Reality, What a Concept (Map)!

Outwardly, Mindmaps and Concept Maps are quite similar. They both have:

• Nodes, representing concepts, ideas, or topics,
  
• Links between the nodes, and
  
• They both begin with a central idea.
  

If we dig into the ideas behind them, however, differences begin to emerge. Last time, I briefly presented this information for Mindmaps. Today, I'll do the same for Concept Maps. Again, keep in mind that this post just skims the surface of the topic of Concept Maps. It is a large field of study, with plenty of literature to study on your own if you are interested.

In the late 1970s and early 1980s, Joseph D. Novak first developed Concept Maps as a tool for education. Since that time, it has developed into a powerful tool used in a wide array of fields. I stumbled upon a great Concept Map, created by Novak himself, for a simple case of a Concept Map explaining Concept Maps. It does such a wonderful job that there is really very little chance that I can add much of value to it, but I'll try to do it anyway.

In the simple case where the Concept Map is a stand-alone tool, it is often used to understand complex ideas. The user starts out with a Focus Question, and goes on to map out relationships to and within the Central Concept. There are several properties that describe a Concept Map:

• It starts with a Central Concepts at the top and is read top-to-bottom, so it starts out looking like a tree,
  
• The Map helps to answer a Focus Question,
  
• A Concept Map represents organized knowledge which allows for better understanding,
  
• Unlike in Mindmaps, concepts may have multiple parents in Concept Maps,
• Nodes represent concepts,
• There are both downward links and crosslinks,
  
• Links are just as important as nodes,
  
• Links are labeled and describe type of relationships between concepts,
  
• Crosslinks can tie together different domains of knowledge in the Map, and
  
• During the creation of the Concept Map, crosslinks can often represent creative leaps.
  

Often, instead of a stand-alone tool, it is part of a larger, automated system. The Concept Map is often the User Interface for a Knowledge Management System or a Computational Reasoning System. Knowledge can be input, or presented, through a Concept Map.

We can see how some simple computational reasoning might work. Structured knowledge enters a system using a Concept Map. If incomplete knowledge enters the system and matches the structure of the Map, then the system may be able to automatically infer missing relationships. As a simple example, we have a Concept Map representing the structure of a family, and knowledge enters the system saying Bob "is the son of" Lisa and Chuck "is the son of" Lisa. Based upon the knowledge input to the system through the "Family" Concept Map, the system can infer that Bob "is the brother of" Chuck, and that Chuck "is the brother of" Bob.

This Concept Map, from the same paper as the image above, represents the seasons. It presents all the information about how the seasons are determined and how they relate to each other. As you can see, a relatively small, simple Map is packed with a lot of knowledge. If you wanted to learn about seasons, this would be an effective way to do it. It would also be a good way for you to communicate what you know about seasons to someone else.

Now that I've introduced both Mindmaps and Concept Maps, next time I'll talk about when you might want to use a Mindmap rather than a Concept Map, and vice versa. If you have any questions, just post them as comments, and I'll respond to them as quickly as is possible.

N.B. Thanks to Joseph D. Novak and Alberto J. Cañas for the images used in this post, from their paper:

The Theory Underlying Concept Maps and How to Construct Them, J. D Novak & A. J. Cañas (2006), Technical Report IHMC CmapTools 2006-01, Florida Institute for Human and Machine Cognition, 2006.