User Evaluation of Map-Based Visual Analytic Tools

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F19%3A73596942" target="_blank" >RIV/61989592:15310/19:73596942 - isvavai.cz</a>
Alternative codes found
RIV/00216224:14310/19:00110457
Result on the web
<a href="https://www.mdpi.com/2220-9964/8/8/363/htm" target="_blank" >https://www.mdpi.com/2220-9964/8/8/363/htm</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/ijgi8080363" target="_blank" >10.3390/ijgi8080363</a>

Result language
angličtina
Original language name
User Evaluation of Map-Based Visual Analytic Tools
Original language description
Big data have also become a big challenge for cartographers, as the majority of big data may be localized. The use of visual analytics tools, as well as comprising interactive maps, stimulates inter-disciplinary actors to explore new ideas and decision-making methods. This paper deals with the evaluation of three map-based visual analytics tools by means of the eye-tracking method. The conceptual part of the paper begins with an analysis of the state-of-the-art and ends with the design of proof-of-concept experiments. The verification part consists of the design, composition, and realization of the conducted eye-tracking experiment, in which three map-based visual analytics tools were tested in terms of user-friendliness. A set of recommendations on GUI (graphical user interface) design and interactive functionality for map makers is formulated on the basis of the discovered errors and shortcomings in the assessed stimuli. The results of the verification were used as inputs for improving the three tested map-based visual analytics tools and might serve as a best practice for map-based visual analytics tools in general, as well as for improving the policy making cycle as elaborated by the European project PoliVisu (Policy Development based on Advanced Geospatial Data Analytics and Visualization).
Czech name
—
Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project
<a href="/en/project/LTACH17002" target="_blank" >LTACH17002: Dynamic mapping methods oriented to risk and disaster management in the era of big data</a><br>
Continuities
O - Projekt operacniho programu

Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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