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We present a mixed methods user study evaluating augmented reality (AR) as a visualization technique for use in astronomy journal publications. This work is motivated by the highly spatial nature of scientific visualizations employed in astronomy, including spatial reasoning tasks for hypothesis generation and scientific communications. In this 52-person user study, we evaluate two AR approaches (one traditional tabletop projection and the other with a ‘tangible’ aid) as spatial 3D visualization techniques, as compared to a baseline 3D rendering on a phone. We identify a significant difference in mental and physical workload between the two AR conditions in men and women. Qualitatively, through thematic coding of interviews, we identify notable observed differences ranging from device-specific physical challenges, to subdomain-specific utility within astronomy. The confluence of quantitative and qualitative results suggest a tension between workload and engagement when comparing non-AR and AR technologies. We summarize these findings and contribute them for reference in data visualization research furthering novel scientific communications in astronomy journal publications. 

In this paper, we present the Vis Repligogy framework that enables conducting replication studies in the class. Replication studies are crucial to strengthening the data visualization field and ensuring its foundations are solid and methods accurate. Although visualization researchers acknowledge the epistemological significance of replications and their necessity to establish trust and reliability, the field has made little progress to support the publication of such studies and, importantly, provide methods to the community to encourage replications. Therefore, we contribute Vis Repligogy, a novel framework to systematically incorporate replications within visualization course curricula that not only teaches students replication and evaluation methodologies but also results in executed replication studies to validate prior work. To validate the feasibility of the framework, we present case studies of two graduate data visualization courses that implemented it. These courses resulted in a total of five replication studies. Finally, we reflect on our experience implementing the Vis Repligogy framework to provide useful recommendations for future use. We envision this framework will encourage instructors to conduct replications in their courses, help facilitate more replications in visualization pedagogy and in research, and support a culture shift towards reproducible research. Supplemental materials of this paper are available at https://osf.io/ncb6d/. 

We present a mixed methods user study evaluating augmented reality (AR) as a visualization technique for use in astronomy journal publications. This work is motivated by the highly spatial nature of scientific visualizations employed in astronomy, including spatial reasoning tasks for hypothesis generation and scientific communications. In this 52-person user study, we evaluate two AR approaches (one traditional tabletop projection and the other with a 'tangible' aid) as spatial 3D visualization techniques, as compared to a baseline 3D rendering on a phone. We identify a significant difference in mental and physical workload between the two AR conditions in men and women. Qualitatively, through thematic coding of interviews, we identify notable observed differences ranging from device-specific physical challenges, to subdomain-specific utility within astronomy. The confluence of quantitative and qualitative results suggest a tension between workload and engagement when comparing non-AR and AR technologies. We summarize these findings and contribute them for reference in data visualization research furthering novel scientific communications in astronomy journal publications. 

The effectiveness of a visualization technique is dependent on how well it supports the tasks or goals of an end-user. To measure the effectiveness of a visualization technique, researchers often use a comparative study design. In a comparative study, two or more visualization techniques are compared over a set of tasks and commonly measure human performance in terms of task accuracy and completion time. Despite the critical role of tasks in comparative studies, the current lack of guidance in existing literature on best practices for task selection and communication of research results in evaluation studies is problematic. In this work, we systematically identify and curate the task-based challenges of comparative studies by reviewing existing visualization literature on the topic. Furthermore, for each of the presented challenges we discuss the potential threats to validity for a comparative study. The challenges discussed in this paper are further backed by evidence identified in a detailed survey of comparative tree visualization studies. Finally, we recommend best practices from personal experience and the surveyed tree visualization studies to provide guidelines for other researchers to mitigate the challenges. The survey data and a free copy of the paper is available at https://osf.io/g3btk/ 

In the task abstraction phase of the visualization design process, including in "design studies", a practitioner maps the observed domain goals to generalizable abstract tasks using visualization theory in order to better understand and address the users needs. We argue that this manual task abstraction process is prone to errors due to designer biases and a lack of domain background and knowledge. Under these circumstances, a collaborator can help validate and provide sanity checks to visualization practitioners during this important task abstraction stage. However, having a human collaborator is not always feasible and may be subject to the same biases and pitfalls. In this paper, we first describe the challenges associated with task abstraction. We then propose a conceptual Digital Collaborator: an artificial intelligence system that aims to help visualization practitioners by augmenting their ability to validate and reason about the output of task abstraction. We also discuss several practical design challenges of designing and implementing such systems. 

Timelines are commonly represented on a horizontal line, which is not necessarily the most effective way to visualize temporal event sequences. However, few experiments have evaluated how timeline shape influences task performance. We present the design and results of a controlled experiment run on Amazon Mechanical Turk (n=192) in which we evaluate how timeline shape affects task completion time, correctness, and user preference. We tested 12 combinations of 4 shapes --- horizontal line, vertical line, circle, and spiral — and 3 data types — recurrent, non-recurrent, and mixed event sequences. We found good evidence that timeline shape meaningfully affects user task completion time but not correctness and that users have a strong shape preference. Building on our results, we present design guidelines for creating effective timeline visualizations based on user task and data types. A free copy of this paper, the evaluation stimuli and data, and code are available https://osf.io/qr5yu/