Semiology of Graphics: Information Visualization and Data Interpretation Frameworks
Overview
This paper examines Jacques Bertin's semiology of graphics framework and its application to information visualization. It discusses how visual signs and symbols are used to interpret data, explores the role of elementary perceptual tasks in graph comprehension, and analyzes graphical components including invariants, variables, and visual variableness in data representation.
What this essay covers
- Introduction to semiology of graphics and Bertin's 1967 theoretical framework
- Role of data visualization in information processing and decision-making
- Components of graphical interpretation: invariants, variables, and perceptual tasks
- Visual variables and implantations (point, line, area) in graph analysis
- Case study analysis of Italian postal savings deposits graph (1877-1881)
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Information Visualization
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Information Visualization
Introduction
Semiology of graphics refers to the study of signs and symbols, including their use or interpretation. In 1967, Jacques Bertin publish his book Semiology Graphique. The books present numerous theoretic principles that are applied in the starting point of understanding information visualization in research. Additionally, Bertin managed to create a thorough conceptual framework that guides, critiques, and analyzes the construction of information graphics. Visualization of data is a central factor in the way people digest and consume information. Over the last few decades, there have been an increase in the utilization of charts to explain important information. Moreover, the human mind is known to process information visually and effectively. Elementary perceptual tasks are things that individuals are required to complete whenever they are observing charts. These perceptual tasks assist the user to comprehend the data visualization being used in a particular graph. Notably, the level of perception differs between individuals, and is usually affected by the skill level or cognitive abilities of the person (Bertin, 1967).
In the process of interpreting visual information, data visualization plays an important role in science and daily work. This ensures that decision makers can observe of analytic that are presented visually. In this regard, they can understand the complex issues being presented and understand the patterns that define the trends or meaning of the visualization. Processing of information is easier using graphical representations and provides faster ways of understanding critical information.