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SEMANTIC WEB

ABSTRACT:

This topic introduces one of the toughest problems that the web is facing today.

Search engines now a day’s depends and search only depending on the key words. Humans

are capable of using the Web to carry out tasks such as finding the Finish 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. Semantic Web which is machine

friendly and makes the computer to know what the user wants. Once your computer can

understand a person a place and event days it can help you interact with those things.This

topic introduces the semantic web concepts and how to implement it using RDFa (Resource

Description Framework) and foaf(friend of a friend) vocabulary on your webpage. So the

Semantic Web makes our life easier by helping computers helps us get what we want.

However Semantic Web technologies are still very much in their infancies, and the future of

the project in general appears to be bright.

Electronics & Computer Engineering, P.V.P.S.I.T 1



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1.INTRODUCTION:

Currently the focus of a W3C working group, the Semantic Web vision was

conceived by Tim Berners-Lee, the inventor of the World Wide Web. The World Wide Web

changed the way we communicate, the way we do business, the way we seek information and

entertainment – the very way most of us live our daily lives. Calling it the next step in Web

evolution, Berners-Lee defines the Semantic Web as “a web of data that can be processed

directly and indirectly by machines.”

In the Semantic Web data itself becomes part of the Web and is able to be processed

independently of application, platform, or domain. This is in contrast to the World Wide Webas we know it today, which contains virtually boundless information in the form of

documents. We can use computers to search for these documents, but they still have to be

read and interpreted by humans before any useful information can be extrapolated.

Computers can present you with information but can’t understand what the

information is well enough to display the data that is most relevant in a given circumstance.

The Semantic Web, on the other hand, is about having data as well as documents on the Web

so that machines can process, transform, assemble, and even act on the data in useful ways.

The semantic web is comprised of a philosophy, 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 have 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.


http://en.wikipedia.org/wiki/Working_groups



http://en.wikipedia.org/wiki/Resource_Description_Framework



http://en.wikipedia.org/wiki/Notation_3

http://en.wikipedia.org/wiki/Turtle_(syntax)

http://en.wikipedia.org/w/index.php?title=N-Triples&action=edit

http://en.wikipedia.org/wiki/RDF_Schema


http://en.wikipedia.org/wiki/Web_Ontology_Language


http://en.wikipedia.org/wiki/Description_logic


http://en.wikipedia.org/wiki/Concept


http://en.wikipedia.org/wiki/Terminology

http://en.wikipedia.org/wiki/Causality


http://en.wikipedia.org/wiki/Knowledge_domain




http://en.wikipedia.org/wiki/Notation_3

http://en.wikipedia.org/wiki/Turtle_(syntax)

http://en.wikipedia.org/w/index.php?title=N-Triples&action=edit






http://en.wikipedia.org/wiki/Terminology







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2.VISION OF THE SEMANTIC WEB:

The vision of the Semantic Web is a “web of data” that not only harnesses the

seemingly endless amount of data on the World Wide Web, but also connects that

information with data in relational databases and other non-interoperable information

repositories, for example, EDI systems. Considering that relational databases house the

majority of enterprise data today, the ability of Semantic Web technologies to access and

process it alongside other data from Web sites, other databases, XML documents, and other

systems increases the amount of useful data available exponentially. In addition, relational

databases already include a great deal of semantic information. Databases are organized in

tables and columns based on the relationships between the data they house, and theseRelationships reveal the meaning (the semantics) of the data. Data integration applications

offer the potential for connecting disparate sources, but they require one-to-one mappings

between elements in each different data repository. The Semantic Web, however, allows a

machine to connect to any other machine and exchange and process data efficiently based on

built-in, universally available semantic information that describes each resource. In effect, the

Semantic Web will allow us to access all the information listed above as one huge database.

Semantics ?

When I searched the dictionary for the meaning of the word semantics I discovered

that it is an adjective and it meaning is as follows

1. Of or relating to meaning, especially meaning in language.

2. Of, relating to, or according to the science of semantics.

So Semantics is an adjective which gives the meaning of something. Semantics is

actually related to syntax. In most languages syntax is how you say something. Semantics isthe meaning behind what you have said. Let’s take a phrase “I Love technology” as an

example. The syntax is all the letters, words, punctuation marks in the sentence. The

semantics is what the sentence actually mean. In this case that means you enjoy learning

about and using new technology. Now if we would change the sentence using different

symbol for the word love we are changing the sentence however note that the semantics of

the sentence still the same. When you write “I ♥ technology” it still means that you enjoy

learning and using new technology.




