The visual representation of information is critical for both learning and teaching. To put something on paper and organize the information as to make visual sense – in words, lines, colors, and curves – is to recognize some understanding and to create a basis for new insight and discovery.

Logic is the study of reasoning, the systematic approach to reaching a conclusion, or the examination of competing arguments with regards to a central issue or question. Logic can be broken down into deductive and inductive reasoning, one drawing conclusions from specific examples and the other drawing conclusions from definitions or axioms. Logic can also be broken down into analysis and synthesis, one examining individual component parts and the other combining component parts into a whole. In any event, logic is a way to get from questions to answer, disbelief to belief, and data to insight.

One such type of logic is visual logic, or what I’ll call “spectrum logic”. It’s the combination of the visual representation of information and the many realms of logic. The reason I use the term “spectrum” is two-fold. First of all, it’s by definition the representation of a full range of possible values/conditions for a given topic. And second of all, it suggests continuity along its range and therefore implies a high level of seamlessness and efficiency.

So in the world of analysis and problem solving, how do we apply spectrum logic? Well, just follow every possible visual path from any origin within your visual space and try to optimize your path to the result. Place your problem in the center of a sphere/cube and run the full spectrum of paths to that center point. Left to right and right to left, bottom-up and top-down, outside in and inside out, spiral inward and spiraling out. Think about the component parts that make up the visual space, and the conditions that fall along each path. Why is your problem so complex? What makes it so complex? Can you qualify your problem in color, words, shape, and text? Can you quantify it and its components? Is it made up of many unknown dimensions or a few known ones? Picture your problem, logically break it apart, and put it back together. Take a diverse set of paths to and from your problem, and find out which one gives you an optimal set of insights in return. Hopefully, if the answers and conclusions are not clear, you’ll at least have learned something in the process.