Computerworld - Computers have so overloaded us with data, it's become increasingly difficult to find the information we seek. Beginning in the 1990s, powerful search engines like Yahoo, AltaVista and Google made the Web an incomparably valuable information resource, but the growth of available information has rendered even those remarkable tools far less useful. Google currently indexes more than 4 billion pages, and queries often return tens of thousands of pages, but they are arranged in no discernable order.
One promising approach, still in its infancy, is called topic mapping.
Consider the traditional nonfiction book. The care with which its index is created can make the difference between it functioning as a reference work or being a nearly useless compilation of facts. A good index shows what topics are covered, where to find them and how they are organized; offers subcategories and cross-references; and provides pointers to related topics.
But even the best such indexes have limitations. Each covers just one work, and books' very nature restricts the types of information an index can reference. If we want to encompass more than the ideas in a single book—say, a company's accumulated store of documents and its knowledge base—we need to include more than words on paper. We can find pieces of this knowledge in e-mail messages and headers, individual calendars and schedules, spreadsheets, and structured and unstructured documents in a variety of formats. It can also be found in databases and data warehouses of various types; libraries of images, including audio and video; and data and business rules contained inside application programs and data files. And we must always be aware of security and privacy concerns—who can access what information? Where do we begin?
In contrast, a topic map is a kind of data structure, just as an outline or a set of categories is. In practice, topic maps were standardized by the International Standards Organization in 2000 (ISO/IEC 13250) as XML Topic Maps, or XTM. XTM provides a basic model using XML tags to represent the structure of information resources, concepts and the relationships between them.
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