The visual display of quantitative information
The visual display of quantitative information
Task-analytic design of graphic presentations
Task-analytic design of graphic presentations
A cognitive model for understanding graphical perception
Human-Computer Interaction
A Task Centered Framework for Computer Security Data Visualization
VizSec '08 Proceedings of the 5th international workshop on Visualization for Computer Security
Measuring effective data visualization
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
Decision tree induction for identifying trends in line graphs
ISMIS'08 Proceedings of the 17th international conference on Foundations of intelligent systems
Diagrams'10 Proceedings of the 6th international conference on Diagrammatic representation and inference
Toward a comprehensive model of graph comprehension: making the case for spatial cognition
Diagrams'06 Proceedings of the 4th international conference on Diagrammatic Representation and Inference
Twelve years of diagrams research
Journal of Visual Languages and Computing
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Research on graph comprehension has been concerned with relatively low-level information extraction. However, laboratory studies often produce conflicting findings because real-world graph interpretation requires going beyond the data presentation to make inferences and solve problems. Furthermore, in real-world settings, graphical information is presented in the context of relevant prior knowledge. According to our model, knowledge-based graph comprehension involves an interaction of top-down and bottom up processes. Several types of knowledge are brought to bear on graphs: domain knowledge, graphical skills, and explanatory skills. During the initial processing, people chunk the visual features in the graphs. Nevertheless, prior knowledge guides the processing of visual features. We outline the key assumptions of this model and show how this model explains the extant data and generates testable predictions.