Evaluating Information Visualizations
By Sheelagh Carpendale. Information Visualization, 2008
403 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Sociology and Political Science
View Paper: https://www.semanticscholar.org/paper/28d63b0a44ad4fa462795137c67175decd9bf160
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Tamara Munzner
- Michael Sedlmair
- Miriah D. Meyer
- Niloofar Zarei
- Petra Isenberg
- Eric D. Ragan
- Sina Mohseni
- Sheelagh Carpendale
In Sociology and Political Science
- Tamara Munzner
- Michael Sedlmair
- Miriah D. Meyer
- Petra Isenberg
- Sheelagh Carpendale
- Catherine Plaisant
- Enrico Bertini
- Heidi Lam
Citations in the corpus
- A Multidisciplinary Survey and Framework for Design and Evaluation of Explainable AI Systems (2018, background): “ch often makes it difficult to evaluate with controlled studies. Case studies, expert reviews, and focus groups are often used for evaluation of visual analytics and decision-support tools for experts [95,18]. Case studies aim to collect experts users feedback while performing high-level cognitive ta”
- Design Study Methodology: Reflections from the Trenches and the Stacks (2012, methodology): “The visualization literature contains a multitude of proposed methods for evaluating visualization tools in the wild [13, 33, 69, 85, 95], as well as guidance on using them [39, 50].”
- Empirical Studies in Information Visualization: Seven Scenarios (2012, positive): “Researchers and practitioners in the field have long identified many of the challenges faced when planning, conducting, and executing an evaluation of a visualization tool or system [10], [41], [54], [63].”