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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/. 

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/