Ontology Driven Information Systems for Search, Integration and Analysis on Semantic Technology

Ontology Driven Information Systems for Search, Integration and Analysis on Semantic Technology

As a constituent technology, ontology work of this sort is defensible. As the basis for programmatic research and implementation, it is a speculative and immature technology of uncertain promise.

Users will be able to use programs that can understand semantics of the data to help them answer complex questions. This sort of hyperbole is characteristic of much of the genre of semantic web conjectures, papers, and proposals thus far. It is reminiscent of the AI hype of a decade ago and practical systems based on these ideas are no more in evidence now than they were then.

Such research is fashionable at the moment, due in part to support from defense agencies, in part because the Web offers the first distributed environment that makes even the dream seem tractable.

It (proposed research in Semantic Web) pre-supposes the availability of semantic information extracted from the base documents -an unsolved problem of many years...

Google has shown that huge improvements in search technology can be made without understanding semantics. Perhaps after a certain point, semantics are needed for further improvements, but a better argument is needed.

These reservations and skepticism likely stem from a variety of reasons. Specifically, database researchers may have reservations stemming from the over whelming role of description logic in the W3C's Semantic Web Activity and related standards. The vision of the Semantic Web proposed in several articles may seem, to many readers, like a proposed solution to the long standing AI problems. Lastly, one of the major skepticism is related to the legitimate concern about the scalability of the three core capabilities for the Semantic Web to be successful, namely the scalability of (a) ontology creation and maintenance of large ontologies, (b) semantic annotation, and (c) inference mechanisms or other computing approaches involving large, realistic ontologies, metadata, and heterogeneous data sets.

Despite these reservations, some of them well justified, we believe semantic technology is beginning to mature and will play a significant role in the development of future information systems. We believe that database research will greatly benefit by playing critical roles in the development of both Semantic Technology and the Semantic Web. In addition, we also feel that the database community is very well equipped to play their part in realizing this vision.

• Identify some prevalent myths about the Semantic Web.

• Identify instances of Semantic Technology in action and how the database community can make invaluable contributions to the same.

By Semantic Technology, we imply application of techniques that support and exploit semantics of information (as opposed to syntax and structure/schematic issues ) to enhance existing information systems. In contrast, the Semantic Web technology (more specifically its vision) is best defined as "The Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation". Currently in more practical terms, Semantic Web technology also implies the use of standards such as RDF/RDFS, and for some OWL. It is however important to note that while description logic is a center piece for many Semantic Web researchers, it is not a necessary component for many applications that exploit semantics. For the Semantic Technology as the term is used here, complex query processing, involving both metadata and ontology takes the center piece,and is where the database technology continues to play a critical role. This becomes especially relevant when ontology is populated by many persons or by extracting and integrating knowledge from multiple sources.

Article Source: http://EzineArticles.com/expert/Will_J_Green/1222726

Article Source: http://EzineArticles.com/6684828

_(By Will J Green).