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To support the nuances of collaborative work, many researchers have been exploring the field of Augmented Reality (AR), aiming to assist in co-located or remote scenarios. Solutions using AR allow taking advantage from seamless integration of virtual objects and real-world objects, thus providing collaborators with a shared understanding or common ground environment. However, most of the research efforts, so far, have been devoted to experiment with technology and mature methods to support its design and development. Therefore, it is now time to understand where the field stands and how well can it address collaborative work with AR, to better characterize and evaluate the collaboration process. In this article, we perform an analysis of the different dimensions that should be taken into account when analysing the contributions of AR to the collaborative work effort. Then, we bring these dimensions forward into a conceptual framework and propose an extended human-centered taxonomy for the categorization of the main features of Collaborative AR. Our goal is to foster harmonization of perspectives for the field, which may help create a common ground for systematization and discussion. We hope to influence and improve how research in this field is reported by providing a structured list of the defining characteristics. Finally, some examples of the use of the taxonomy are presented to show how it can serve to gather information for characterizing AR-supported collaborative work, and illustrate its potential as the grounds to elicit further studies. [ABSTRACT FROM AUTHOR]

Educational Data Virtual Lab (EDVL) is an open-source platform for data exploration and analysis that combines the power of a coding environment, the convenience of an interactive visualization engine, and the infrastructure needed to handle the complete data lifecycle. Based on the building blocks of the FIWARE European platform and Apache Zeppelin, this tool allows domain experts to become acquainted with data science methods using the data available within their own organization, ensuring that the skills they acquire are relevant to their field and driven by their own professional goals. We used EDVL in a pilot study in which we carried out a focus group within a multinational company to gain insight into potential users' perceptions of EDVL, both from the educational and operational points of view. The results of our evaluation suggest that EDVL holds a great potential to train the workforce in data science skills and to enable collaboration among professionals with different levels of expertise. [ABSTRACT FROM AUTHOR]

With the widespread advent of visualization techniques to convey complex data, visualization literacy (VL) is growing in importance. Two noteworthy facets of literacy are user understanding and the discovery of visual patterns with the help of graphical representations. The research literature on VL provides useful guidance and opportunities for further studies in this field. This introduction summarizes and presents research on VL that examines how well users understand basic and advanced data representations. To the best of our knowledge, this is the first tutorial article on interactive VL. We describe evaluation categories of existing relevant research into unique subject groups that facilitate and inform comparisons of literacy literature and provide a starting point for interested readers. In addition, the introduction also provides an overview of the various evaluation techniques used in this field of research and their challenging nature. Our introduction provides researchers with unexplored directions that may lead to future work. This starting point serves as a valuable resource for beginners interested in the topic of VL. [ABSTRACT FROM AUTHOR]

Decision-making processes and decision support systems (DSS) have been improved by a variety of methods originated from several scientific fields, such as information science and artificial intelligence (AI). Situated visualization (SV) allows presenting visual data representations in context and may support better DSS. 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 viable in several situations. Moreover, it may provide a positive contribution to more effective and efficient decision-making, as the users have contextual, relevant, and appropriate information that fosters more informed choices. As new challenges and opportunities arise, it is important to understand the relevance of intertwining these fields. Based on literature analysis, this paper introduces the main concepts involved, and, through practical examples, addresses and discusses current areas of application, benefits, challenges, and opportunities of using SV through AR to visualize data in context to support better decision-making processes. In the end, a set of guidelines for the design and implementation of DSS based on situated augmented reality are proposed. [ABSTRACT FROM AUTHOR]

Assembly processes require now more than ever a systematic way to improve efficiency complying with increasing product demand. Several industrial scenarios have been using augmented reality (AR) to enhance environments with different types of information and influence the overall user satisfaction and performance. The purpose of this work is to evaluate three different AR-based methods that can be used to support users during the execution of assembly procedures. The AR methods evaluated are handheld mobile AR, indirect AR (showing the augmented scene on a monitor) and see-through head-mounted display. A user study was performed to assess performance, mental and physical workload, as well as acceptance of the aforementioned methods. Results from a thirty participants study did not reveal a best method in terms of performance and user preference, showing that all methods are adequate to support users. However, the study highlights the strengths and weaknesses of each method, which may lead to potential advantages in specific use cases. [ABSTRACT FROM AUTHOR]

The ability to recognize misleading data visualizations is a key aspect of visualization literacy. In this article, we argue that learning to successfully identify a deceptive graphic requires strategies that deliberately force learners to take an active role in the visualization process. We describe a series of experiments where three groups of learners were shown various deceptive graphics and asked to answer a series of questions. Three different interventions were analyzed to compare the educational effectiveness of the strategies used to engage learners into the process of identifying deceptive visualizations. Our results suggest that the ability to identify deceptive visualizations must be explicitly taught as a core element of visualization literacy. Although both traditional and self-learning approaches are beneficial, the more active the intervention, the higher its educational effectiveness. [ABSTRACT FROM AUTHOR]

Rayground is a novel online framework for fast prototyping and interactive demonstration of ray tracing algorithms. It aims to set the ground for the online development of ray-traced visualization algorithms in an accessible manner for everyone, stripping off the mechanics that get in the way of creativity and the understanding of the core concepts. Due to the COVID-19 pandemic, remote teaching and online coursework have taken center stage. In this work, we demonstrate how Rayground can incorporate advanced instructive rendering media during online lectures as well as offer attractive student assignments in an engaging, hands-on manner. We cover things to consider when building or porting methods to this new development platform, best practices in remote teaching and learning activities, and time-tested assessment and grading strategies suitable for fully online university courses. [ABSTRACT FROM AUTHOR]

