Data-First Visualization Design Studies

Oppermann, Michael; Munzner, Tamara

doi:10.1109/beliv51497.2020.00016

Cited by 20 publications

(14 citation statements)

References 40 publications

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“…The visual elements are, in turn, representations of data that have been collected, stored, fetched, filtered, transported and transformed to and from some data storage. Figure 1 illustrates an overview of Tim's visualizations based on simplification of previous work [28,31,43,53,56]: (i) Data are collected from the test systems in the test environment: verdicts, log files, etc. (ii) The configuration of how test resources are partitioned is a valuable reference for the user.…”

Section: Visualizationmentioning

confidence: 99%

Software test results exploration and visualization with continuous integration and nightly testing

Strandberg

Afzal

Sundmark

2022

Int J Softw Tools Technol Transfer

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Software testing is key for quality assurance of embedded systems. However, with increased development pace, the amount of test results data risks growing to a level where exploration and visualization of the results are unmanageable. This paper covers a tool, Tim, implemented at a company developing embedded systems, where software development occurs in parallel branches and nightly testing is partitioned over software branches, test systems and test cases. Tim aims to replace a previous solution with problems of scalability, requirements and technological flora. Tim was implemented with a reference group over several months. For validation, data were collected both from reference group meetings and logs from the usage of the tool. Data were analyzed quantitatively and qualitatively. The main contributions from the study include the implementation of eight views for test results exploration and visualization, the identification of four solutions patterns for these views (filtering, aggregation, previews and comparisons), as well as six challenges frequently discussed at reference group meetings (expectations, anomalies, navigation, integrations, hardware details and plots). Results are put in perspective with related work and future work is proposed, e.g., enhanced anomaly detection and integrations with more systems such as risk management, source code and requirements repositories.

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Section: Visualizationmentioning

confidence: 99%

Software test results exploration and visualization with continuous integration and nightly testing

Strandberg

Afzal

Sundmark

2022

Int J Softw Tools Technol Transfer

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“…1, we did not begin our work with a scientific question in mind but with the interest in the data itself, to plan visits to carnivorous plant habitat locations during future travel. Our work thus started with a data collection [56]. Originally unaware that specialized citizen science projects (like iNaturalist, see Sec.…”

Section: Initial Data Acquisition and Analysismentioning

confidence: 99%

Do You Believe Your (Social Media) Data? A Personal Story on Location Data Biases, Errors, and Plausibility as Well as Their Visualization

Isenberg

Salazar²,

Blanco³

et al. 2022

IEEE Trans. Visual. Comput. Graphics

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We present a case study on a journey about a personal data collection of carnivorous plant species habitats, and the resulting scientific exploration of location data biases, data errors, location hiding, and data plausibility. While initially driven by personal interest, our work led to the analysis and development of various means for visualizing threats to insight from geo-tagged social media data. In the course of this endeavor we analyzed local and global geographic distributions and their inaccuracies. We also contribute Motion Plausibility Profiles-a new means for visualizing how believable a specific contributor's location data is or if it was likely manipulated. We then compared our own repurposed social media dataset with data from a dedicated citizen science project. Compared to biases and errors in the literature on traditional citizen science data, with our visualizations we could also identify some new types or show new aspects for known ones. Moreover, we demonstrate several types of errors and biases for repurposed social media data.

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“…On this basis, we analyzed who would profit from this data, which types of tasks exist, and whether visualization methods needed to be adapted to better facilitate these use cases. We took this data-first perspective [OM20] to better understand the challenges and opportunities the data poses before applying it to a problem. Further, we intend to provide an initial frame to the domain of visualizing flow in the carotids and outline possible directions.…”

Section: Domain Characterizationmentioning

confidence: 99%

“…As this work is motivated by our conjecture that visualizing blood flow in the carotids could support real-world analysis tasks, we follow the recently proposed outline to a data-first design study [OM20]: We contribute a stakeholder analysis, concluding that medical practitioners could benefit from simulated flow in the human carotids. We then analyze and abstract the data and tasks involved in studying blood flow properties w.r.t.…”

Section: Introductionmentioning

confidence: 99%

Visualizing Carotid Blood Flow Simulations for Stroke Prevention

Eulzer

Meuschke

Klingner

et al. 2021

Computer Graphics Forum

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In this work, we investigate how concepts from medical flow visualization can be applied to enhance stroke prevention diagnostics. Our focus lies on carotid stenoses, i.e., local narrowings of the major brain‐supplying arteries, which are a frequent cause of stroke. Carotid surgery can reduce the stroke risk associated with stenoses, however, the procedure entails risks itself. Therefore, a thorough assessment of each case is necessary. In routine diagnostics, the morphology and hemodynamics of an afflicted vessel are separately analyzed using angiography and sonography, respectively. Blood flow simulations based on computational fluid dynamics could enable the visual integration of hemodynamic and morphological information and provide a higher resolution on relevant parameters. We identify and abstract the tasks involved in the assessment of stenoses and investigate how clinicians could derive relevant insights from carotid blood flow simulations. We adapt and refine a combination of techniques to facilitate this purpose, integrating spatiotemporal navigation, dimensional reduction, and contextual embedding. We evaluated and discussed our approach with an interdisciplinary group of medical practitioners, fluid simulation and flow visualization researchers. Our initial findings indicate that visualization techniques could promote usage of carotid blood flow simulations in practice.

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Data-First Visualization Design Studies

Cited by 20 publications

References 40 publications

Software test results exploration and visualization with continuous integration and nightly testing

Software test results exploration and visualization with continuous integration and nightly testing

Do You Believe Your (Social Media) Data? A Personal Story on Location Data Biases, Errors, and Plausibility as Well as Their Visualization

Visualizing Carotid Blood Flow Simulations for Stroke Prevention

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