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The Internet

When we talk about the syntax and semantics what we really talking about is

communication when you want to communicate with somebody else you use your voice to do

so. The internet created a standard way to communicate with each other. In other words itgave a voice to the computer so that they may talk to each other and exchange information.

However much like a parrot mimic you and sounds without understanding them. Computer

nearly mimic the human information to one another so while the internet enables computer to

talk to one another it was not designed to teach them what the information actually means.

The Web

When the web came along and created a very quick and easy way for us to retrieve

and view information. You can think web as a huge document storage and retrieval system.

When you put a website address into your browser so it sends the request to a website. The

request basically states that you would like the document located at the address that you gave.

The website retrieves the document and sends it back to your web browser. This document is

written in a language called HTML. The html language that defines syntax that computer can

understand. It tell the computer how to display the document to you so the two really needed

things that the web did is create a way to get any document on the internet and also created asyntax called html that is used to display the documents for you.

2.1 The Problem

Data that is generally hidden away in HTML files is often useful in some contexts, but

not in others. The problem with the majority of data on the web that is in this form at the

moment is that it is difficult to use on large scale, because there is no global system for

publishing data in such a way as it can be easily processed by anyone. Technically WWWmeans a set of protocols and languages driven by a strong standards approach namely URI,

HTTP, HTML, and HML.

The principles involved are the

1) Implementation and platform independence crucial and

2) World Wide Web consortium the most prominent.

Google –Market Cap: 72.45 $




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In comparison shopping also, the Market cap is 502.70$. Also in WWW who can you

trust to send you e-mail and how can we know for sure if a transaction really occurred. So

what’s the big deal. We have the internet that talks to each other we have the web that store

and retrieve any documents on the internet and the search engines which can find any of the

website that we want. The web is already pretty good how we are going to make it any better

the answer lies in semantics. ”Remember computer today just blindly retrieves and shows

information that’s the problem”. Computers don’t understand the meaning behind the

WebPages that they are showing us. While they may understand the syntax the semantics last

on them. Now if we can get computers to recognize what in a webpage they could learn want

they are interested in if they know that they can help us get what we want. They would

change passively helping us to actively helping us.

About 3,660,000 Results were returned....

2.2 A web of Things

This is what semantic web is all about it help the computer understand the meaning

behind the web page. The web of today is about documents where as semantic web is about

things. When I say things I mean anything, people, places, events, music, movies and just

about any concept that you think of. The semantic web is not only about pointing things out

to a computer but also about letting computers know how this are related to each other. There

are several pouncing technologies that are in use today that can embed semantics in a html

document too the more popular ways are called

1. Micro formats




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2. RDFa

RDFa

RDFa is based on RDF, RDF stands for Resource Description Framework. That’s the

fancy way of saying that it can describe any concept relationship or thing that exists in the

universe the idea RDF is sample and it does very easy to grasp. RDF has features that

facilitate data merging even if the underlying schemas differ, and it specifically supports the

evolution of schemas over time without requiring all the data consumers to be changed. RDF

extends the linking structure of the Web to use URIs to name the relationship between things

as well as the two ends of the link (this is usually referred to as a “triple”).

Using this simple model, it allows structured and semi-structured data to be mixed,

exposed, and shared across different applications. This linking structure forms a directed,

labeled graph, where the edges represent the named link between two resources, represented

by the graph nodes. This graph view is the easiest possible mental model for RDF and is

often used in easy-to-understand visual explanations. There are three things in RDF subjects,

predicates and objects. If you remember to your elementary school English classes this

should sound pretty familiar to you the subject, object and predicate approach how most

western languages create basic semantics. The subject refers to the thing you are describing

the predicate usually refers to an attribute of a thing that you are describing and the object is

the thing which you are referring to with the predicate.

Consider a basic example

“Avinash likes sweets”

In the above statement Avinash is the subject, likes is the predicate and sweets is the object.

Using this simple idea we can describe anything so that is basically what RDF enables us to

do.

