This page is an overview of W3C's use of TAP for supporting W3C's Experimental Semantic Search, an extension of W3C's search service that helps contextualize a users query in terms of relevant W3C documents, activities, people, and services.
TAP's goals are to enable the Semantic Web by providing some simple tools that make the web a giant distributed Database. TAP is open source development effort by R.V. Guha (IBM), Rob McCool (Stanford) and others which provide a set of protocols and conventions that create a coherent whole of independantly produced bits of information, and a simple API to navigate the graph. Local, independantly managed knowledge bases can be aggegated to form selected centers of knowledge useful for particular applications.
Given a users search term, TAP provides for the ability to look up the term in a Knowledge Base (a collection of related information). If the term is found in the Knowledge Base (KB), based on the type of the concept it denotes, we determine the kinds of activities that are typically associated with that concept. Based on that, we determine the kinds of data (i.e, property types of the concept) from the global graph that should be used to augment the search results.
The information and communication intensive environment of the W3C provides challenges for effective access to content. Data is maintained at W3C in various structures, managed by different parts of the organization for a variety of reasons. This data can be represented in RDF/XML and as such stitched together to provide something greater than the sum of the individual parts. This combined data provides the basis for the knowledge base which drives the W3C Semantic Search application. These data sets include: