Multivariate Data: Data that contain multiple attributes measured in some observations space are denoted multivariate data.
Visualization Pipeline: Describes data analysis, filtering, mapping, and rendering as steps of visualization.
Visualization: A visual approach to gaining insight into data.
Expressiveness: A visual representation is expressive if it communicates all information that is relevant with respect to the current analysis task.
Interaction: Denotes the use of specific techniques to adjust visual representations according to the task at hand.
Data Cube: The dimensions of a dataset can be modeled as a hyper-cube, which allows an easy selection of relevant parts of the data.
Appropriateness: A visual representation is appropriate if its benefit and creation effort are balanced.
Effectiveness: A visual representation is effective if it has been generated in accordance with the capabilities of the human visual system.