Communicating data visually is not only about perception and precision, but also understanding. ISOTYPE was developed to bridge the gap between showing data in a way that’s easy to read and at the same time easier to understand than unadorned bar charts. Continue reading The ISOTYPE
How do we know what we can do with things in the world or in user interfaces? What makes us push buttons, flip switches, or pick up objects that fit our hands? This guidance comes from affordances, a clever and intuitive theory that has been around for decades but is often misunderstood. Continue reading Affordances
Networks are usually drawn using a technique called node-link diagrams. While that works well for small graphs (the technical name for networks), it breaks down beyond a few dozen nodes. Better techniques exist, though these are currently focused on specific types of graphs or answer particular questions. Continue reading Graphs Beyond the Hairball
Venn diagrams are a great way to visualize the structure of set relationships. They’re also an example of a technique that works very well for a particular purpose, but that entirely fails outside its well-defined scope or when the number of sets gets too large.
The common wisdom in visualization is that to find periodicity in data, it should be displayed on a spiral whose period the user can control. Repeating patterns are easy to spot on a spiral, and its layout suggests repetition. But are spirals really the most effective way of finding periodic patterns? Here is an interactive version that lets you compare spirals against a rectangular layout to find out for yourself.
Continue reading Spirals for Periodic Data
When visualizing uncertainty in data, a common choice is to use blur. While that may seem natural, it is unfortunately ineffective. Blur has the effect of guiding attention, but is hard to quantify and annoying to look at. Uncertainty information, or any other data, cannot be shown effectively this way. Continue reading Blur and Uncertainty Visualization
Parallel coordinates are one of the most famous visualization techniques, and among the most common subjects of academic papers in visualization. While initially confusing, they are a very powerful tool for understanding multi-dimensional numerical datasets.
Continue reading Parallel Coordinates
Pie charts are perhaps the most ubiquitous chart type; they can be found in newspapers, business reports, and many other places. But few people actually understand the function of the pie chart and how to use it properly. In addition to issues stemming from using too many categories, the biggest problem is getting the basic premise: that the pie slices sum up to a meaningful whole.
Continue reading Understanding Pie Charts
Treemaps are the single most used ‘real’ InfoVis technique there is. Interestingly, they have proven to be even more useful for unstructured data than for the hierarchies which they were originally developed for. Here is a brief history, discussion of current practical uses, and of the importance of treemaps for the adoption and understanding of information visualization.
Continue reading Treemaps
Visual representations of time are particularly interesting, because they seem so logical. A point in time is a point in the visualization, an interval is a line. But things are not always that simple: planning and temporal uncertainty require more powerful visual tools. Sets of Possible Occurrences (SOPOs) are an example of a visual representation of time that is very flexible and powerful – and totally unintuitive.
Continue reading Sets of Possible Occurrences