In this blog post, Paul Parsons, Research Scientist - IBM Canada R&D Centre, discusses the importance of not only visualizing the large "bodies of information" we're interested in analyzing, especially given our access to big data, but also being able to interact with this visualized data to extract the full value, or big insights, we're truly after. Each one of these mechanism - visualizing the data and interacting with the visualized data - is really two sides of the same coin each equally important in fully understanding what the data is trying to tell us. Here's Paul's post:
This is the first in a series of posts dealing with interactive visualization. These posts take a conceptual rather than technical approach, and are not concerned with any specific technology, platform, or type of visualization. This first post will discuss the general importance of interaction, and subsequent posts will dive into more detail.
The role of visualization in making informed decisions, making sense of bodies of information and datasets, achieving valuable insights in the era of big data—and, in general, performing data-driven and information-intensive activities—has become widely acknowledged in recent years. Additionally, research to date has uncovered and characterized many of the benefits of visualization for performing all kinds of tasks and activities.
For instance, we know that visualization can reveal properties of datasets that are not revealed by common statistical analysis, determine what information is perceived and processed, help distribute cognitive and perceptual load, and benefit human tasks and activities in numerous other ways.
Although we know that visualizations can help with understanding, making decisions, and performing other such activities, in the modern era, visualizing the data is only half the concern—we must also be concerned with opportunities for interacting with data (or, more correctly, interacting with the visualization of data). Historically, largely due to media constraints, visualizations have been static (think about the use of charts, graphs, and diagrams in books throughout the past centuries—even back to the use of drawings on cave walls). Because we are accustomed to static visualizations, interaction is often considered only as an afterthought to visualization design. Moreover, much of the visualization design guidance we currently have has come from an era in which static media were dominant. If we want to get the most out of our data, we must have interaction at the forefront of consideration. Indeed, research has shown that static visualizations can lead us to draw the wrong conclusions about the underlying information! Interaction is not simply a nice thing to have—it actually goes to the heart of human thinking itself—that is, we think and carry out our tasks by interacting with things in the world! In other words, interaction is a fundamental part of human activity.
Let’s look in a bit more detail:
When we engage in any type activity that involves data or information that is external to our brains, and that requires a reasonable degree of mental effort (e.g., making a decision about where to distribute resources based on complex sales data from the last quarter), a certain amount of cognitive load is placed on the person who is doing the reasoning. When we use tools to help us (e.g., visualizations), some of the burden is ‘offloaded' onto the visualizations due to their exploitation of perceptual characteristics of human beings. While we can gain much valuable information about visualization design simply from understanding this, it is a mistake to assume that this is the extent of the utility of visualization. What is missing from such an assessment is an understanding of the fundamental manner in which human beings engage in such cognitive, information-intensive activities: we interact with things in the world. Research done in the cognitive sciences in recent decades suggests that actions that we perform in the world should often be considered as part of thought itself! Think about how we naturally want to pick objects up, handle them—interact with them—in order to understand, make sense of, and use them to make future decisions. If we think of visualizations in a similar fashion, we will begin to see the deep potential that interaction brings to gaining insights from data.
To illustrate this point simply, consider the visualization shown here:
This particular visualization is a type of matrix diagram that represents character co-occurrences in Victor Hugo’s Les Misérables. In this visualization, each colored cell represents two characters that appeared in the same chapter; darker cells indicate characters that co-occurred more frequently.
Take a second to reflect on what insights can be gained from looking at this visualization in its static form. Now, head over to this site to see the interactive version. Interact with it using the drop-down menu, and see if you gain any more insight into the underlying relationships. Making this visualization interactive brings it to life and provides numerous benefits for thinking and reasoning about the underlying data. Although this is a very simple example, it is used to give an indication as to the possibilities and utility of interaction in visualization.
That’s it for now. Subsequent posts will dive further into the issue of interaction, and will address the following:
• fundamental patterns of interaction with visualizations and their benefits for supporting tasks and activities
• common properties of visualizations that influence how they are perceived, and how they should be made adjustable through interaction
Stay tuned for these in the near future!