- Transaction between systems business - Biology, law etc 65,900,000 results were returned Semantic web gives solutions to the above problems. 2. Introduction to the Semantic Web: According to Sir Tim “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.” Web is Human Friendly Whereas the SEMANTIC WEB is machine friendly. Semantic Web means adding semantic annotation to web resources. We can make the Web machine friendly by Creating an environment for Knowledge inference. 2. Making Knowledge self-explainable for machines. 3. Establishing Trust We can make it meaningful for machines as shown in figure. 3. Ontologies: Ontology is standard for some knowledge domain. Examples are Healthcare, Bioinformatics, and CRM and web services. It provides a formal and agreed upon controlled vocabulary, which is used to define concepts and information can be tagged according to these concepts.
Properties (price is a property of product), subclass Of (Employee is subclass of person). OWL ontologies can be developed independently, having concepts reference each other. Network effect is shown in second figure. So SEMANTIC WEB is • The next generation of the WWW • Information has machine-process able and machine understandable Semantics • Not a separate Web but an augmentation of the current one • Ontologies as building block
6. CHALLENGES AND OPPORTUNITIES: To make the semantic web working we need the ontology technology as follows: • Ontology Languages: Expressivity Reasoning support Web compliance • Ontology Reasoning: Large scale knowledge handling o Fault-tolerant o Stable & scalable inference machines • Ontology Management Techniques: o Editing and browsing o Storage an d retrieval o Versioning and evolution Support • Ontology Integration Techniques: o Ontology mapping, alignment, merging o Semantic interoperability determination 7. BOTTLENECKS: Sufficient metadata is the main bottleneck of the Semantic Web. There is a loop: - Without metadata, no applications will be built - Without applications, no one will create metadata
The gap between academic and commercial is called THE META DATA GAP. 8. META DATA CHASM: Ontology creation requires companies and organization to standardize their concepts. It is much harder than to standardize than communication protocols. Ontology creation requires large investments. Because ontologies reduce the uncertainty of information, their benefits will be revealed mainly in the long run. 9. SEMANTIC WEB APPLICATIONS: • Adobe – uses RDF as a basis for documenting meta-data, in PDF and other tools • Boeing – uses RDF and OWL in several internal projects • AGFA – uses RDF to categorize medical photos • NOKIA – lots of Semantic Web activities. Including RDF knowledge store • IBM - Strong research activities FOAF: Stands for “Friend Of A Friend”. It provides a template for metadata about people, and their interests, relationships and activities. It is an open community-lead and open source initiative. FOAF is used to trust e-mail. The trust can be inferred as shown in figure.
13. Conclusion: We conclude that Semantic Web can be seen as the huge engineering solution to the problems of WWW. One of the best things about the web is that it’s so many different things to so many different people. The coming Semantic Web will multiply this versatility a thousand fold. For some, t he defining feature of the Semantic Web will be the ease with which your PDA, your laptop, your desktop, your server, and your car will communicate with each other. For others, it will be the automation of corporate decisions that previously had to be laboriously For still others, it will be the ability to assess the trust worthiness of documents on the web. . However, the Semantic web vision of a web has possibilities for application in most web technology.