contributed articles

Doi: 10.1145/1409360.1409377

How ontologies provide the semantics,
as explained here with the help
of Harry Potter and his owl Hedwig.
By ian hoRRocKs
ontologies
and the
semantic Web
While phenomenally successful in terms of amount
of accessible content and number of users, today’s
Web is a relatively simple artifact. Web content
consists mainly of distributed hypertext and
hypermedia, accessible via keyword-based search and
link navigation. simplicity is one of the Web’s great
strengths and an important factor in its popularity and
growth; even naive users quickly learn to use it and
even create their own content.

however, the explosion in both the range and quantity of Web content also highlights serious shortcomings in the hypertext paradigm. the required content becomes increasingly difficult to locate via search and browse; for example, finding information about people with common names (or famous namesakes) can be frustrating. answering more complex queries, along with more general information retrieval, integration, sharing, and processing, can be difficult or even impossible; for example, retrieving a list of the names of E.u. heads of state is apparently

beyond the capabilities of all existing Web query engines, in spite of the fact that the relevant information is readily available on the Web. Such a task typically requires the integration of information from multiple sources; for example, a list of E.U. member states can be found at europa.eu, and a list of heads of state by country can be found at rulers.org.

Specific integration problems are often solved through some kind of software “glue” that combines information and services from multiple sources. For example, in a so-called mashup, location information from one source might be combined with map information from another source to show the location of and provide directions to points of interest (such as hotels and restaurants). Another approach, seen increasingly in so-called Web 2.0 applications, is to harness the power of user communities in order to share and annotate information; examples include image- and video-sharing sites (such as Flickr and You Tube) and auction sites (such as eBay). In them, annotations usually take the form of simple tags (such as “beach,” “birthday,” “family,” and “friends”). However, the meaning of tags is typically not well defined and may be impenetrable even to human users; examples (from Flickr) include “sasquatchmusicfestival,” “ celebrity-lookalikes,” and “twab08.”

Despite their usefulness, these approaches do not solve the general problem of how to locate and integrate information without human intervention. This is the aim of the semantic Web³ according to the World Wide Web Consortium (W3C) Semantic Web FAQ; the goal is to “allow data to be shared effectively by wider communities, and to be processed automatically by tools as well as manually.” The prototypical example of a semantic Web application is an automated travel agent that, given constraints and preferences, gives the user suitable travel or vacation suggestions. A key feature of such a “software agent” is that it would not simply exploit a predetermined set of informa-