The Semantic Web is a project that intends to create a universal medium for information exchange by putting documents with computer-processable meaning (semantics) on the World Wide Web. Currently under the direction of the Web's creator, Tim Berners-Lee of the World Wide Web Consortium, the Semantic Web extends the Web through the use of standards, markup languages and related processing tools.

Contents [hide] 1 Relationship to the Hypertext Web 2 Components 3 Potential benefits of the Semantic Web 4 Potential threats and criticism of the Semantic Web 5 See also 6 References

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Relationship to the Hypertext Web

Currently, the World Wide Web is based primarily on documents written in HyperText Markup Language (HTML), a markup convention that is used for coding a body of text interspersed with multimedia objects such as images and interactive forms. HTML, as it is generally deployed, has limited ability to classify the blocks of text on a page, apart from the roles they play in a typical document's organization and in the desired visual layout. For example, with HTML and a tool to render it (perhaps Web browser software, perhaps another user agent), one can create and present a page that lists items for sale. The HTML of this catalog page can make simple, document-level assertions such as "this document's title is 'Widget Superstore'". But there is no capability within the HTML itself to unambiguously assert that, say, item number X586172 is an Acme Gizmo with a retail price of €199, or that it is a consumer product. Rather, HTML can only say that the span of text "X586172" is something that should be positioned near "Acme Gizmo" and "€199", etc. There is no way to say "this is a catalog" or even to establish that "Acme Gizmo" is a kind of title or that "€199" is a price. There is also no way to express that these pieces of information are bound together in describing a discrete item, distinct from other items perhaps listed on the page. The Semantic Web addresses this shortcoming, using the descriptive technologies Resource Description Framework (RDF) and Web Ontology Language (OWL), and the data-centric, customizable Extensible Markup Language (XML). These technologies are combined in order to provide descriptions that supplement or replace the content of Web documents. Thus, content may manifest as descriptive data stored in Web-accessible databases, or as markup within documents (particularly, in Extensible HTML (XHTML) interspersed with XML, or, more often, purely in XML, with layout/rendering cues stored separately). The machine-readable descriptions enable content managers to add meaning to the content, thereby facilitating automated information gathering and research by computers.

Components

The Semantic Web comprises the standards and tools of XML, XML Schema, RDF, RDF Schema and OWL. The OWL Web Ontology Language Overview describes the function and relationship of each of these components of the Semantic Web:

• XML provides a surface syntax for structured documents, but imposes no semantic constraints on the meaning of these documents.
• XML Schema is a language for restricting the structure of XML documents.
• RDF is a simple data model for referring to objects ("resources") and how they are related. An RDF-based model can be represented in XML syntax.
• RDF Schema is a vocabulary for describing properties and classes of RDF resources, with a semantics for generalization-hierarchies of such properties and classes.
• OWL adds more vocabulary for describing properties and classes: among others, relations between classes (e.g. disjointness), cardinality (e.g. "exactly one"), equality, richer typing of properties, characteristics of properties (e.g. symmetry), and enumerated classes.

The intent is to enhance the usability and usefulness of the Web and its interconnected resources through:

• documents "marked up" with semantic information (an extension of the HTML <meta> tags used in today's Web pages to supply information for Web search engines using web crawlers). This could be machine-readable information about the human-readable content of the document (such as the creator, title, description, etc., of the document) or it could be purely metadata representing a set of facts (such as resources and services elsewhere in the site). (Note that anything that can be identified with a Uniform Resource Identifier (URI) can be described, so the semantic web can reason about people, places, ideas, cats, etc.)
• common metadata vocabularies (ontologies) and maps between vocabularies that allow document creators to know how to mark up their documents so that agents can use the information in the supplied metadata (so that Author in the sense of 'the Author of the page' won't be confused with Author in the sense of a book that is the subject of a book review).
• automated agents to perform tasks for users of the Semantic Web using this metadata
• web-based services (often with agents of their own) to supply information specifically to agents (for example, a Trust service that an agent could ask if some online store has a history of poor service or spamming).

