From Wikipedia, the free encyclopedia
The Semantic Web is an evolving extension of the World Wide Web in which the semantics of information and services on the web is defined, making it possible for the web to understand and satisfy the requests of people and machines to use the web content. It derives from World Wide Web Consortium director Sir Tim Berners-Lee‘s vision of the Web as a universal medium for data, information, and knowledge exchange.
At its core, the semantic web comprises a set of design principles, collaborative working groups, and a variety of enabling technologies. Some elements of the semantic web are expressed as prospective future possibilities that are yet to be implemented or realized. Other elements of the semantic web are expressed in formal specifications. Some of these include Resource Description Framework (RDF), a variety of data interchange formats (e.g. RDF/XML, N3, Turtle, N-Triples), and notations such as RDF Schema (RDFS) and the Web Ontology Language (OWL), all of which are intended to provide a formal description of concepts, terms, and relationships within a given knowledge domain.
Humans are capable of using the Web to carry out tasks such as finding the Finnish word for “monkey”, reserving a library book, and searching for a low price for a DVD. 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 vision of information that is understandable by computers, so that they can perform more of the tedious work involved in finding, sharing, and combining information on the web.
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.
– Tim Berners-Lee, 1999
Semantic publishing will benefit greatly from the semantic web. In particular, the semantic web is expected to revolutionize scientific publishing, such as real-time publishing and sharing of experimental data on the Internet. This simple but radical idea is now being explored by W3C HCLS group’s Scientific Publishing Task Force.
People keep asking what Web 3.0 is. I think maybe when you’ve got an overlay of scalable vector graphics – everything rippling and folding and looking misty – on Web 2.0 and access to a semantic Web integrated across a huge space of data, you’ll have access to an unbelievable data resource.”
– Tim Berners-Lee, 2006
 Relationship to the hypertext web
 Limitations of HTML
Many files on a typical computer can be loosely divided into documents and data. Documents like mail messages, reports, and brochures are read by humans. Data, like calendars, addressbooks, playlists, and spreadsheets are presented using an application program which lets them be viewed, searched and combined in many ways.
Currently, the World Wide Web is based mainly 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. Metadata tags, for example
provide a method by which computers can categorise the content of web pages.
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 assert unambiguously that, for example, 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.
Semantic HTML refers to the traditional HTML practice of markup following intention, rather than specifying layout details directly. For example, the use of
<em> denoting “emphasis” rather than
<i>, which specifies italics. Layout details are left up to the browser, in combination with Cascading Style Sheets. But this practice falls short of specifying the semantics of objects such as items for sale or prices.
Microformats represent unofficial attempts to extend HTML syntax to create machine-readable semantic markup about objects such as retail stores and items for sale.
 Semantic Web solutions
The Semantic Web takes the solution further. It involves publishing in languages specifically designed for data: Resource Description Framework (RDF), Web Ontology Language (OWL), and Extensible Markup Language (XML). HTML describes documents and the links between them. RDF, OWL, and XML, by contrast, can describe arbitrary things such as people, meetings, or airplane parts. Tim Berners-Lee calls the resulting network of Linked Data the Giant Global Graph, in contrast to the HTML-based World Wide Web.
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 or rendering cues stored separately). The machine-readable descriptions enable content managers to add meaning to the content, i.e. to describe the structure of the knowledge we have about that content. In this way, a machine can process knowledge itself, instead of text, using processes similar to human deductive reasoning and inference, thereby obtaining more meaningful results and helping computers to perform automated information gathering and research.
An example of a tag that would be used in a non-semantic web page:
Encoding similar information in a semantic web page might look like this:
 Relationship to object oriented programming
A number of authors highlight the similarities which the Semantic Web shares with object-oriented programming (OOP). Both the semantic web and object-oriented programming have classes with attributes and the concept of instances or objects. Linked Data uses Dereferenceable Uniform Resource Identifiers in a manner similar to the common programming concept of pointers or “object identifiers” in OOP. Dereferenceable URIs can thus be used to access “data by reference“. The Unified Modeling Language is designed to communicate about object-oriented systems, and can thus be used for both object-oriented programming and semantic web development.
