by Cristián Opazo
A 3-D visualization of a particle collision event at the LHC
- Living in the information age has fundamentally transformed the way we interact with the world around us. In particular, it has transformed the way we digest information from the many sources at our disposal. Understanding diverse, complex sets of data has become a familiar task for all of us to deal with even through the simple process of reading the paper every morning. In other words, information technologies are reshaping our literacy to necessarily include new digital literacies.
The term Scientific Visualization has been used for decades in relation to the use of computer technologies as a way of synthesizing the results of modeling and simulation in scientific and engineering practice. More recently, visualization is increasingly also concerned with data from other sources, including large and heterogeneous data collections found in business and finance, administration, the social sciences, humanities, and even the arts. A new research area called Information Visualization emerged in the early ’90s, to support analysis of heterogeneous data sets in diverse areas of knowledge. As a consequence, the term Data Visualization is gaining acceptance to include both the scientific and information visualization fields. Today, data visualization has become a very active area of research and teaching.
The origins of this field are in the early days of computer graphics in the ’50s, when the first digital images were generated by computers. With the rapid increase of processing power, larger and more complex numerical models were developed, resulting in the generation of huge numerical data sets. Also, large data sets were generated by data acquisition devices such as medical scanners, electronic microscopes and large-scale telescopes, and data was collected in large databases containing not only numerical and textual information, but also several varieties of new media. Advanced techniques in computer graphics were needed to process and visualize these new, massive data sets.
A 3-D sonogram image of a baby fetus
- Edward Tufte‘s now classic books on information visualization, The Visual Display of Quantitative Information (1983) and Envisioning Information (1991), encourage the use of visual paradigms with the goal of understanding complex relationships by synthesizing both statistics and aesthetic dimensions. A little earlier, Jacques Bertin, the French cartographer and geographer, introduced a suite of ideas parallel to Tufte’s in his book Semiologie Graphique (1967). The basis of Bertin’s work is the acknowledgment that graphic tools present a set of signs and a rule-based language that allow one to transcribe existing complex relations among qualitative and quantitative data. For Bertin and Tufte, the power of visual perception and graphic presentation has a double function, serving both as a tool for discovery and a way to augment cognition.
In future posts, I will describe in more detail the current landscape of data visualization across the fields of natural sciences, social sciences, humanities and the arts. Stay tuned.
