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Visualization, Analytics, and Data Understanding / Text, Document, and Notebook Visualization

Interdisciplinary data science teams face high communication costs; non-technical members struggle to understand complex code.

lightbulbPractical problemText, Document, and Notebook Visualization

Interdisciplinary data science teams face high communication costs; non-technical members struggle to understand complex code.

CSCW '23NBGuru: Generating Explorable Data Science Flowcharts to Facilitate Asynchronous Communication in Interdisciplinary Data Science Teams

Similar questions

lightbulbPractical problemText, Document, and Notebook Visualization

Users struggle to effectively parse complex-format semi-structured text, hindering downstream analysis.

CHI '25StructVizor: Interactive Profiling of Semi-Structured Textual Data

lightbulbPractical problemText, Document, and Notebook Visualization

Users struggle to quickly understand and navigate complex long-text content generated by large language models.

UIST '23Graphologue: Exploring Large Language Model Responses with Interactive Diagrams

lightbulbPractical problemText, Document, and Notebook Visualization

Qualitative researchers struggle to efficiently analyze large-scale text data while remaining skeptical of algorithm-introduced bias.

UIST '22Scholastic: Graphical Human-AI Collaboration for Inductive and Interpretive Text Analysis

lightbulbPractical problemText, Document, and Notebook Visualization

Data scientists spend considerable time creating presentation slides for complex results.

CHI '22Telling Stories from Computational Notebooks: AI-Assisted Presentation Slides Creation for Presenting Data Science Work

lightbulbPractical problemText, Document, and Notebook Visualization

Linguists' multi-tool data processing workflows are inefficient and lack intuitive visualization analysis tools.

CHI '21CorpSum: Towards an Enabling Tool-Design for Language Researchers to Explore, Analyze and Visualize Corpora

lightbulbPractical problemText, Document, and Notebook Visualization

Researchers struggle to analyze domain documents and compare their similarities and differences at a conceptual level.

CHI '21ConceptScope: Organizing and Visualizing Knowledge in Documents based on Domain Ontology

Related papers

StructVizor: Interactive Profiling of Semi-Structured Textual Data

Yanwei Huang, Yan Miao, Di Weng

Graphologue: Exploring Large Language Model Responses with Interactive Diagrams

Peiling Jiang, Jude Rayan, Steven P Dow

Scholastic: Graphical Human-AI Collaboration for Inductive and Interpretive Text Analysis

Matt-Heun Hong, Lauren A. Marsh, Jessica L Feuston

Telling Stories from Computational Notebooks: AI-Assisted Presentation Slides Creation for Presenting Data Science Work

Chengbo Zheng, Dakuo Wang, April Yi Wang

CorpSum: Towards an Enabling Tool-Design for Language Researchers to Explore, Analyze and Visualize Corpora

Asil Çetin, Thomas Torsney-Weir, Torsten Moeller

ConceptScope: Organizing and Visualizing Knowledge in Documents based on Domain Ontology

Xiaoyu Zhang, Senthil Chandrasegaran, Kwan-Liu Ma

Fork It: Supporting Stateful Alternatives in Computational Notebooks

Nathaniel Weinman, Steven M. Drucker, Titus Barik

NBSearch: Semantic Search and Visual Exploration of Computational Notebooks

Xingjun Li, Yuanxin Wang, Hong Wang