Building knowledge through images in physics

摘要

This article considers the role of images in physics. Utilizing the Systemic Functional Linguistic dimension of field it shows that diagrams that present large classification and composition taxonomies as well as long sequences of activities can be overlaid upon graphs that show arrays of ordered data. Through an analysis using the concepts of semantic density and semantic gravity from Legitimation Code Theory, it is argued that this allows images to present large degrees of meaning in a single snapshot whilst also linking abstracted theory to specific instances of data. That is, the analysis shows that images play a significant role in developing technical physics knowledge through abstractions away from the empirical world. This article contributes to the growing body of research focusing on the structuring of knowledge and the non-linguistic semiotic resources used to organize it.