Topic Maps: The GPS of the Web

Topic maps represent a radically new approach to solving some of today's most pressing business problems. We live in an age in which knowledge is becoming the key asset of many organizations, but at the same time we find ourselves drowning in excesses of information. Given such a situation, how do we:

• find that needle of relevant information in the haystack of infosmog that surrounds us,
• capture and manage precious corporate memory, and
• most importantly, build a bridge between knowledge and the information?

Topic maps can help with all three. They promise to revolutionize the ways in which we search for and navigate information, they allow us to model and represent knowledge in an interchangeable form, and they provide a unifying framework for knowledge and information management.

But as with most "radically new" things, the basic concepts are grounded in ideas that are familiar to all of us.

One starting point for understanding topic maps is the traditional back-of-book index -- that carefully handcrafted map into its subject area that enriches any good book. The building blocks of such an index are topics (and the names by which they are known), associations between topics (in the form of "see also" references), and occurrences of those topics (the page numbers or locators).

Topic maps are based on the same core concepts, but in topic maps they are generalized in order to be able to deal with the vastly more demanding requirements of digital information. This generalization allows them to incorporate the key features of glossaries, thesauri, and TOCs, as well as indexes, into a single unified model.

That model basically describes the knowledge structures inherent in the underlying information: It is used to chart the topics of the subject matter and present a concise and accurate map for readers.

This map can then be perused in an intuitive manner that reflects the associative mode typical of the way humans think. Thus, instead of wading through realms of irrelevant information, it becomes possible to navigate around (or search through) a multidimensional topic space to find topics of interest and from there go directly to the precise pieces of information that are most relevant.

Alternatively the map can be used to answer queries of far greater complexity than any of today’s web search engines would be able to tackle.

The basic model of topics and associations, the ability to type those constructs, and a mechanism for dealing with the problem of context, mean that topic maps have a lot in common with the semantic networks used to represent knowledge in the field of artificial intelligence. But they also add a new axis to the model of semantic networks -- that of occurrences -- that provides a bridge to the domain of information management.

This makes topic maps ideal for representing knowledge in other fields as well. For example, topic maps can be used to encode the interrelation of roles, products, procedures, and so on that constitute corporate memory, and to link them to the corresponding documentation; thus topic maps become an enabling technology for knowledge management.

For traditional commercial publishers, producing well-crafted topic maps will be a new way of leveraging their existing knowledge and experience and combating the threat to their existence posed by the vast amounts of information now available for free.

In fact, topic maps are the ideal enabling technology for describing almost any kind of complex relationship, whether it be in information, knowledge, process or social engineering. They will doubtless become the "Global Positioning System of the World Wide Web", but their potential is greater yet. Ontopia seeks to leverage that potential through the delivery of high quality topic map software and consulting services.