Heuristics for Supporting Cooperative Dashboard Design

Setlur, Vidya; Correll, Michael; Satyanarayan, Arvind; Tory, Melanie

doi:10.1109/tvcg.2023.3327158

Cited by 6 publications

(1 citation statement)

References 87 publications

(112 reference statements)

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“…Dashboards have proven invaluable in public health settings [28,29] owing to their ability to visually summarize key metrics and statistics [30,31], thereby aiding surveillance and fostering evidence-based responses to emerging health threats [32,33]. Furthermore, dashboards are conducive to collaborative sense making among multiple individuals [34][35][36]. This feature makes them particularly suited to fatality review meetings, which are designed to be collaborative and deliberative in nature.…”

Section: Introductionmentioning

confidence: 99%

Development of a Real-Time Dashboard for Overdose Touchpoints: User-Centered Design Approach

Salvi,

Gillenwater,

Cockrum

et al. 2024

JMIR Hum Factors

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Background Overdose Fatality Review (OFR) is an important public health tool for shaping overdose prevention strategies in communities. However, OFR teams review only a few cases at a time, which typically represent a small fraction of the total fatalities in their jurisdiction. Such limited review could result in a partial understanding of local overdose patterns, leading to policy recommendations that do not fully address the broader community needs. Objective This study explored the potential to enhance conventional OFRs with a data dashboard, incorporating visualizations of touchpoints—events that precede overdoses—to highlight prevention opportunities. Methods We conducted 2 focus groups and a survey of OFR experts to characterize their information needs and design a real-time dashboard that tracks and measures decedents’ past interactions with services in Indiana. Experts (N=27) were engaged, yielding insights on essential data features to incorporate and providing feedback to guide the development of visualizations. Results The findings highlighted the importance of showing decedents’ interactions with health services (emergency medical services) and the justice system (incarcerations). Emphasis was also placed on maintaining decedent anonymity, particularly in small communities, and the need for training OFR members in data interpretation. The developed dashboard summarizes key touchpoint metrics, including prevalence, interaction frequency, and time intervals between touchpoints and overdoses, with data viewable at the county and state levels. In an initial evaluation, the dashboard was well received for its comprehensive data coverage and its potential for enhancing OFR recommendations and case selection. Conclusions The Indiana touchpoints dashboard is the first to display real-time visualizations that link administrative and overdose mortality data across the state. This resource equips local health officials and OFRs with timely, quantitative, and spatiotemporal insights into overdose risk factors in their communities, facilitating data-driven interventions and policy changes. However, fully integrating the dashboard into OFR practices will likely require training teams in data interpretation and decision-making.

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Section: Introductionmentioning

confidence: 99%

Development of a Real-Time Dashboard for Overdose Touchpoints: User-Centered Design Approach

Salvi,

Gillenwater,

Cockrum

et al. 2024

JMIR Hum Factors

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Charting EDA: Characterizing Interactive Visualization Use in Computational Notebooks with a Mixed-Methods Formalism

Wootton,

Fox,

Peck

et al. 2025

IEEE Trans. Visual. Comput. Graphics

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Interactive visualizations are powerful tools for Exploratory Data Analysis (EDA), but how do they affect the observations analysts make about their data? We conducted a qualitative experiment with 13 professional data scientists analyzing two datasets with Jupyter notebooks, collecting a rich dataset of interaction traces and think-aloud utterances. By qualitatively coding participant utterances, we introduce a formalism that describes EDA as a sequence of analysis states, where each state is comprised of either a representation an analyst constructed (e.g., the output of a data frame, an interactive visualization, etc.) or an observation the analyst made with a representation (e.g., about missing data, the relationship between variables, etc.). By applying our formalism to our dataset, we are able to identify that interactive visualizations, on average, lead to earlier and more complex insights about relationships between dataset attributes compared to static visualizations. Moreover, by calculating metrics such as revisiting count and representational diversity, we are able to uncover that some representations serve more as as "planning aids" during EDA rather than tools strictly for hypothesis-answering. We show how these measures helped identify other patterns of analysis behavior, such as the "80-20 rule", where a small subset of representations drove the majority of observations. Based on these findings, we offer design guidelines for interactive exploratory analysis tooling and reflect on future directions for studying the role that visualizations play in EDA.

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“I Came Across a Junk”: Understanding Design Flaws of Data Visualization from the Public's Perspective

Lan,

Liu

2025

IEEE Trans. Visual. Comput. Graphics

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Heuristics for Supporting Cooperative Dashboard Design

Cited by 6 publications

References 87 publications

Development of a Real-Time Dashboard for Overdose Touchpoints: User-Centered Design Approach

Development of a Real-Time Dashboard for Overdose Touchpoints: User-Centered Design Approach

Charting EDA: Characterizing Interactive Visualization Use in Computational Notebooks with a Mixed-Methods Formalism

“I Came Across a Junk”: Understanding Design Flaws of Data Visualization from the Public's Perspective

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