When the web was first being created in the late 1980s and early 1990s, it was done using object-oriented programming languages such as Objective-C, Smalltalk and CORBA. In the mid-1990s this development practice was furthered with the announcement of the Enterprise Objects Framework, Portable Distributed Objects and WebObjects all by NeXT, in addition to the Component Object Model released by Microsoft. XML was then released in 1998, and RDF a year after in 1999.
Similarity to object oriented programming also came from two other routes: the first was the development of the very knowledge-centric “Hyperdocument” systems by Douglas Engelbart , and the second comes from the usage and development of the Hypertext Transfer Protocol.[clarification needed]
 Skeptical reactions
 Practical feasibility
Critics (e.g. Which Semantic Web?) question the basic feasibility of a complete or even partial fulfillment of the semantic web. Cory Doctorow’s critique (“metacrap“)is from the perspective of human behavior and personal preferences. For example, people lie: they may include spurious metadata into Web pages in an attempt to mislead Semantic Web engines that naively assume the metadata’s veracity. This phenomenon was well-known with metatags that fooled the AltaVista ranking algorithm into elevating the ranking of certain Web pages: the Google indexing engine specifically looks for such attempts at manipulation. Peter Gärdenfors and Timo Honkela point out that logic-based semantic web technologies cover only a fraction of the relevant phenomena related to semantics  .
Where semantic web technologies have found a greater degree of practical adoption, it has tended to be among core specialized communities and organizations for intra-company projects. The practical constraints toward adoption have appeared less challenging where domain and scope is more limited than that of the general public and the World-Wide Web.
 An unrealized idea
The original 2001 Scientific American article by Berners-Lee described an expected evolution of the existing Web to a Semantic Web. Such an evolution has yet to occur. Indeed, a more recent article from Berners-Lee and colleagues stated that: “This simple idea, however, remains largely unrealized.”
 Censorship and privacy
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 much 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 geo location meta-data, there would be very little anonymity associated with the authorship of articles on things such as a personal blog.
 Doubling output formats
Another criticism of the semantic web is that it would be much more time-consuming to create and publish content because there would need to be two formats for one piece of data: one for human viewing and one for machines. 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. The development of microformats has been one reaction to this kind of criticism.
Specifications such as eRDF and RDFa allow arbitrary RDF data to be embedded in HTML pages. The GRDDL (Gleaning Resource Descriptions from Dialects of Language) mechanism allows existing material (including microformats) to be automatically interpreted as RDF, so publishers only need to use a single format, such as HTML.
The idea of a ‘semantic web’ necessarily coming from some marking code other than simple HTML is built on the assumption that it is not possible for a machine to appropriately interpret code based on nothing but the order relationships of letters and words. If this is not true, then it may be possible to build a ‘semantic web’ on HTML alone, making a specially built ‘semantic web’ coding system unnecessary.
There are latent dynamic network models that can, under certain conditions, be ‘trained’ to appropriately ‘learn’ meaning based on order data, in the process ‘learning’ relationships with order (a kind of rudimentary working grammar). See for example latent semantic analysis
The semantic web comprises the standards and tools of XML, XML Schema, RDF, RDF Schema and OWL that are organized in the Semantic Web Stack. The OWL Web Ontology Language Overview describes the function and relationship of each of these components of the semantic web:
- XML provides an elemental syntax for content structure within documents, yet associates no semantics with the meaning of the content contained within.
- XML Schema is a language for providing and restricting the structure and content of elements contained within XML documents.
- RDF is a simple language for expressing data models, which refer to objects (“resources“) and their relationships. An RDF-based model can be represented in XML syntax.
- RDF Schema is a vocabulary for describing properties and classes of RDF-based resources, with semantics for generalized-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.
- SPARQL is a protocol and query language for semantic web data sources.
Current ongoing standardizations include:
- Servers which expose existing data systems using the RDF and SPARQL standards. Many converters to RDF exist from different applications. Relational databases are an important source. The semantic web server attaches to the existing system without affecting its operation.
