From visual complexity to categorical database

Abstract

Taking as a starting point the taxonomy of algorithmic visualizations of big data, attempted by Manuel Lima in his web site and book “Visual Complexity”, I consider the readability of human meaning from big data through Pregnant’s Law of Gestalt Psychology (a property of human experience) and Lakoff & Johnson’s “image schema” (a conceptualization of bodily experience). Next, the author introduces “categorical database” based on category theory, which has been attracting attention from various fields in recent years, and propose the possibility that the basic structure of category, i.e., diagram of directed graphs, can become a common language connecting visual complexity (visualization), dynamism of image schema (meaning), and the structure of the universe (physics).