The primary facilitators of this technology are URIs (which identify resources) along with XML and namespaces. These, together with a bit of logic, form RDF, which can be used to say anything about anything. As well as RDF, many other technologies such as Topic Maps and pre-web artificial intelligence technologies are likely to contribute to the Semantic Web. A popular application of the Semantic Web is Friend of a Friend (or FoaF), which describes relationships among people and other agents in terms of RDF. An implementation of a Semantic Web Browser is the BigBlogZoo. Over 60,000 xml feeds have been categorised using the DMOZ schema and can be spidered. It is free. The commercial version, MediaMiner, allows you to mine these feeds for information. Another freely downloadable tool is the new plug-in to Firefox, Piggy Bank. Piggy Bank works by extracting or translating web scripts into RDF information and storing this information on the user’s computer. This information can then be retrieved independently of the original context and used in other contexts, for example by using Google Maps to display information. Piggy Bank works with a new service, Semantic Bank, which combines the idea of tagging information with the new web languages. Piggy Bank was developed by the Simile Project, which also provides RDFizers, tools that can be used to translate specific types of information, for example weather reports for US zip codes, into RDF. Efforts like these could ease a potentially troublesome transition between the web of today and its semantic successor. A Semantic Web is not Artificial Intelligence. The concept of machine-understandable documents does not imply some magical artificial intelligence which allows machines to comprehend human mumblings. It only indicates a machine's ability to solve a well-defined problem by performing well-defined operations on existing well-defined data. Instead of asking machines to understand people's language, it involves asking people to make the extra effort to create information comprehensible to a computer. Even though it is simple to define, RDF at the level with the power of a semantic web will be a complete language, capable of expressing paradoxes and tautologies, and in which it will be possible to phrase questions whose answers would to a machine require a search of the entire web and an unimaginable amount of time to resolve. Each mechanical RDF application will use a schema to restrict its use of RDF to a deliberately limited language. However, when links are made between the RDF webs, the result will be an expression of a huge amount of information. It is clear that because the Semantic Web must be able to include all kinds of data to represent the world, the language itself must be compeletely expressive. The semantic web is the next generation web containing action-able information i.e. information derived from data through a semantic theory so that it can be processed directly and indirectly by machines. A semantic web agent does not have artificial intelligence, it uses the structured sets of information and inference rules to understand the relationship between different data resources. To classify the data from multiple domains based on its properties and its relationship with other data, we need to use descriptive technologies e.g. RDF, RDFS, OWL, XML (these are officially recommended by W3C) to add meaning to the contents of web documents to facilitate automated information gathering and research by computers. RDF is an XML-based standard for describing resources that exist on the web. Resources on the web are identified by URIs, which uses a global naming convention. RDF statements describe a resource, the resource’s properties, and the values of those properties. RDF statements are often referred to as “triples” that consist of a subject, predicate, and object, which correspond to a resource (subject) a property (predicate), and a property value (object). RDFS is used to create vocabularies that describe groups of related RDF resources and the relationships between those resources. OWL defines the types of relationships that can be expressed in RDF using an XML vocabulary to indicate the hierarchies and relationships between different resources.

Potential benefits of the Semantic Web

Humans are capable of using the Web to carry out tasks such as finding the Swedish word for "car," to reserve a library book, or to search for the cheapest DVD and buy it. However, a computer cannot accomplish the same tasks without human direction because web pages are designed to be read by people, not machines. The Semantic Web is a project aimed to make web pages understandable by computers, so that they can search websites and perform actions in a standardized way. The potential benefits are that computers can harness the enormous network of information and services on the Web. A computer could, for example, automatically find the nearest manicurist or book an appointment that fits a person's schedule. Currently there is much data on our computers which we cannot browse, or process by, for example, pulling into a spreadsheet, graphing it or joining it with other data. This includes personal data like calendars, playlists, GPS coordinates, and bank statements; enterprise product and workflow and resources; and public data such as weather, events and the properties of materials. A lot of the things that could be done with the Semantic Web could also be done without it, and indeed already are done in some cases, but the Semantic Web provides a standard which makes such services far easier to implement. Tim Berners-Lee originally expressed the vision of the semantic web as follows: I have a dream for the Web [in which computers] become capable of analyzing all the data on the Web – the content, links, and transactions between people and computers. A ‘Semantic Web’, which should make this possible, has yet to emerge, but when it does, the day-to-day mechanisms of trade, bureaucracy and our daily lives will be handled by machines talking to machines. The ‘intelligent agents’ people have touted for ages will finally materialize. (Berners-Lee, 1999)

Potential threats and criticism of the Semantic Web

Enthusiasm about the Semantic Web could be tempered by concerns regarding censorship and privacy. For instance, text-analyzing techniques can now be easily bypassed by using other words, metaphors for instance, or by using images in place of words. An advanced implementation of the Semantic Web would make it a lot easier for governments to control the viewing and creation of online information as this information would be much easier for an automated content-blocking machine to understand. In addition, the issue has also been raised that with the use of FOAF files and Geolocation meta-data, there would be very little anonymity associated with the authorship of articles on things such as a personal blog. Another criticism of the Semantic Web is that it would be much more time-consuming to create and publish content as there would need to be two formats for one piece of data. One format would need to be specialized for human viewing and the other would have to be specialized for machines. With this being the case, it would be much less likely for companies to adopt these practices as it would only slow down their progress. However, many web applications in development are addressing this issue by creating a machine readable format upon the publishing of data or the request of a machine for such data. Yet another criticism stems from the fact that the Semantic Web is based on a traditional client-server architecture, which ultimately is not scalable. URIs within RDF are still machine-specific references, which calls the persistence of these documents into question. Many have pointed to MAYA's Information Commons as a more practical implementation of the basic RDF schema that is both distributed and ultimately scalable. An eternal concern of some critics is how to find a source of revenue to pay the bandwidth costs. Additionally, just because your computer can retrieve and analyze data, does not mean that you will have the time to consider the analysis.


(source wikipedia.org)