- 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-understandable information about the human-understandable 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 animals, people, places, ideas, etc.) Semantic markup is often generated automatically, rather than manually.
- 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 data
- 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)
This section provides some example projects and tools, but is very incomplete. The choice of projects is somewhat arbitrary but may serve illustrative purposes. It is also remarkable that in this early stage of the development of semantic web technology, it is already possible to compile a list of hundreds of components that in one way or another can be used in building or extending semantic webs.
DBpedia is an effort to publish structured data extracted from Wikipedia: the data is published in RDF and made available on the Web for use under the GNU Free Documentation License, thus allowing Semantic Web agents to provide inferencing and advanced querying over the Wikipedia-derived dataset and facilitating interlinking, re-use and extension in other data-sources.
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.
The SIOC Project – Semantically-Interlinked Online Communities provides a vocabulary of terms and relationships that model web data spaces. Examples of such data spaces include, among others: discussion forums, weblogs, blogrolls / feed subscriptions, mailing lists, shared bookmarks, image galleries.
 Open GUID
Aimed at providing context for the Semantic Web, Open GUID maintains a global Identifier repository for use in the linked web. Domain-specific Ontologies and content publishers establish identity relationships with Open GUIDs.
Semantic Interoperability of Metadata and Information in unLike Environments
A database consolidating high-throughput life sciences experimental data tagged and connected via biomedical ontologies. Nextbio is accessible via a search engine interface. Researchers can contribute their findings for incorporation to the database. The database currently supports gene or protein expression data and is steadily expanding to support other biological data types.
 Linking Open Data
The Linking Open Data project is a community-led effort to create openly accessible, and interlinked, RDF Data on the Web. The data in question takes the form of RDF Data Sets drawn from a broad collection of data sources. There is a focus on the Linked Data style of publishing RDF on the Web. See #Triplify for a small plugin to expose data from your Web application as Linked Data.
The project is one of several sponsored by the W3C’s Semantic Web Education & Outreach Interest Group (SWEO).
Insemtives is a European Seventh Framework Program (FP7) -funded project with the objective to bridge the gap between human and computational intelligence for the semantic content authoring.
 Notification Services
 Semantic Web Ping Service
The Semantic Web Ping Service is a notification service for the semantic web that tracks the creation and modification of RDF based data sources on the Web. It provides Web Services for loosely coupled monitoring of RDF data. In addition, it provides a breakdown of RDF data sources tracked by vocabulary that includes: SIOC, FOAF, DOAP, RDFS, and OWL.
 Piggy Bank
Another freely downloadable tool is the Piggy Bank plug-in to Firefox. 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.
 See also
- Linked Data Web
- Social Semantic Web
- Semantic Web Services
- Semantic Sensor Web
- Semantic advertising
- Entity-attribute-value model
- Website Parse Template
- Wikipedia:Semantic MediaWiki
- List of emerging technologies
- ^ Berners-Lee, Tim; James Hendler and Ora Lassila (May 17, 2001). “The Semantic Web“. Scientific American Magazine.
. Retrieved on 2008-03-26.
- ^ a b “W3C Semantic Web Frequently Asked Questions”. W3C.
. Retrieved on 2008-03-13.
- ^ Herman, Ivan (2008-03-07). “Semantic Web Activity Statement”. W3C.
. Retrieved on 2008-03-13.
- ^ “Design Issues”. W3C.
. Retrieved on 2008-03-13.
- ^ Herman, Ivan (2008-03-12). “W3C Semantic Web Activity”. W3C.
. Retrieved on 2008-03-13.
- ^ Berners-Lee, Tim; Fischetti, Mark (1999). Weaving the Web. HarperSanFrancisco. chapter 12. ISBN 9780062515872.
- ^ Victoria Shannon (2006-06-26). “A ‘more revolutionary’ Web”. International Herald Tribune.
. Retrieved on 2006-05-24.
- ^ Knublauch, Holger; Oberle, Daniel; Tetlow, Phil; Evan (2006-03-09). “A Semantic Web Primer for Object-Oriented Software Developers”. W3C.
