11 citations · 72 across the 21 of their papers we have counts for
24 papers
Task-Centered Benchmark for Interactive Network Visualization & Analysis
Ameya Patil, Wei Jun Tan, Ishan Sinha +1
Interactive network visualization and analysis (INVA) enables iterative, visual and algorithmic analysis of large network datasets. Although numerous benchmarks have been developed…
Optimizing Dataflow Systems for Scalable Interactive Visualization
Junran Yang, Hyekang Kevin Joo, Sai Yerramreddy +2
Supporting the interactive exploration of large datasets is a popular and challenging use case for data management systems. Traditionally, the interface and the back-end system are…
Too Many Cooks: Exploring How Graphical Perception Studies Influence Visualization Recommendations in Draco
Zehua Zeng, Junran Yang, Dominik Moritz +2
Findings from graphical perception can guide visualization recommendation algorithms in identifying effective visualization designs. However, existing algorithms use knowledge from…
WhaleVis: Visualizing the History of Commercial Whaling
Ameya Patil, Zoe Rand, Trevor Branch +1
Whales are an important part of the oceanic ecosystem. Although historic commercial whale hunting a.k.a. whaling has severely threatened whale populations, whale researchers are lo…
What Exactly is an Insight? A Literature Review
Leilani Battle, Alvitta Ottley
Insights are often considered the ideal outcome of visual analysis sessions. However, there is no single definition of what an insight is. Some scholars define insights as correlat…
Toward a Scalable Census of Dashboard Designs in the Wild: A Case Study with Tableau Public
Joanna Purich, Arjun Srinivasan, Michael Correll +3
Dashboards remain ubiquitous artifacts for presenting or reasoning with data across different domains. Yet, there has been little work that provides a quantifiable, systematic, and…
How Do Data Science Workers Communicate Intermediate Results?
Rock Yuren Pang, Ruotong Wang, Joely Nelson +1
Data science workers increasingly collaborate on large-scale projects before communicating insights to a broader audience in the form of visualization. While prior work has modeled…
Code Code Evolution: Understanding How People Change Data Science Notebooks Over Time
Deepthi Raghunandan, Aayushi Roy, Shenzhi Shi +2
Sensemaking is the iterative process of identifying, extracting, and explaining insights from data, where each iteration is referred to as the "sensemaking loop." Although recent w…
Streamlining Visualization Authoring in D3 Through User-Driven Templates
Hannah Bako, Alisha Varma, Anuoluwapo Faboro +4
D3 is arguably the most popular tool for implementing web based visualizations. Yet D3 has a steep learning curve that may hinder its adoption and continued use. To simplify the pr…
What Do We Mean When We Say "Insight"? A Formal Synthesis of Existing Theory
Leilani Battle, Alvitta Ottley
Researchers have derived many theoretical models for specifying users' insights as they interact with a visualization system. These representations are essential for understanding…
Lodestar: Supporting Independent Learning and Rapid Experimentation Through Data-Driven Analysis Recommendations
Deepthi Raghunandan, Zhe Cui, Kartik Krishnan +5
Keeping abreast of current trends, technologies, and best practices in visualization and data analysis is becoming increasingly difficult, especially for fledgling data scientists.…
An Adaptive Benchmark for Modeling User Exploration of Large Datasets
Joanna Purich, Anthony Wise, Leilani Battle
In this paper, we present a new DBMS performance benchmark that can simulate user exploration with any specified dashboard design made of standard visualization and interaction com…
Recommendations for Visualization Recommendations: Exploring Preferences and Priorities in Public Health
Calvin Bao, Siyao Li, Sarah Flores +2
The promise of visualization recommendation systems is that analysts will be automatically provided with relevant and high-quality visualizations that will reduce the work of manua…
Demonstration of VegaPlus: Optimizing Declarative Visualization Languages
Junran Yang, Hyekang Kevin Joo, Sai S. Yerramreddy +3
While many visualization specification languages are user-friendly, they tend to have one critical drawback: they are designed for small data on the client-side and, as a result, p…
A Grammar-Based Approach for Applying Visualization Taxonomies to Interaction Logs
Sneha Gathani, Shayan Monadjemi, Alvitta Ottley +1
Researchers collect large amounts of user interaction data with the goal of mapping user's workflows and behaviors to their higher-level motivations, intuitions, and goals. Althoug…
User-Driven Support for Visualization Prototyping in D3
Hannah K. Bako, Alisha Varma, Anuoluwapo Faboro +5
Templates have emerged as an effective approach to simplifying the visualization design and programming process. For example, they enable users to quickly generate multiple visuali…
An Evaluation-Focused Framework for Visualization Recommendation Algorithms
Zehua Zeng, Phoebe Moh, Fan Du +5
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 a…
A Review and Collation of Graphical Perception Knowledge for Visualization Recommendation
Zehua Zeng, Leilani Battle
Selecting appropriate visual encodings is critical to designing effective visualization recommendation systems, yet few findings from graphical perception are typically applied wit…
Exploring D3 Implementation Challenges on Stack Overflow
Leilani Battle, Danni Feng, Kelli Webber
Visualization languages help to standardize the process of designing effective visualizations, one of the most prominent being D3. However, few researchers have analyzed at scale h…
Guided Hyperparameter Tuning Through Visualization and Inference
Hyekang Joo, Calvin Bao, Ishan Sen +2
For deep learning practitioners, hyperparameter tuning for optimizing model performance can be a computationally expensive task. Though visualization can help practitioners relate…
Vis Ex Machina: An Analysis of Trust in Human versus Algorithmically Generated Visualization Recommendations
Rachael Zehrung, Astha Singhal, Michael Correll +1
More visualization systems are simplifying the data analysis process by automatically suggesting relevant visualizations. However, little work has been done to understand if users…
Kyrix-S: Authoring Scalable Scatterplot Visualizations of Big Data
Wenbo Tao, Xinli Hou, Adam Sah +3
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 allev…
Beagle: Automated Extraction and Interpretation of Visualizations from the Web
Leilani Battle, Peitong Duan, Zachery Miranda +3
"How common is interactive visualization on the web?" "What is the most popular visualization design?" "How prevalent are pie charts really?" These questions intimate the role of i…
Indexing Cost Sensitive Prediction
Leilani Battle, Edward Benson, Aditya Parameswaran +1
Predictive models are often used for real-time decision making. However, typical machine learning techniques ignore feature evaluation cost, and focus solely on the accuracy of the…