In an effort to develop visualization analysis and design skills in master's level information visualization students, the authors use a well-known analytical usability evaluation method, heuristic evaluation, with different sets of heuristics to teach students to analyze visualization applications. The proposed approach, used for three consecutive years, has successfully stimulated critical analysis and discussion sessions as well as helped raise students' awareness concerning the benefit of using systematic analysis methods and the strategies and guidelines that should be used to design visualization applications. [ABSTRACT FROM AUTHOR]

The past 10 years have seen profound changes in visualization algorithms, techniques, methodologies, and applications. These changes are forcing alterations to visualization courses. Unfortunately, outdated course content recommendations, together with profound changes in the underlying technology and methodology, are producing an unstable ground for educators at a time when visual representations are becoming increasingly important. To address this issue, educators held meetings or workshops at Siggraph 2011 and 2012 and a panel and workshop at Eurographics 2012. This article presents the insights gathered at these events. [ABSTRACT FROM AUTHOR]

Abstract: Color mapping is an important technique used in visualization to build visual representations of data and information. With output devices such as computer displays providing a large number of colors, developers sometimes tend to build their visualization to be visually appealing, while forgetting the main goal of clear depiction of the underlying data. Visualization researchers have profited from findings in adjoining areas such as human vision and psychophysics which, combined with their own experience, enabled them to establish guidelines that might help practitioners to select appropriate color scales and adjust the associated color maps, for particular applications. This survey presents an overview on the subject of color scales by focusing on important guidelines, experimental research work and tools proposed to help non-expert users. [Copyright &y& Elsevier]

Data charts are widely used in our daily lives, being present in regular media, such as newspapers, magazines, web pages, books, and many others. In general, a well-constructed data chart leads to an intuitive understanding of its underlying data. In the same way, when data charts have wrong design choices, a redesign of these representations might be needed. However, in most cases, these charts are shown as a static image, which means that the original data are not usually available. Therefore, automatic methods could be applied to extract the underlying data from the chart images to allow these changes. The task of recognizing charts and extracting data from them is complex, largely due to the variety of chart types and their visual characteristics. Other features in real-world images that can make this task difficult are photo distortions, noise, alignment, etc. Two computer vision techniques that can assist this task and have been little explored in this context are perspective detection and correction. These methods transform a distorted and noisy chart in a clear chart, with its type ready for data extraction or other uses. This paper proposes a classification, detection, and perspective correction process that is suitable for real-world usage, when considering the data used for training a state-of-the-art model for the extraction of a chart in real-world photography. The results showed that, with slight changes, chart recognition methods are now ready for real-world charts, when taking time and accuracy into consideration. [ABSTRACT FROM AUTHOR]

Augmented Reality (AR) is a key technology in the transition to Industry 4.0 and smart manufacturing, gaining reputation in a wide range of industrial fields One promising application is in another field of Industry 4.0, the data monitoring, where AR can be used to visualize and interact with complex and big data in real time, potentially improving the efficiency and accuracy of decision-making In this work, we propose a Pervasive AR tool for data monitoring, developed in collaboration with industry partners. An web application of the same data monitoring function is also created for comparison purposes A Human-Centered Design (HCD) methodology was used to identify the needs and requirements of industrial analysts, which led to the development of these systems Preliminary user studies, with 17 participants having distinct levels of expertise in industry, data analysis and computer science, were conducted to collect opinions and suggestions for improvements, as well as, quantitative data regarding the technologies considered A succeeding user study was then prepared, in which 12 participants used two conditions (C1 — Hands-free Pervasive AR tool for HMDs and C2 — Web tool for tablet devices) to fulfill a set of data monitoring tasks in an industry assembly line The result of these studies confirm the potential of Pervasive AR for data monitoring, as it engages users, promote environmental awareness, contextualizes data and allows fast self-localization. [Display omitted] • Two user studies with more than 10 participants each, industrial settings tasks. • Understand which method (Web or AR) stands out according to the task characteristic. • The findings reveal that certain methods were more effective for types of task. • Display methods significantly influenced participants across analysis. • These studies confirm the potential of Pervasive AR for data monitoring. [ABSTRACT FROM AUTHOR]

The authors argue in favor of introducing user studies into computer graphics, human-computer interaction, and information visualization courses. They discuss two sets of user studies they developed and performed over several years, with student collaboration, and the different aspects of the studies they had to consider. They also discuss a user study they designed for an information visualization course. [ABSTRACT FROM PUBLISHER]

Abstract: In the last two years, we have been using the Visualization Toolkit (VTK) as a tool for teaching “3D Modelling and Visualization”, an elective course offered to Computer Engineering students. Students start by using OpenGL and, afterwards, use VTK in half of their lab classes, in order to accomplish some tasks and acquire knowledge on its features and functionalities. They are also required to develop a visualization application based on VTK. We first present the motivation for using VTK and the main features of the “3D Modelling and Visualization” course. Afterwards, we describe some of the most successful projects developed by our students. Then, we globally analyse the effectiveness of using VTK, and present the results of a questionnaire handed out to the students who attended the course in the last semester. [Copyright &y& Elsevier]