A Nested Model for Visualization Design and Validation

By Tamara Munzner. IEEE Transactions on Visualization and Computer Graphics, 2009

985 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Information Systems, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/e8cfef98279aabd43f65d465b304345aec15d9bb

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

1. Shixia Liu
2. Weiwei Cui
3. Yingcai Wu
4. Hao Wei
5. Matthew Brehmer
6. Torsten Möller
7. Michael Sedlmair
8. Ronghua Liang

In Information Systems

1. Michael Sedlmair
2. Matthew Brehmer
3. Shixia Liu
4. Miriah D. Meyer
5. Hao Wei
6. Weiwei Cui
7. Petra Isenberg
8. David S. Ebert

In Sociology and Political Science

1. Shixia Liu
2. Michael Sedlmair
3. Matthew Brehmer
4. Yingcai Wu
5. Weiwei Cui
6. Miriah D. Meyer
7. Hao Wei
8. Tamara Munzner

Citations in the corpus

• A Systematic Review on the Practice of Evaluating Visualization (2013, methodology): “Munzner’s Nested Model [47] identifies four levels of visualization design—problem characterization, data and task abstraction, visual encoding/interaction design, and algorithm design—and provides guidance on valid evaluation methods for these different design levels.”
• A Multi-Level Typology of Abstract Visualization Tasks (2013, methodology): “We consider visual encoding and interaction techniques in a unified way because many methods incorporate aspects of both [41, 43], such as focus + context techniques [20, 46].”
• A Survey of Visual Analytics Techniques and Applications: State-of-the-Art Research and Future Challenges (2013, background): “Munzner et al.[27] divided the visual analysis design into four layers: domain problem characterization, data/operation abstraction design, encoding/interaction technique design, and algorithm design.”
• Design Study Methodology: Reflections from the Trenches and the Stacks (2012, methodology): “• validation: A crucial aspect of our definition is the validation of the problem analysis and the visualization design in the broad sense of Munzner’s nested model [50].”
• Manifold: A Model-Agnostic Framework for Interpretation and Diagnosis of Machine Learning Models (2018, methodology): “Then we characterize abstractions of the tasks that the framework should support using visual analysis vocabularies [28].”
• How Hierarchical Topics Evolve in Large Text Corpora (2014, methodology): “Following the nested model for visualization design and validation [28], we conducted a series of interviews and focus-group sessions with the four experts to generalize and develop an understanding on how they explore and analyze hierarchical topics in a large document collection.”