick, each region is comprised of multivariate data, which is encoded into simple shapes with colors. Additionally, users can adjust the resolution of data values to get an overview as well as details of the data. GeoBrick allows users to (1) juxtapose data and spatial profiles of discontiguous regions, (2) identify temporal patterns of user-defined classes of regions, and (3) comparatively evaluate across distinct configurations of regions. We demonstrate the effectiveness and efficacy of GeoBrick using two case studies.

KW - Interactive data analysis

KW - Multivariate data

KW - Spatiotemporal visualization

KW - Visual analytics

UR - https://www.scopus.com/pages/publications/85035775499

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DO - 10.1007/s00371-017-1461-y

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VL - 35

SP - 191

EP - 204

JO - Visual Computer

JF - Visual Computer

IS - 2

ER -

GeoBrick: exploration of spatiotemporal data

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Keywords

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