Bayesian Modelling of Alluvial Diagram Complexity

Arunkumar, Anjana; Ginjpalli, Shashank; Bryan, Chris

doi:10.1109/vis49827.2021.9623282

Cited by 4 publications

(3 citation statements)

References 27 publications

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“…Study duration averaged roughly 15:55 (±2:38) minutes, resulting in an average hourly pay of $12.73 (±$2.11). SurveyMonkey 4 was used to display the study and store participant responses. We excluded 15 participants as their performance indicated they did not understand the task (i.e., more than 70% of ratings had the values of 0, -10 or +10) during/after training, or they took more than 20 minutes to complete the study (>2σ ).…”

Section: Set-up and Participantsmentioning

confidence: 99%

“…Prior work has extensively examined the design elements that make some visualizations intrinsically more memorable than others across charts in the wild [9,10,32]. Concurrently, there have been attempts to define and evaluate higher-level concepts like engagement [11,35,61,64] and effectiveness [4,17,83] across a plethora of (often synthetic and minimalist) chart types. However, the difference in the nature of charts studied through these different lenses poses challenges in reconciling good empirical results and rules of thumb with good exemplars of real-world visualizations.…”

Section: Introductionmentioning

confidence: 99%

“…https://www.prolific.co3 See supplemental material for further demographic details 4. https://www.surveymonkey.com…”

mentioning

confidence: 99%

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PMU Tracker: A Visualization Platform for Epicentric Event Propagation Analysis in the Power Grid

Arunkumar

Pinceti

Sankar

et al. 2022

IEEE Trans. Visual. Comput. Graphics

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The electrical power grid is a critical infrastructure, with disruptions in transmission having severe repercussions on daily activities, across multiple sectors. To identify, prevent, and mitigate such events, power grids are being refurbished as 'smart' systems that include the widespread deployment of GPS-enabled phasor measurement units (PMUs). PMUs provide fast, precise, and time-synchronized measurements of voltage and current, enabling real-time wide-area monitoring and control. However, the potential benefits of PMUs, for analyzing grid events like abnormal power oscillations and load fluctuations, are hindered by the fact that these sensors produce large, concurrent volumes of noisy data. In this paper, we describe working with power grid engineers to investigate how this problem can be addressed from a visual analytics perspective. As a result, we have developed PMU Tracker, an event localization tool that supports power grid operators in visually analyzing and identifying power grid events and tracking their propagation through the power grid's network. As a part of the PMU Tracker interface, we develop a novel visualization technique which we term an epicentric cluster dendrogram, which allows operators to analyze the effects of an event as it propagates outwards from a source location. We robustly validate PMU Tracker with: (1) a usage scenario demonstrating how PMU Tracker can be used to analyze anomalous grid events, and (2) case studies with power grid operators using a real-world interconnection dataset. Our results indicate that PMU Tracker effectively supports the analysis of power grid events; we also demonstrate and discuss how PMU Tracker's visual analytics approach can be generalized to other domains composed of time-varying networks with epicentric event characteristics.

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Section: Set-up and Participantsmentioning

confidence: 99%