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The Web part brings in a persistent theme, in which information is distributed— spread throughout the Web—rather than concentrated in a few repositories. Most systems that use concept identification to retrieve information maintain their own concept hierarchies and attempt to identify those concepts in the documents they index. Sometimes concepts in a document collection are identified automatically, with varying success. To go further requires that documents be able to declare their own vocabularies and sets of concepts and to identify where they’re used.
In one sense, meta data is still data; the distinction lies in the intended use of the data and in the subject of the meta data. It’s meta data that will be used for searches and for discovery of information. Annotation can also be thought of as meta data.
Because annotations should be shareable, and because the meaning of different types of annotations should be widely understood, support for extensive annotation capabilities is often seen as part of the Semantic Web.
Consider a sports researcher looking for baseball data. There are various online baseball databases: The Major League Baseball web site is but one of many. But if our researcher wants to find performance statistics for Stan Musial, whose career lasted from the 1940s to the 1960s, she can’t get data for the whole period in a mutually compatible format. At least for baseball statistics, there is some common agreement on the definitions of the most important statistics, so that a batting average is always computed the same way—this is more than can be said for most separate collections of data.
If the Web functioned as an interoperable database, the researcher could get the data from all the important sites, and the researcher’s software would be able to either display all the data together or automatically combine data from, say, the Major League Baseball site and the Baseball Almanac.
Consider an analogy with a physical library. Most libraries in the United States use either the Dewey Decimal System or the Library of Congress method to catalog their books. After using the card catalog or its electronic version, a person becomes familiar with the classifications and learns how to find books on the shelves. Here, the standard access methods are the familiar classification system and the physical arrangement of books in the library.
A more advanced approach would be to send out discovery requests based on the services required, and for candidate services to describe their capabilities in such a way that the would-be user could deduce their capabilities and instigate a conversation to find any missing or uncertain information. Returning to the library example, this would be like getting an experienced research librarian to tell you which reference books to look at and how to understand the information in them.
To give you a feel for the way these areas might interact and how the Semantic
Web could provide great value, here are two scenarios that were developed during
the workshop “Research Challenges and Perspectives of the Semantic Web.”1
Both scenarios illustrate what might be called personal services. Of course,
similar scenarios could be constructed for many other areas, such as business-to-business
transactions. Note that the language is taken directly from the report without
corrections for grammatical and spelling errors.
Clara hit the “explain!” button. “I used his company directory
for finding his DAML2 enhanced vita:
he’s got the required skills as a statistician who led the data mining
group of the database department at Montana U. for the requirement of a researcher
who worked on machine learning.” Clara hit then the “evidence!”
button. The assistant started displaying “I checked his affiliation
with university of Montana, he is cited several times in their web pages:
reasonably trusted; I
checked his publication records from publishers’ DAML sources and asked
bill
assistant a rating of the journals: highly trusted. More details?”
Clara had enough and let her assistant inform Bill’s.
1 This workshop was organized by the European Consortium in Informatics and Mathematics (ERCIM) for the European Union Future Emergent Technology program (EU-FET) and the US National Science Foundation (NSF). It was held in Sophia-Antipolis, France, in October 2001.
2 DARPA Agent Markup Language; see chapter 7.
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Created: March 27, 2003
Revised: October 4, 2004
URL: http://webreference.com/internet/semantic/1
