The Usability of a GeoVisual Analytics Environment for the Exploration and Analysis of Different Datasets

Irma Kveladze, Menno-Jan Kraak, C. P. J. M. van Elzakker

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

1 Citation (Scopus)

Abstract

A GeoVisual Analytics (GVA) environment is based on highly interactive and dynamic visualization techniques intending to reveal knowledge in complex and multivariate datasets. By depicting information, these techniques amplify human capabilities and facilitate the performance of cognitive tasks for pattern recognition, decision-making or analytical reasoning. However, the question is whether those visual representations are suitable for visualization of different types of data to perform similar tasks. The limited usability studies that have been done on interactive analytical environments have failed to yield a definite answer. Therefore, this paper presents an evaluation experiment on how an interactive GVA environment can be designed that will effectively support similar task execution processes for different use cases. In the GVA environment investigated, four graphic representations of the Space-Time Cube (STC), graphs and maps are interactively integrated to allow data manipulation from location, attribute and time perspectives for overview and detailed analysis. The results of the experiment revealed that the four visual representations in a GVA environment appear to be effective and efficient to explore different datasets with similar tasks, but require some sophistication.
Original languageEnglish
Title of host publicationICAI 2017 : Advances in Carography and GIScience
EditorsPeterson M.
PublisherSpringer
Publication date2017
Pages207-221
ISBN (Print)978-3-319-57335-9
ISBN (Electronic)978-3-319-57336-6
DOIs
Publication statusPublished - 2017
Event28th International Cartographic Conference - Washington DC, United States
Duration: 2 Jul 20177 Jul 2017
Conference number: 28

Conference

Conference28th International Cartographic Conference
Number28
CountryUnited States
CityWashington DC
Period02/07/201707/07/2017
SeriesLecture notes in geoinformation and Cartography
ISSN1863-2246

Fingerprint

Visualization
Pattern recognition
Decision making
Experiments

Keywords

  • GeoVisual analytics
  • Tools
  • Evaluations

Cite this

Kveladze, I., Kraak, M-J., & van Elzakker, C. P. J. M. (2017). The Usability of a GeoVisual Analytics Environment for the Exploration and Analysis of Different Datasets. In P. M. (Ed.), ICAI 2017: Advances in Carography and GIScience (pp. 207-221). Springer. Lecture notes in geoinformation and Cartography https://doi.org/10.1007/978-3-319-57336-6_15
Kveladze, Irma ; Kraak, Menno-Jan ; van Elzakker, C. P. J. M. / The Usability of a GeoVisual Analytics Environment for the Exploration and Analysis of Different Datasets. ICAI 2017: Advances in Carography and GIScience. editor / Peterson M. Springer, 2017. pp. 207-221 (Lecture notes in geoinformation and Cartography).
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Kveladze, I, Kraak, M-J & van Elzakker, CPJM 2017, The Usability of a GeoVisual Analytics Environment for the Exploration and Analysis of Different Datasets. in P M. (ed.), ICAI 2017: Advances in Carography and GIScience. Springer, Lecture notes in geoinformation and Cartography, pp. 207-221, 28th International Cartographic Conference, Washington DC, United States, 02/07/2017. https://doi.org/10.1007/978-3-319-57336-6_15

The Usability of a GeoVisual Analytics Environment for the Exploration and Analysis of Different Datasets. / Kveladze, Irma; Kraak, Menno-Jan; van Elzakker, C. P. J. M.

ICAI 2017: Advances in Carography and GIScience. ed. / Peterson M. Springer, 2017. p. 207-221 (Lecture notes in geoinformation and Cartography).

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

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Kveladze I, Kraak M-J, van Elzakker CPJM. The Usability of a GeoVisual Analytics Environment for the Exploration and Analysis of Different Datasets. In M. P, editor, ICAI 2017: Advances in Carography and GIScience. Springer. 2017. p. 207-221. (Lecture notes in geoinformation and Cartography). https://doi.org/10.1007/978-3-319-57336-6_15