Information Classification: Why I love Topic Maps

Doug Cornelius recently made a post about his trouble with folksonomies and taxonomies. Like him, I’ve had trouble with taxonomies. They’re hard work to build and when the information world they reflect changes you’ve just got to re-do the whole thing again. Folksonomies are a good alternative because they’re built by the users as the content is built. Unfortunately, this unstructured view of the world has troubles with scalability and issues with tags that mean the same thing: e.g. dog, dogs, canine, puppy, as tags all mean the same thing. Is there a way to bridge these two world? The answer is yes, and it involves something called topic maps.

Topic maps is an ISO standard for representing knowledge and often written/expressed as XML. It does this very successfully by capturing how people think about the knowledge inside their heads - that is, in terms of the relationships between bits of information - rather than just capturing information alone.

In the information classification world you can use a topic map to describe the relationship between a cluster of tags that mean the same thing and their relationship to the taxonomic view of the world.

canine equals dog, pooch, puppy, dogs, puppies

In corporate terms, a topic map can store:

• the relationships of a piece of content
• it’s position in a website structure’s hierarchical taxonomy
• all the tags used
• any metadata you can think of (date, author, time published, time changed, Dublin Core metadata if you want)
• a reference link to the records system and the business classification scheme used for appraisal and sentencing.

My Dog has type document

My Dog is about canine

canine is a function of the dog catcher department

canine has a disposal authority of next Tuesday

My Dog should be disposed of next Tuesday

You can also make relationships between pieces of content.

Rex is a canine

In people terms, topic maps also have advantages over other information systems because of the way it represents relationships. When I think of a topic like wine, I also think of Shiraz, Merlot, the Hunter Valley in NSW, my time in France, cheap French Bordeaux… I could go on and on… All of these things are about wine. As I learn more about wine, my thoughts and ideas about the topic of wine adapt, refine, expand and change. It’s hard to capture this fluidity of relationships in a database because the information model needed to support it need to change. In the land of topic maps, because it is based on XML, all you do is express new piece of information as a topic, and then add the new relationships between those topics.

Rex has a property of black colour

Rex has a property of is male

Rex has a property of fur that is fluffy

Rex likes Shiraz-flavoured dog food

Shiraz-flavoured dog food is eaten by dogs

Shiraz-flavoured dog food tastes like wine

Wine contains alcohol

Wine has type red

Wine has type white

Shiraz is a red wine

I recently had an engagement with a government agency. They had clients who, more or less, spoke a different language. They had their own terms for naming the things they did - a very different world to the government agency. In my information architecture report I basically recommended they use a topic map to articulate the relationship between these two world views. For the agency, it gave them the ability to understand and report on their own clients’ work to the Minister in the language of the agency, as well as the ability to communicate to their clients in the language of the clients.

All these things make topic maps very cool and very sexy. If you’re afraid of the folksonomic world because it lacks structure, but still want to give users the ability to tag their own content, then use a topic map to infer structure and relate the folksonomic world to your folk taxonomic or corporate taxonomic world view.

M