Sep 16th, 2007
Visual Thinking Skills: Architecture, Part 1
One of the most important things that you can do for yourself and your audience when you are considering a solution that involves visual mapping is to ask yourself the right questions about how your solution will be deployed.
One of the most important of these questions that you can ask yourself is:
What visual mapping methodology or mix of methodologies will best express the output of my thinking process in this situation?
There has been an incredible amount of work done in the area of visual thinking. Much of this is academic, or specialized to work in certain fields, but there are many choices that are appropriate for regular general use. Mind mapping is one of the most useful and flexible, partly because of its special limitations. It is easy to make a mind map that is overlarge, but it isn’t too easy to create one that is overcomplicated. Where mind maps are not appropriate, there is usually another excellent choice. I will ignore linear methods such as flow charts and very specialized methods such as Unified Modeling Language and Conceptual Graphs for now and concentrate on very general, dynamic means of knowledge representation.
Here are some basic guidelines when deciding how to express different kinds of visual maps. For each technique, I will list pros and cons, and a sampling of useful software tools.
2D Mind Map, or Idea Map
Nodes radiate out from a single central node. Each node may have an unlimited number of child nodes. Each node except the central node also has one parent and may have an unlimited number of siblings. It is sort of like a tree in the shape of a circle.
Strengths: Lending hierarchical structure to unstructured data or ideas, as in categorizing lists or brainstorming or certain kinds of problem-solving. Mind maps can be freely annotated with text and pictures.
Weaknesses: Mind mapping doesn’t work well when you need flexible relationships among nodes that are cousin or siblings or one another, or a child node having two parent nodes, or many nodes linking to one another in a single diagram that aren’t hierarchically related. It works best in a tree-like structure. Non parent / child relationships can only be indicated by drawing lines between nodes, which can be cumbersome due to the overall circular, nested shape of the diagram.
Software tools: MindManager, FreeMind, NovaMind, Cayra, MindMeister, bubbl.us, Tinderbox
3D Mind Map
Each node has an unlimited number of parents, children, and siblings and any node can be related to any other node in any way that is not paradoxical (a child can’t be its parent node’s parent, etc.). You could describe it as a sphere with a surface that may change almost entirely as it rotates. There is no real central node as in a 2D mind map. Any node can be centralized, contextualizing the presentation of the map, making the relationships radiating from the central node most prominent until another node is centralized. The relationships themselves can be annotated in some tools, similar to concept or topic maps.
Strengths: Almost arbitrarily complex relationships among potentially huge sets of nodes. Surprising insight can be gained into relations inherent to the data set being visualized by just moving around in the map and playing with linking things together.
Weaknesses: 3D mind maps can be challenging to present in printed form and can become overly complicated because so much data can be accommodated by them, all of which is somehow related.
Software tools: PersonalBrain, Cayra, Tinderbox
A Cayra hybrid:
Topic Map, Concept Map, Semantic Network
These are really three different types of diagrams, but they are very similar. They consist of set of typed or untyped nodes connected by typed or untyped lines that are either directional arrows or just lines. They can be more or less formal. There is an ISO standard for topic maps. They tend to be less friendly and a bit more complicated than mind maps, but sometimes convey more information. One node is related to any number of other nodes, and the relationships are usually described (”has a”, “is a”, “loves”, “begins with”). Concept maps are probably the most generally useful of this lot primarily because they tend to be the least formal.
Strengths: Fluid or no hierarchy. Descriptions of arbitrarily complex relationships can be represented. Attempts at combining seemingly unrelated ideas and topics may produce surprisingly useful results. These diagrams are often excellent for diagramming things that lead to complex, difficult-to-read prose.
Weaknesses: If you are not describing something that is pretty formal and limited, these diagrams can be sort of vague. They can also be hard to read if they are on the large side.
Software tools: Tinderbox, CmapTools, Cayra
Venn Diagram
A Venn Diagram is a picture of two or more interlinked circles representing contrasting ideas. Topics are placed in one circle if they apply only to one of the ideas. If a topic applies to two ideas that are next to each other, it is placed in the area where the circles overlap. This diagram has its origin in set theory.
Strengths: Venn diagrams a very good at illustrating comparisons.
Weaknesses: They are good for almost nothing else.
Software tools: Inspiration, SmartDraw, ConceptDraw
In part two of the Visual Thinking Skills: Architecture series we’ll discuss sharing the visual maps we create.
Many people have a difficult time sitting down at a computer or with a piece of paper and creating a visual representation of ideas that are running around in their minds, or of information that is coming into their sphere of influence. There is very much information on the web right now about how to get started with mind mapping or some other visual mapping technique, but not very much beyond the basics. It is this gap between green-field theory and everyday practice that makes visual thinking impractical for many people. I have been using visual mapping tools and techniques for many years, and thought that I would share some advice about hurdles that I’ve overcome or am struggling to clear.
