38 citations · 94 across the 12 of their papers we have counts for
12 papers
LinkQ: An LLM-Assisted Visual Interface for Knowledge Graph Question-Answering
Harry Li, Gabriel Appleby, Ashley Suh
We present LinkQ, a system that leverages a large language model (LLM) to facilitate knowledge graph (KG) query construction through natural language question-answering. Traditiona…
A Preliminary Roadmap for LLMs as Assistants in Exploring, Analyzing, and Visualizing Knowledge Graphs
Harry Li, Gabriel Appleby, Ashley Suh
We present a mixed-methods study to explore how large language models (LLMs) can assist users in the visual exploration and analysis of knowledge graphs (KGs). We surveyed and inte…
Preliminary Guidelines For Combining Data Integration and Visual Data Analysis
Adam Coscia, Ashley Suh, Remco Chang +1
Data integration is often performed to consolidate information from multiple disparate data sources during visual data analysis. However, integration operations are usually separat…
Visual Validation versus Visual Estimation: A Study on the Average Value in Scatterplots
Daniel Braun, Ashley Suh, Remco Chang +2
We investigate the ability of individuals to visually validate statistical models in terms of their fit to the data. While visual model estimation has been studied extensively, vis…
Knowledge Graphs in Practice: Characterizing their Users, Challenges, and Visualization Opportunities
Harry Li, Gabriel Appleby, Camelia Daniela Brumar +2
This study presents insights from interviews with nineteen Knowledge Graph (KG) practitioners who work in both enterprise and academic settings on a wide variety of use cases. Thro…
Analysis Without Data: Teaching Students to Tackle the VAST Challenge
Edward W He, Daniel Tolessa, Ashley Suh +1
The VAST Challenges have been shown to be an effective tool in visual analytics education, encouraging student learning while enforcing good visualization design and development pr…
Inferential Tasks as an Evaluation Technique for Visualization
Ashley Suh, Ab Mosca, Shannon Robinson +4
Designing suitable tasks for visualization evaluation remains challenging. Traditional evaluation techniques commonly rely on 'low-level' or 'open-ended' tasks to assess the effica…
Are Metrics Enough? Guidelines for Communicating and Visualizing Predictive Models to Subject Matter Experts
Ashley Suh, Gabriel Appleby, Erik W. Anderson +3
Presenting a predictive model's performance is a communication bottleneck that threatens collaborations between data scientists and subject matter experts. Accuracy and error metri…
A Grammar of Hypotheses for Visualization, Data, and Analysis
Ashley Suh, Ab Mosca, Eugene Wu +1
We present a grammar for expressing hypotheses in visual data analysis to formalize the previously abstract notion of "analysis tasks." Through the lens of our grammar, we lay the…
UnProjection: Leveraging Inverse-Projections for Visual Analytics of High-Dimensional Data
Mateus Espadoto, Gabriel Appleby, Ashley Suh +6
Projection techniques are often used to visualize high-dimensional data, allowing users to better understand the overall structure of multi-dimensional spaces on a 2D screen. Altho…
TopoLines: Topological Smoothing for Line Charts
Paul Rosen, Ashley Suh, Christopher Salgado +1
Line charts are commonly used to visualize a series of data values. When the data are noisy, smoothing is applied to make the signal more apparent. Conventional methods used to smo…
Persistent Homology Guided Force-Directed Graph Layouts
Ashley Suh, Mustafa Hajij, Bei Wang +2
Graphs are commonly used to encode relationships among entities, yet their abstractness makes them difficult to analyze. Node-link diagrams are popular for drawing graphs, and forc…