Unraveling the Design Space of Immersive Analytics: A Systematic Review

Saffo, David; Bartolomeo, Sara Di; Crnovrsanin, Tarik; South, Laura; Raynor, Justin; Yildirim, Caglar; Dunne, Cody

doi:10.1109/tvcg.2023.3327368

Cited by 5 publications

(1 citation statement)

References 86 publications

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“…Furthermore, da Silva et al [dSTCT19] used a systematic review approach to analyse evaluation practice in AR tools for education focusing mainly on education specific criteria, but also including a more general classification along methodologies. Finally, Saffo et al [SBC*23] presented a design space for immersive analytics also mentioning two different types of evaluation studies, i.e. comparing approaches and understanding how users perform.…”

Section: Introductionmentioning

confidence: 99%

A Systematic Literature Review of User Evaluation in Immersive Analytics

Friedl‐Knirsch,

Pointecker,

Pfistermüller

et al. 2024

Computer Graphics Forum

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User evaluation is a common and useful tool for systematically generating knowledge and validating novel approaches in the domain of Immersive Analytics. Since this research domain centres around users, user evaluation is of extraordinary relevance. Additionally, Immersive Analytics is an interdisciplinary field of research where different communities bring in their own methodologies. It is vital to investigate and synchronise these different approaches with the long‐term goal to reach a shared evaluation framework. While there have been several studies focusing on Immersive Analytics as a whole or on certain aspects of the domain, this is the first systematic review of the state of evaluation methodology in Immersive Analytics. The main objective of this systematic literature review is to illustrate methodologies and research areas that are still underrepresented in user studies by identifying current practice in user evaluation in the domain of Immersive Analytics in coherence with the PRISMA protocol. (see https://www.acm.org/publications/class-2012)

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Section: Introductionmentioning

confidence: 99%

A Systematic Literature Review of User Evaluation in Immersive Analytics

Friedl‐Knirsch,

Pointecker,

Pfistermüller

et al. 2024

Computer Graphics Forum

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Indy Survey Tool: A Framework to Unearth Correlations in Survey Data

Crnovrsanin,

Bartolomeo,

Wilson

et al. 2023

2023 IEEE Visualization and Visual Analytics (VIS)

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Figure 1: An example of how the Indy Survey Tool we present was used in recent survey on Immersive Analytics [16]. The left panel (1) lets users filter using a search bar, timeline, and topic selector. The top bar (2) provides information about the survey and how to add new entries. The center (3) shows a short summary of each included paper. The collapsible visualization panel (4) on the right shows a correlation matrix for two selected dimensions. Interacting with the left and right panels filters the papers displayed in the center. Upon selection of a paper, a detail view pops up with all of its information (not shown).

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