. Retrieved on 2008-07-30.
- ^ Connolly, Daniel (2002-08-13). “An Evaluation of the World Wide Web with respect to Engelbart’s Requirements”. W3C.
. Retrieved on 2008-07-30.
- ^ Engelbart, Douglas (1990). “Knowledge-Domain Interoperability and an Open Hyperdocument System”. Bootstrap Institute.
. Retrieved on 2008-07-30.
- ^ Connolly, Dan. “From the editor… WebApps”. W3C.
. Retrieved on 2008-07-30.
- ^ Gärdenfors, Peter (2004), “How to make the Semantic Web more semantic”, Formal Ontology in Information Systems: proceedings of the third international conference (FOIS-2004) (IOS Press): p. 17-34
- ^ Timo Honkela, Ville Könönen, Tiina Lindh-Knuutila and Mari-Sanna Paukkeri (2008), “Simulating processes of concept formation and communication“, Journal of Economic Methodology,
- ^ a b Ivan Herman (2007). “State of the Semantic Web”. Semantic Days 2007.
. Retrieved on 2007-07-26.
- ^ Berners-Lee, Tim (2001-05-01). “The Semantic Web”. Scientific American.
. Retrieved on 2008-03-13.
- ^ Nigel Shadbolt, Wendy Hall, Tim Berners-Lee (2006). “The Semantic Web Revisited”. IEEE Intelligent Systems.
. Retrieved on 2007-04-13.
- ^ See, for instance: Bergman, Michael K.. “Sweet Tools”. AI3; Adaptive Information, Adaptive Innovation, Adaptive Infrastructure.
. Retrieved on 2009-01-05.
- ^ “Open GUID”. OpenGUID.net.
. Retrieved on 2008-10-19.
 Further reading
- Grigoris Antoniou, Frank van Harmelen (2008-03-31). A Semantic Web Primer, 2nd Edition. The MIT Press. ISBN 0262012421. .
- Dean Allemang, James Hendler (2008-05-09). Semantic Web for the Working Ontologist: Effective Modeling in RDFS and OWL. Morgan Kaufmann. ISBN 9780123735560. .
- John Davies (2006-07-11). Semantic Web Technologies: Trends and Research in Ontology-based Systems. Wiley. ISBN 0470025964. .
- Pascal Hitzler, Markus Krötzsch, Sebastian Rudolph (2009-08-25). Foundations of Semantic Web Technologies. CRCPress. ISBN 142009050X.
- Thomas B. Passin (2004-03-01). Explorer’s Guide to the Semantic Web. Manning Publications. ISBN 1932394206. .
- Liyang Yu (2007-06-14). Introduction to Semantic Web and Semantic Web Services. CRC Press. ISBN 1584889330. .
- Jeffrey T. Pollock (2009-03-23). Semantic Web For Dummies. For Dummies. ISBN 0470396792. .
 External links
- W3C Semantic Web Activity
- Semantic Web Interest Group IRC channel
- semanticweb.org the Semantic Web community wiki, including descriptions of many related tools, events, and ontologies
- The Semantic Web: An Introduction
- Shiyong Lu, Ming Dong, and Farshad Fotouhi, “The Semantic Web: Opportunities and Challenges for Next-Generation Web Applications”, Information Research, Special Issue on the Semantic Web, 7(4), 2002.
- Semantic Web in c#
- Introduction to Ontologies and Semantic Web
- GoPubMed: bringing Pubmed and the semantic web together
- Semantic Web Video Lectures
- Corporate Semantic Web – Research group focused on adoption of Semantic Web technologies in enterprises
- Insemtives – EU FP7 Research project focused on incentivising users to contribute semantic content
 Semantic Web software and demonstrations
- Human Computation Video Luis Von Ahn presents innovative techniques to incorporate RDF info into a database of images, video or other group of data.
- SWED portal provided by WordPressHelp
- Semantic Systems Biology
- Semantic Search engine provided by Inbenta
- Semandeks an approach for generating semantic content through social input
- Maven Semantic Healthcare Database