The web today enables people to access documents and services on the Internet but today’s methods require human intelligence. The semantic web augments the current web with formalized knowledge and well-formatted data that can be processed by computers. 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, combining, and acting upon information on the web. Data that is generally hidden away in HTML files is often useful in some contexts, but there is no global system for publishing data in such a way that it can be easily processed by anyone. This makes Semantic Web a rational solution for the problem. This will enable computers to assist human users in tasks and understand data the way they cannot today. If you want to understand how the world of internet works, follow this link.
The layered architecture serves as the basic building block of the system and supports the vision of a Web imbued with meaning. The similarities that it shares with the object-oriented programming language has made the Unified Modelling Language usable by both object-oriented Programming and semantic web development and the Semantic Web Browsers, extend the notion of the Web browser into the Semantic Web. There will also be the creation of new applications and services from combinations of existing service.
Semantics is the study of meaning. It is the branch of linguistics and logic concerned with meaning. It’s as old as the ancient Greeks. For most of us it was a deadly dull sub-discipline of philosophy, to be avoided. But it turns out that we can’t avoid it. We are drowning in a sea of data which occasionally is generously referred to as information‚ but the truth is that almost all of it must be interpreted by humans to be of any use. The growth and availability of data and, therefore, our need to consider it in decision-making and planning is growing exponentially, and our systems, rather than helping with this, are for the most part contributing to the problem.
The Semantic Web is a web that is able to describe things in a way that computers can understand. The Semantic Web is not about links between web pages. The Semantic Web describes the relationships between things (like A is a part of B and Y is a member of Z) and the properties of things (like size, weight, age, and price). In an evolving development of the World Wide Web in which the meaning (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. Tim is also known for introducing HTTP communications, WWW, URIs.
Implementing the Semantic Web requires adding semantic metadata, or data that describes data, to information resources. This will allow machines to effectively process the data based on the semantic information that describes it. When there is enough semantic information associated with data, computers can make inferences about the data, i.e., understand what a data resource is and how it relates to other data. 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. 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.
The common use of the term Semantic Web is to identify a set of technologies, tools, and standards which form the basic building blocks of a system that could support the vision of a Web imbued with meaning. The Semantic Web has been developing a layered architecture, which is often represented using a diagram first proposed by Tim Berners-Lee, with many variations since.
While necessarily a simplification which has to be used with some caution, it nevertheless gives a reasonable conceptualization of the various components of the semantic Web. We describe briefly these layers.
A. Unicode and URI:
Unicode, the Standard for computer character representation, and URIs, the standard for identifying and locating resources (such as pages on the Web), provide a baseline for representing characters used in most of the languages in the world, and for identifying resources.
XML and its related Standards, such as Namespaces, and Schemas, form a common means for structuring data on the Web but without communicating the meaning of the data. These are well established within the Web already.
C. Resource Description Framework:
RDF is the first layer of the Semantic Web proper. RDF is a simple metadata representation framework, using URIs to identify Web- based resources and a graph model for describing relationships between resources. Several syntactic representations are available, including a standard XML format. RDF Schema: a simple type modeling language for describing classes of resources and properties between them in the basic RDF model.It provides a simple reasoning framework for inferring types of resources.
a richer language for providing more complex constraints on the types of resources and their properties.
E. Logic and Proof:
an (automatic) reasoning system provided on top of the ontology structure to make new inferences. Thus, using such a system, a software agent can make deductions as to whether a particular resource satisfies its requirements (and vice versa).
The final layer of the stack addresses issues of trust that the Semantic Web can support. This component has not progressed far beyond a vision of allowing people to ask questions of the trustworthiness of the information on the Web, in order to provide an assurance of its quality.
Understand following Topics:
A. Semantic Web Browser
Semantic Web Browsers, extend the notion of the Web browser into the Semantic Web by allowing the RDF annotations of resources to be read and presented in a structured manner. For example, the Haystack Web-browser from MIT, it aggregates RDF from multiple arbitrary locations and presents it to the user in a human-readable fashion, with point and click semantics that let the user navigate from one piece of Semantic Web data to other, related pieces.
A user can load RDF annotations from other websites, and also catalog information from his or her own file-store or e-mail accounts. The structured searches can be made based on this annotation, and links between information can be created and presented based on the connections between resources embodied in the RDF.
There exist similarities between the Semantic Web and 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 Dereference able Uniform Resource Identifiers in a manner similar to the common programming concept of pointers or “object identifiers” in OOP. Dereference able Uris can thus be used to access “data by reference”. The Unified Modelling Language is designed to communicate about object-oriented systems, and can thus be used for both object-oriented programming and semantic web development.
A. Future Development
We have seen in this article that there has been significant and enthusiastic effort over the last few years to explore and develop the technology, shared vocabularies and ideas which are turning Tim Berners-Lees vision into a reality. There is a long way to We have seen in this paper that there has been significant and enthusiastic effort over the last few years to explore go until it is a standard part of the Web Infrastructure but, nevertheless, there has been startling progress in the last few years. Semantic technologies have become central to a broad range of research and development initiatives. This diagram visualizes the intersections of four major development themes in the semantic wave: networking (e.g., semantic web, grid & p2p), content (e.g., knowledge extraction, semantic enhancement, executable content, semantic search), services (e.g., composite applications, semantic web services), and cognition (e.g. semantic UI, knowledge computing, intelligent agents).
B. Challenges to the development:
Some of the challenges for the Semantic Web include vastness, vagueness, uncertainty, inconsistency and deceit. Automated reasoning systems will have to deal with all of these issues in order to achieve
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 ow price for a gadget. 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, combining, and acting upon information on the web. 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 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.
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 Mark-up 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 itself as descriptive data stored in Web-accessible databases, or as mark-up 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.
We have chosen few areas and tried to apply the semantic web to simplify the process: information management, digital libraries, virtual communities, and e-learning.
A. Information Management:
The Semantic Web enhances the capabilities of those tools which form a familiar part of the current Web so that they can become useful information management tools in their own right. A more structured and directed approach to managing this information space, within institutions can make this information more useful, with less wasted effort, and more capacity to measure the quality of information.
B. Digital Libraries:
the impact on digital libraries, combined with the Open Access Initiative and the rise of open archiving is likely to be quite profound. Libraries become ‘value-added’ information annotators and collators rather than the archivists of externally published literature and the holders of the published output of institutions.
C. Building communities and collaborations:
A major impact is likely to occur in the way that academic communities work together. The tools for forming virtual communities and sharing information across that community are simple and lightweight, and, if the development of blogs and the use of RSS is an indication, can enhance the interaction of an interested community by an enormous amount
all of the above can influence e-learning. However, we should also consider specifically, support for the presentation and delivery of course materials and for assisting and assessing students. Again, the impact of the Semantic Web is likely to mean that these can be more closely tailored to the needs of the user.
The Semantic Web has great potential, and with direct application to education and business sector. however, it has been a long time in development and does require an investment of time, expertise, and resources. But, the time does seem right to start to think how best to use the simpler applications of the technology.
So what should institutions and industries consider doing now? Institutional libraries should be considering joining collaborations to explore how Semantic Web can best be investing in training staff, with a view to providing Semantic Web solutions within the next two to three years. Information science professionals and academics working in particular fields should work together to provide the vocabularies and domain ontologies required to support particular fields.
In the future, the Semantic Web may not even be noticeable. The tools of the Semantic Web will be integrated into Virtual Learning Environments and Virtual Research Environments on our desktops, as well as in browsers and search engines. What we will have is a richer experience of IT that is better able to deliver the right information at the right time in the right way, so we can get on with the serious business of research and teaching.
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