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Usability evaluation in immersive data analytics environments

Grant number: 17/23684-3
Support type:Scholarships abroad - Research
Effective date (Start): May 15, 2018
Effective date (End): May 14, 2019
Field of knowledge:Physical Sciences and Mathematics - Computer Science - Computer Systems
Principal researcher:Tiago Silva da Silva
Grantee:Tiago Silva da Silva
Host: Frank Maurer
Home Institution: Instituto de Ciência e Tecnologia (ICT). Universidade Federal de São Paulo (UNIFESP). Campus São José dos Campos. São José dos Campos , SP, Brazil
Research place: University of Calgary, Canada  

Abstract

Immersive Analytics explores new immersive technologies to support decision making and data analysis. Immersive Analytics explores interaction and display technologies to immerse users in their data. The possible target domains for Immersive Analytics include Life Sciences, Disaster and Emergency Management, Archeology, Business Intelligence, Transport and Logistics, Personal Information Management, Environmental Monitoring, Health Informatics, and Education. There is still a lack of understanding on design issues and usability concerns for creating effective user interfaces for data analytics in immersive environments. Much of the existing work is focused on narrow applications for visualizing specific data sets in few immersive devices. Thus, evaluating the usability of an Immersive Analytics environment is a challenging task. To the best of our knowledge, there is one study in the literature focused specifically on evaluating usability of such domain. This study tried to apply Nielsen's usability heuristics to evaluate an immersive analytic system in virtual reality for multiple abstract views of data correlated to a geographic visualization. Moreover, because Immersive Analytics is an emerging field, there is not a well-defined set of guidelines from which to abstract heuristics that address the unique challenges of its design space. Therefore, the main goal of this project is to propose a set of heuristics to guide the inspection evaluation as well as the design of Immersive Data Analytics Applications. The proposed set of heuristics will be validated through a rigid process of experimentation based on established guidelines to this aim. Finally, noteworthy that the results of the development of this project will contribute directly to the interests of UNIFESP-SJC, as well as CEMADEN, both in the research field and practical application. (AU)

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