Answering Why and When?: A Systematic Literature Review of Application Scenarios and Evaluation for Immersive Data Visualization Analytics

Answering Why and When?: A Systematic Literature Review of Application Scenarios and Evaluation for Immersive Data Visualization Analytics

Najwa Ayuni Jamaludin, Farhan Mohamed, Vei Siang Chan, Mohd Shahrizal Sunar, Ali Selamat, Ondrej Krejcar, Andres Iglesias
Copyright: © 2023 |Pages: 29
DOI: 10.4018/JCIT.323799
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Immersive analytics (IA) is a fast-growing research field that concerns improving and facilitating human sense making and data understanding through an immersive experience. Understanding the suitable application scenario that will benefit from IA enables a shift towards developing effective and meaningful applications. This paper aims to explore tasks and scenarios that can benefit from IA by conducting a systematic review of existing studies and mapping them according to the multi-level typology for abstract visualization tasks, which is also known as the what-why-how framework. The study synthesizes several works to answer the why within the context of multiple levels of specificity. In addition, this study also explores the application domains and IA guiding scenarios to address when scenarios best integrate with IA. Then, the paper discusses the IA evaluation types and research methods to evaluate an IA application that can promote effective user engagement in IA. Finally, the limitations and potential future works are discussed.
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The emergence of big data marked the beginning of a new era of data visualization, leading to a significant evolution of visual analytics over the past several decades. As the volume and intricacy of data rise, the importance of improved data visualization tools also increases. In response to this demand, new data visualization market leaders have emerged, including Tableau, Spotfire, and QlikView. These companies provide sophisticated features and capabilities that enable users to visualize and interact with data in novel manners. Established corporations like Microsoft, IBM, and Oracle are also major players in the data analytics industry. Microsoft offers PowerPivot for data modeling and analysis. It later released Power View, a data visualization tool that allows for the creation of interactive visualizations. IBM provides Cognos Insight, a data visualization product that enables the creation of dynamic dashboards and reports with tools for exploration, analysis, and visualization. Moreover, Oracle acquired Endeca, a data discovery and visualization company. The organization integrated its technology into its business intelligence and analytics solutions, allowing users to explore and analyze data using interactive dashboards and reports. Over the years, existing software has also evolved to incorporate new features and functionality that reflect the changing requirements of consumers in this era of big data.

The use of immersive technologies, namely virtual reality (VR), augmented reality (AR), and mixed reality (MR), have gained widespread notoriety and acceptance. Furthermore, their usage extends beyond the gaming and entertainment industries. Immersive applications have been commonly used in fields like geographic information systems (GIS), healthcare, engineering, data analytics, and visualizations. As the need for enhanced data visualization tools grows more prevalent, immersive technologies usage in data analytics has evolved into a field known as immersive analytics (IA). This new approach to data analysis relies on VR, AR, and MR technologies to create an immersive environment for exploring and analyzing complex data. By allowing users to visualize and interact with data in three dimensions (3D), IA promotes user engagement with data in a more natural and intuitive way. Users within an IA environment can perform real-time data exploration and manipulation by moving around and interacting with 3D visualizations in a virtual space, thus making it easier to analyze and navigate large datasets and gaining better insights into data through a user-friendly, immersive data interaction. This approach is particularly useful for processing and visualizing complex datasets, such as those typically found in scientific research, engineering, healthcare, industry, business, and other domains.

Although IA is still in its infancy, the use of these technologies in data visualization has been proposed since the early 1990s (Fonnet & Prie, 2021). Representing and displaying 3D data in an immersive environment offers better insight and enhances human perception. Furthermore, this type of data representation could be an enhanced alternative to some limitations in conventional two-dimensional (2D) data representation. Promising opportunities have sparked the interest of researchers from fields like data visualization, VR, human-computer interaction (HCI), and computer graphics into the field of IA to improve the understanding of data through immersive features. As a result, the use of immersive technologies in visualization tasks has exploded into a growing field of research.

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