URI :( Uniform Resource Identifier)

RDF uses URI’s to specify subjects and predicates. URI stands for Uniform ResourceIdentifier. And is how we Identify things on the web. You're probably already familiar with


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one form of URI: the URL or Uniform Resource Locator . A URL is an address that lets you

visit a webpage, such as: http://www.w3.org/Addressing/. If you break it down, you can see

that a URL tells your computer where to find a specific resource (in this case, the W3C's

Addressing website). Unlike most other forms of URIs, a URL both identifies and locates.

Contrast this with a "mid:" URI. A "mid:" URI identifies an email message, but it isn't able to

locate a copy of the message for you.

http://www.example.org/relly/long/urls/are/hard/to/type/ect/

URI can be very long and annoying the type out. This is why we have a new concept in rdfa

called curi. curi’s are a short hand ways of writing a long URI. curi is the abbreviation of

compact URI. An example of curi is foaf:name.

In this case of curi foaf expands to a much linger URL and name is appended to the URL.

You don’t need to know what URI means right now just the that the ting on the left side of

the colon expands to a long URL and the thing on the right side of the colon is added to the

end of the expanded URL.

Triples And N3 Notation

RDF and curis often come up when people talk about rdfa they are used when

discussing rdf statements. Now rdf is a concept not a syntax so we must learn how to express

rdf statements. This is where N3 notation comes in. Remember that in RDF every thing is

subject, predicate, object statement.

This statement is called triple. If we take out previous example

“Avinash like sweets”

We can express it in N3 notation likes so.

@prefix pref:http://example.org/vocubular<#Avinash> <pref:likes> <#sweets>.

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The prefix line lets us know what the short hand is for all the curies in the documents in other

words it defines what the name spaces are moving to the next line we found the actual triple

the first item is subject and is enclosed in angle brackets to specify. The second item is the

predicate which is also a URI,the third Item is the object is also a URI, finally there is a

period at the end of the triple to end the statement. There can be many triples associated with

a particular subject the more triples there are the more we know about the subject. If we look

closely at this example you will also notice that the predicate points to something called

vocabulary.

The foaf vocabulary

Just like N3 is syntax used to describe RDF to humans, Rdfa is a syntax used to

describe RDF to computers. Neither N3 nor Rdfa have any inherit meaning until you pair

them with vocabulary. The vocabulary defines what the triple actually means a vocabulary

allows a computer to understand when you are talking about a specific concept. One such

vocabulary that is quite popular on the semantic web is friend of a friend vocabulary also

known as foaf. Foaf contains several concepts that are useful for identifying people and

representing relationship those people foaf will be the first vocabulary we use in this paper.

2.3 Creating a Triple

Using the foaf vocabulary it is easy to start describing someone on any web page,all

you need is URI that talks about a person and a proper predicate to describe that person. Let’s

use Avinash as a person let the browser know what’s his full name is. First we will need to

specify that we are going to use the foaf vocabulary in our xhtml webpage. We do this by

using an xmlns as an attribute, we will also need use two rdfa attributes about and property

the first one is the about attribute and is used to set the subject and the second one is the

property attribute and is used to set the predicate. Finally we set his name using the text that

will appear on the webpage this is really helpful because when somebody changes his name

on the page perhaps to add middle initial they won’t have to change anything else for the

machine readable part of the data to be updated. Both the human readable and the machine

readable rest comes from the exact same location on the page ensuring that both human and

machine have most update data.

<body xmlns: foaf= http://xmlns.com/foaf/0.1/>

 Avinash Gupta




http://xmlns.com/foaf/0.1/

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</body>

Looking back over the example we define the namespace at the top of the document

we then set the subject using the about attribute this followed by starting the predicate using a

curi which uses the namespace at the top of the document finally we specify the object by

rapping in the span element.

Any browser reading this webpage will know the Avinash full name.

Types and Relationships

Now that the browser knows that there is something with the name on the page we

need to let it know that Avinash is also a person to do this we can use the instance of

attribute. Instance of is used to specify a type which is very special sort of attribute on a

subject. A type specifies exactly what class of thing the subject falls into. In this case Avinash

is a person foaf has a class called person, so we apply using the instance of attribute. Now the

browser knows that Avinash is a person. Let’s go one step further and create a relationship.




AvinashGupta



</body>

by stating that Avinash knows someone else on the page named Rahul, to do this we setup

another person on the page named Rahul in the same way we setup Avinash.

