Tuesday, September 6, 2011

Reaction: Graphical Perception: Theory, Experimentation and Application to the Development of Graphical Models

The authors in this paper attempt at establishing a foundation for using graphical methods for data analysis and data presentation. The approach suggested in this paper depends on graphical perception which means to decode the information from graphs visually.

The paper starts with identifying the perpetual tasks in extracting the information from the graphs. The authors have considered various features for doing so. The authors have cited various types of perpetual tasks and have also used graphs and charts to explain the application of identifying the information using the perpetual tasks. The authors have delved into explaining each type of charts and graphs and have also explained how the information can be perceived using various parameters like density, shades, amount, etc.

Discussing further in this paper, the authors have tried to order the various perpetual tasks. The ordering is based on accuracy of extraction. However during the discussion, the authors have appropriately indicated that accuracy of the graph is not the sole criteria of ordering. They state that the graph should represent all the quantitative information and should organise so as to visualise the information and its structure. The authors perform and discuss about their experiments to check their hypothesis. And the results discussed prove the theory by illustrating that judgements of position can be more accurate than judgments of lengths and angle. There is also a discussion on position – length judgements which requires few revisions as stated in the paper. The discussion is further extended to analyse and redesign many of the graph forms.

Thus in this paper the authors have used elementary perceptual tasks. They have stated about the limitations of performing experiments for graphical perception as the differences seen in the recorded judgments by the people. But the theory proposed in this paper to identify the perceptual tasks to understand the information from the graphical visualisation seems to be practical and could be studied upon for further developments.