Situated visualisation (SV), which embeds data representations directly within the context to which they refer, offers a paradigm for augmenting perception, understanding, and decision-making in real-world environments. Inspired by comic-books and previous work on visualisation, this article presents the relevance of SV in the form of superpowers. Each superpower is explained through the lens of augmented reality (AR). By mapping these capabilities, the article positions SV not just as a technical advancement, but as a new frontier in human-centred design, inviting researchers to rethink the role of visualisation in a world where data and reality increasingly coexist. Therefore, the paper also offers guidelines for its effective design and implementation. Finally, a structured evaluation questionnaire (the VIEWUS), specifically designed for AR-based Situated visualisation systems, is proposed. VIEWUS integrates key factors such as usability, engagement, situational awareness, visual fatigue, and workload, combining and adapting items from established instruments. It allows for a comprehensive assessment using a 5-point Likert scale and supports iterative improvement of SV systems based on user feedback.

This paper presents an Augmented Reality (AR) application based on Situated Visualization (SV), aimed at increasing awareness of air pollution. Given that technological progress must be achieved through meticulous evaluation processes, the article also presents the assessment of the stated application. Therefore, this article begins by examining how AR applications are appraised. Building upon this review, and focusing particularly on those where SV is provided, a discussion is presented regarding the points that must be carefully considered when evaluating this type of AR application, as well as the factors that need to be measured, along with the most popular methods for evaluating these factors. However, it is noted that if a simultaneous evaluation of all the factors that matter to SV is intended, the number of questions to be asked could be significant. Therefore, a preliminary approach to enable such an appraisal is proposed and used in the mentioned application to demonstrate the merits of the proposed Questionnaire.

Augmented Reality (AR) has the ability to display and interact with additional information aligned with the real world and to support context-driven visualization techniques. Situated Visualization (SV) is a method to represent data in a context that encompasses all the visualizations that change their appearance based on context. Therefore, since AR is typically used so that the user can visualize extra information regarding the surrounding real world environment, this technology is well suited for SV and presents high potential in many situations, as are the cases of collaborative/assistive tasks in the maintenance area and supporting decision-making. AR-based visualizations are commonly constrained to the users' unique egocentric view-point, which reduces their ability to explore all the richness of available information. This limitation is particularly evident in situations that require overviews of all information inside and out of the user's field of view (FOV). This article proposes multi-perspective renderings, transitional interfaces, and the use of multimodal information as methods to extend the user's egocentric viewpoint. The main idea is to coherently present and augment, in the same user's display, dynamic and static feeds of several real and virtual egocentric viewpoints, related to and relevant for the user's task.

Situated Visualization (SV), encompassing all the visualizations that change their appearance based on context, by considering the visualizations that are relevant to the physical context in which they are displayed [1], has been recognized as a method with potential in many situations, as is the case of supporting decision making [2]. Augmented and Mixed Reality (AR/MR) are well suited to assist in such scenarios, given its ability to display additional data regarding the real-world context and be supported by context-driven visualization techniques [3]. Though some perspectives on the SV model have been proposed, such as space, time, place, activity and community, an appropriate systematization, covering the main definitions and perspectives has yet to be established. Hence, there is an urge to obtain a more comprehensive description. The work presented in this paper characterizes the SV model, within the scope of AR/MR, shows a critical analysis of the existing knowledge, expanding the SV model and in turn hoping to elicit discussion within the research community.

Mixed reality (MR) is well suited for situated visualization (SV), a method to represent data in a context, with potential in many situations. However, MR-based visualizations are commonly constrained to the users' single egocentric viewpoint reducing their ability to explore all the available information. This article discusses the main limitations and challenges of this approach based on the analysis of existing literature and identifies opportunities, as well as relevant aspects that must be considered when devising new methods aimed at overcoming those limitations.

The decision-making process and the development of decision support systems (DSS) have been enhanced by a variety of methods originated from information science, cognitive psychology and artificial intelligence over the past years. Situated visualization (SV) is a method to present data representations in context. Its main characteristic is to display data representations near the data referent. As augmented reality (AR) is becoming more mature, affordable and widespread, using it as a tool for SV becomes feasible in several situations. In addition, it may provide a positive contribution to more effective and efficient decision-making, as the users have contextual, relevant and appropriate information to endorse their choices. As new challenges and opportunities arise, it is important to understand the relevance of intertwining these fields. Based on a literature analysis, this paper addresses and discusses current areas of application, benefits, challenges and opportunities of using SV through AR to visualize data in context and to support a decision-making process and its importance in future DSS.