SEMANTIC WEB



RahulKanna



Now all that is left to link them together to do this we use the combination of the rel attribute

and the resource attribute there is a vocabulary term that foaf defines called knows to state

that one resource known another resource we can use the foaf known as the predicate and link

the resource using rel.


 AvinashGupta



 RahulKanna



Avinash is friend with Rahul



</body>

In this case we use recourse to target object for the rel , Rahul could just easily as

have been mentioned on the another website and their remote website URL could have been

used instead of the local URL.

2.4 Building the Semantic Web

This is how the Semantic web is build. Triple by triple, triple linked to other triples

and which they linked to more triples. These links go between pages, blogs, sites and

countries. The more triples that they are in the web the more compute would be able to

understand our world. This means that they will get really good helping us finding news,

music, people places and many more, that what you are interested in.



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Figure 1 Building of semantic Web




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3.Components

Figure2 Required componetns

3.1 The Semantic Web Stack

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:


http://en.wikipedia.org/wiki/File:Semantic-web-stack.png

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XML provides an elemental syntax for content structure within documents, yet

associates no semantics with the meaning of the content contained within. XML is not at

present a necessary component of Semantic Web technologies in most cases, as

alternative syntaxes exists, such as Turtle. Turtle is a de facto standard, but has not been

through a formal standardization process.

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 extends RDF and 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. discontinues), cardinality (e.g. "exactly one"), equality,

richer typing of properties and 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:

Rule Interchange Format (RIF) as the Rule Layer of the Semantic Web Stack

Not yet fully realized layers include:

Unifying Logic and Proof layers are undergoing active research.

The intent is to enhance the usability and usefulness of the Web and its

interconnected resources through:

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



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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)




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5.Challenges

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 deliver on the promise of the Semantic Web.

Vastness: The World Wide Web contains at least 24 billion pages as of this writing(June 13, 2010). The SNOMED CT medical terminology ontology contains 370,000 class

names, and existing technology has not yet been able to eliminate all semantically

duplicated terms. Any automated reasoning system will have to deal with truly huge

inputs.

Vagueness: These are imprecise concepts like "young" or "tall". This arises from the

vagueness of user queries, of concepts represented by content providers, of matching

query terms to provider terms and of trying to combine different knowledge bases with

overlapping but subtly different concepts. Fuzzy logic is the most common technique for

dealing with vagueness.

Uncertainty: These are precise concepts with uncertain values. For example, a patient

might present a set of symptoms which correspond to a number of different distinct

diagnoses each with a different probability. Probabilistic reasoning techniques are

generally employed to address uncertainty.

Inconsistency: These are logical contradictions which will inevitably arise during the

development of large ontologies, and when ontologies from separate sources are

combined. Deductive reasoning fails catastrophically when faced with inconsistency,

because "anything follows from a contradiction". Defensible reasoning and Para

consistent reasoning are two techniques which can be employed to deal with

inconsistency.

Deceit: This is when the producer of the information is intentionally misleading the

consumer of the information. Cryptography techniques are currently utilized to alleviate

this threat.




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Standardization:

Integration and interoperability is always the concern of any open system. This is especially

the concern of the Semantic Web, an open system that has to be scalable at the Internet level.

Currently, a number of ontology representation languages have been proposed and various

ontology library systems have been built. The question is what would be the standardized

ontology representation language. Each of them seems to have its advantages and

disadvantages, and has its proponents and opponents. This might be a feature of our human

being society: each of us has his/her preference. Since the Semantic Web is still at its early

stage, it might be too early to enforce any standardization. Each representation language can

grow on its own and the one or a few ones who win will become the de facto standards. XML

might serve as the meta-languages of these representations to facilitate future interoperation

and integration.

5.2 Formal semantics of the Semantic Web languages

The functional architecture of the Semantic Web has three layers: the metadata layer, the

schema layer and the logical layer. Currently, the RDF (Resource Description Framework,) is

believed to be the most popular data model for the metadata layer. Although it is believed

that the RDF data model is enough for defining and using metadata, the semantics of

reification (statement about statement) is yet to be defined. RDFS (RDF Schema) extends

RDF and is currently a popular schema layer language. It has been recognized that RDFS

lacks a formal semantics and one proposal is to define metamodeling architecture for RDFS

similar to the one for UML (Universal Modelling Language), and hence defines a formal

semantics. This approach, although formal, is complicated and not intuitive. Although RDFS

has been blamed for its semantic confusion and some apparent paradox, it has not been

shown that a formal semantics is impossible. To smooth the way of developing the Semantic

Web, we believe that the semantics of RDFS need to be resolved: either a formal semantics is

defined for it, or the problem of RDFS is pinned down so that the semantic issue can be

resolved.

