Précis: Why a Diagram is (Sometimes) …

Next week I will be posting the précis of one paper from the field of Visual Query Systems. I found that the work done by Tiziana Catarci, Maria F. Costabile, Stefano Levialdi and Carlo Batini is closely related to my research project. I will be able to compare: the notations used by the visual query systems they classified, with the notations used by the participants of my study.

Following is this week précis. This paper has been cited by many authors in the area of visual representations.

Jill H. Larkin, Herbert A. Simon: Why a Diagram is (Sometimes) Worth Ten Thousand Words. Cognitive Science, Vol. 11, No. 1, pages 65-100 (1987).

Diagrams are used to assist in the solution of problems in physics and engineering. The authors compare sentential and diagrammatic representations. Their main objective is to analyze the computational efficiency of informationally equivalent representations in terms of search, recognition and inference cost.

The authors define a sentential representation as a sequence of expressions; in contrast, the elements of a diagrammatic representation are located in a plane in which the concept of adjacency is richer. To illustrate their analysis, they use two examples, one from physics and the other from geometry. They modify the problem definitions starting with natural language versions, followed by the sentential representations and then the diagrammatic representations.

The main conclusions clearly point to the benefits of diagrammatic representations in the recognition and search processes, emphasizing their ability to reduce the use of identifying labels. No differences were found in the inference process. Unfortunately, detailed analyses were conducted mainly for problems with considerable spatial information; other kinds of problems were described only briefly.

A major contribution of this paper is the analysis framework. The use of data structures and inferential rules made possible a detailed analysis of efficiency similar to those applied to determine computational complexity of algorithms. However it was necessary to use a simplified model of the focus transitions between parts of the representations.

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