The Cognitive Science of Visual-Spatial Displays: Implications for Design

By Mary Hegarty. Topics in Cognitive Science, 2011

390 citations recorded by the source corpus.

Subfields: Automotive Engineering, Computer Vision and Pattern Recognition, Social Psychology

View Paper: https://www.semanticscholar.org/paper/d83cad67cba4b554c0cee119c185e5b311305b80

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Automotive Engineering

1. Nizar Abdelkafi
2. Karl Täuscher
3. Lace M. K. Padilla
4. Priti Shah
5. Mary Hegarty
6. Steven L. Franconeri
7. Jeffrey M. Zacks
8. Jessica R. Hullman

In Computer Vision and Pattern Recognition

1. Nizar Abdelkafi
2. Karl Täuscher
3. Lace M. K. Padilla
4. Steven L. Franconeri
5. Jeffrey M. Zacks
6. Priti Shah
7. Jessica R. Hullman
8. Linda M. See

In Social Psychology

1. Nizar Abdelkafi
2. Karl Täuscher
3. Lace M. K. Padilla
4. Priti Shah
5. Steven L. Franconeri
6. Jeffrey M. Zacks
7. Jessica R. Hullman
8. Giles M. Foody

Citations in the corpus

• Decision making with visualizations: a cognitive framework across disciplines (2018, background): “Researchers have generalized this model to propose theories of comprehension, learning, and memory with visual information (Hegarty, 2011; Kriz & Hegarty, 2007; Shah & Freedman, 2011).”
• The Science of Visual Data Communication: What Works (2021, methodology): “We also restrict our scope to quantitative visualizations, omitting discussion of qualitative visualizations of text data, diagrams, and processes (see Hegarty, 2011; Henderson & Segal, 2013, for review).”
• Visual tools for business model innovation: Recommendations from a cognitive perspective (2017, positive): “It builds on insights from cognitive science into how visualizations influence cognitive processes (Larkin and Simon, 1987; Tversky, 2011), and how these insights can lead to design principles for visualization (Hegarty, 2011).”
• Crowdsourcing, Citizen Science or Volunteered Geographic Information? The Current State of Crowdsourced Geographic Information (2016, background): “rces (such as the visual working memory that is critical in processing visual information; or spatial abilities which are critical for how well we can make sense of visualizations) are limited (e.g., Hegarty 2011, Hegarty et al. 2012). Novel visualization designs are necessary, especially those that”
• Geospatial Big Data Handling Theory and Methods: A Review and Research Challenges (2015, background): “It is important to note that human cognitive resources (such as the visual working memory that is critical in processing visual information; or spatial abilities which are critical for how well we can make sense of visualizations) are limited (e.g., Hegarty 2011, Hegarty et al. 2012).”