Information Visualization

Papers
(The TQCC of Information Visualization is 4. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-11-01 to 2024-11-01.)
ArticleCitations
Interactive visualization literacy: The state-of-the-art28
StoryFacets: A design study on storytelling with visualizations for collaborative data analysis13
Predicting intent behind selections in scatterplot visualizations10
The missing path: Analysing incompleteness in knowledge graphs9
Which emphasis technique to use? Perception of emphasis techniques with varying distractors, backgrounds, and visualization types8
Visualisation of law and legal Process: An opportunity missed7
Exploring, browsing and interacting with multi-level and multi-scale dynamics of knowledge7
HyperStorylines: Interactively untangling dynamic hypergraphs7
VNLP: Visible natural language processing6
Virtual-Reality graph visualization based on Fruchterman-Reingold using Unity and SteamVR6
TopoBERT: Exploring the topology of fine-tuned word representations6
Not just a pretty picture: Scientific fact visualisation styles, preferences, confidence and recall5
Out-of-sample data visualization using bi-kernel t-SNE5
Effects of screen-responsive visualization on data comprehension5
Is embodied interaction beneficial? A study on navigating network visualizations5
ATOVis – A visualisation tool for the detection of financial fraud5
Visualizing the invisible: User-centered design of a system for the visualization of flows and concentrations of particles in the air5
Sanguine: Visual analysis for patient blood management5
Visual cluster separation using high-dimensional sharpened dimensionality reduction5
MuzLink: Connected beeswarm timelines for visual analysis of musical adaptations and artist relationships4
Visualization Resources: A Survey4
Design guidelines for narrative maps in sensemaking tasks4
VisRuler: Visual analytics for extracting decision rules from bagged and boosted decision trees4
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