From Dashboard Zoo to Census: A Case Study With Tableau Public.

Dashboards remain ubiquitous tools for analyzing data and disseminating the findings. Understanding the range of dashboard designs, from simple to complex, can support development of authoring tools that enable end-users to meet their analysis and communication goals. Yet, there has been little work that provides a quantifiable, systematic, and descriptive overview of dashboard design patterns.

DracoGPT: Extracting Visualization Design Preferences from Large Language Models.

Trained on vast corpora, Large Language Models (LLMs) have the potential to encode visualization design knowledge and best practices. However, if they fail to do so, they might provide unreliable visualization recommendations. What visualization design preferences, then, have LLMs learned? We contribute DracoGPT, a method for extracting, modeling, and assessing visualization design preferences from LLMs.

Unveiling How Examples Shape Visualization Design Outcomes.

Visualization designers (e.g., journalists or data analysts) often rely on examples to explore the space of possible designs, yet we have little insight into how examples shape data visualization design outcomes.

What Do We Mean When We Say "Insight"? A Formal Synthesis of Existing Theory.

Researchers have derived many theoretical models for specifying users' insights as they interact with a visualization system. These representations are essential for understanding the insight discovery process, such as when inferring user interaction patterns that lead to insight or assessing the rigor of reported insights. However, theoretical models can be difficult to apply to existing tools and user studies, often due to discrepancies in how insight and its constituent parts are defined.

Too Many Cooks: Exploring How Graphical Perception Studies Influence Visualization Recommendations in Draco.

Findings from graphical perception can guide visualization recommendation algorithms in identifying effective visualization designs. However, existing algorithms use knowledge from, at best, a few studies, limiting our understanding of how complementary (or contradictory) graphical perception results influence generated recommendations. In this paper, we present a pipeline of applying a large body of graphical perception results to develop new visualization recommendation algorithms and conduct an exploratory study to investigate how results from graphical perception can alter the behavior of downstream algorithms.

Is Envy Always Bad? An Examination of Benign and Malicious Envy in the Workplace.

The current study investigated workplace envy by exploring if perceived self-efficacy of negative and positive emotions could predict malicious or benign envy. This study also examined how malicious and benign envy relate to two important organizational outcomes: job engagement and turnover intentions. Malicious envy is typically associated with negative emotions toward the target of comparison as well as negative behavioral outcomes, whereas benign envy is typically associated with positive emotions toward the target of comparison as well as positive behavioral outcomes.

Understanding how Designers Find and Use Data Visualization Examples.

Examples are useful for inspiring ideas and facilitating implementation in visualization design. However, there is little understanding of how visualization designers use examples, and how computational tools may support such activities. In this paper, we contribute an exploratory study of current practices in incorporating visualization examples.

An Evaluation-Focused Framework for Visualization Recommendation Algorithms.

Although we have seen a proliferation of algorithms for recommending visualizations, these algorithms are rarely compared with one another, making it difficult to ascertain which algorithm is best for a given visual analysis scenario. Though several formal frameworks have been proposed in response, we believe this issue persists because visualization recommendation algorithms are inadequately specified from an evaluation perspective. In this paper, we propose an evaluation-focused framework to contextualize and compare a broad range of visualization recommendation algorithms.

A systematic review and meta-analysis on the efficacy of stem cell therapy on bone brittleness in mouse models of osteogenesis imperfecta.

There is no cure for osteogenesis imperfecta (OI), and current treatments can only partially correct the bone phenotype. Stem cell therapy holds potential to improve bone quality and quantity in OI. Here, we conduct a systematic review and meta-analysis of published studies to investigate the efficacy of stem cell therapy to rescue bone brittleness in mouse models of OI.

The impact of heart failure on patients and caregivers: A qualitative study.

Background: Heart failure is rising in prevalence but relatively little is known about the experiences and journey of patients and their caregivers. The goal of this paper is to present the symptom and symptom impact experiences of patients with heart failure and their caregivers.

Methods: This was a United States-based study wherein in-person focus groups were conducted.

Kyrix-S: Authoring Scalable Scatterplot Visualizations of Big Data.

Static scatterplots often suffer from the overdraw problem on big datasets where object overlap causes undesirable visual clutter. The use of zooming in scatterplots can help alleviate this problem. With multiple zoom levels, more screen real estate is available, allowing objects to be placed in a less crowded way.

A Structured Review of Data Management Technology for Interactive Visualization and Analysis.

In the last two decades, interactive visualization and analysis have become a central tool in data-driven decision making. Concurrently to the contributions in data visualization, research in data management has produced technology that directly benefits interactive analysis. Here, we contribute a systematic review of 30 years of work in this adjacent field, and highlight techniques and principles we believe to be underappreciated in visualization work.

Pyoderma gangrenosum developing after chest tube placement in a patient with chronic lymphocytic leukemia.

Diagnosis of a neutrophilic dermatosis, such as pyoderma gangrenosum (PG), often is challenging at onset because it can be impossible to distinguish clinically and histopathologically from an acute infection in an immunosuppressed patient, necessitating a detailed patient history as well as correlation pathology with microbial tissue cultures. The dermatologist's ability to distinguish a neutrophilic dermatosis from active infection is of paramount importance, as the decision to treat with surgical debridement, in addition to an antibiotic regimen, can have grave consequences in the misdiagnosed patient. We present a case of PG occurring at a chest tube site in a patient with chronic lymphocytic leukemia (CLL) and highlight the challenges and therapeutic importance of arriving at the correct diagnosis.

A Provenance Task Abstraction Framework.

Visual analytics tools integrate provenance recording to externalize analytic processes or user insights. Provenance can be captured on varying levels of detail, and in turn activities can be characterized from different granularities. However, current approaches do not support inferring activities that can only be characterized across multiple levels of provenance.

The Role of Latency and Task Complexity in Predicting Visual Search Behavior.

Latency in a visualization system is widely believed to affect user behavior in measurable ways, such as requiring the user to wait for the visualization system to respond, leading to interruption of the analytic flow. While this effect is frequently observed and widely accepted, precisely how latency affects different analysis scenarios is less well understood. In this paper, we examine the role of latency in the context of visual search, an essential task in data foraging and exploration using visualization.

Dermatologic Urgencies and Emergencies: What Every Pathologist Should Know.

Context.—: Fatal dermatologic diseases and ones with high morbidity can occur in the inpatient setting. In such cases, prompt and accurate assessment of a bedside skin biopsy is required.

Small peptide substrates and high resolution peptide gels for the analysis of site-specific protein phosphorylation and dephosphorylation.

Protein phosphorylation and dephosphorylation reactions play key regulatory roles in many fundamental cellular processes. Due to the large number of kinases and phosphatases in the genome, the identification of the specific enzymes responsible for a given site in a given protein is immensely challenging. However, because protein kinases and phosphatases recognize local specificity determinants within proteins, it is possible to use small peptides to study the characteristics of site-specific phosphorylation.

Granulomatous pigmented purpuric dermatosis.

The granulomatous variant of the pigmented purpuric dermatoses (PPDs) is a rare and infrequently described condition, with a total of 16 cases published to date. We report a case of granulomatous PPD in a 59-year-old white woman who demonstrated involvement of the arms, legs, chest and back with concurrent hyperlipidaemia. Histopathological examination revealed a lymphohistiocytic infiltrate obscuring the dermoepidermal junction, and loose granuloma formation in the superficial dermis, with extravasated erythrocytes.