Proof and trust

As an open and distributed system, the Semantic Web bears the spirit that "anybody can say

anything on anybody". People all over the world might assert some statements which can




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possibly conflict. Hence, one needs to make sure that the original source does make a

particular statement (proof) and that source is trustworthy (trust).

• Proof. Digital signatures will play an important role in proof. The source has to sign

the statement he makes so that agents can check if information really comes from the

source it claims to be. In addition, other security technologies like encryption and

access control can be used to ensure confidentiality of information.

• Trust. Everybody should be able to define a trust model for himself, i.e., one can

define how much trust he would put on each source on the Semantic Web. Since it is

unrealistic to define the extent of trust for each source, a mechanism is necessary to

derive the degree of trust for each new source. One solution is the notion of "web of

trust": when one trust a source A, he also trusts all other sources that are trusted by

source A, but to a lower extent, in this way, a huge and hierarchical network is created

which facilitates agents infer information based on their trusted knowledge.

Currently, the notion of proof and trust has yet to be formalized, and a theory that integrates

them into inference engines of the Semantic Web is yet to be developed. However, these

technologies are very important and are the foundation of building real commercial

applications (e.g., B2B and B2C systems).




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6.The Possibilities

Things get really exciting when we start exploring to explore the possibilities of the

semantic web. Once your computer understand a person a place and a event days, it can help

you interacting with those things 6 for example if a birthday party is marked up as an event

With a date and a place you can tell your computer to save the date in your calendar. Another

example is in the world of music blogs, Music blogs usually list songs and album reviews on

their front page. If the blog marked up the song in the artist semantic web technology you can

tell page to search the internet for other albums by the same artist. Search engines would also

become a great deal more accurate than they are today. When you search you can search for

any person, place or any particular song. Search engine could then refer to you a website with

a far more accuracy, because it wouldn’t have just depend on keyword in WebPages any

more it could also depends on the semantics on the webpage so that semantic web holds a

great deal of proms and making our life’s easier by helping computers help us get what you

want.

6.1 Web-services

Among the most important web resources on the Semantic Web are those so called web-

services. Here, web-services refers to "web sites that do not merely provide static information

but allow one to effect some action or change in the world". The Semantic Web will enable

users to locate, select, employ, compose, and monitor web-services automatically

• Automatic web-service discovery. Since semantic descriptions of web-services are

registered with some public registries, intelligent mobile agents might migrate from

one service registry to another to find desirable web-services as specified by a user.

There has been some work in agent-assisted browsing of the web. For example,

Letizia is a user interface agent that assists a user browsing the World Wide Web

based on the user's profile. Letizia can learn the profile of a user based on the user'sbrowsing history. This idea can be applied to web-service discovery as well. For




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example, a server might provide web-services at different levels or with different

values towards different users, and an agent might find a web-service based on the

user's profile.

• Automatic web-service invocation. Currently most web-services require human's

intervention during their execution. For example, to buy a book

at http://www.amazon.com, the website requires a user to fill out a form, and then

click a button to execute the service. Usually, multiple interactions between a user and

a web-service are needed to complete the execution of that web-service . The

capability of automatic web-service invocation implies that a software agent will be

able to perform these invocations on behalf of a user, who only needs to tell the agent

to "go to Amazon and buy a book titled The Semantic Web with no more than $50",

and the agent will interact with the web-service with appropriate input data via

computer interpretable APIs.

• Automatic web-service composition and interoperation. Given a library of web-

services and an objective, one might be able to automatically select and compose a

new web-service to achieve the new objective. The prerequisites and consequences of

individual web-services need to be described in a formal way, and the technology for

automatic workflow generation) might be used to generate web-services

automatically.

• Automatic web-service execution monitoring. For long-running complex web-

services, it is desirable to be able to track and query the status of the execution of each

service as well as its components.

The industry has already seen the potential market enabled by web-services and some efforts

have been put to the development of standards for electronic commerce, in particular for the

description of web-services. For example, Microsoft, IBM and Ariba proposed UDDI(Universal Description, Discovery, and Integration, 2000) to describe a standard for an online

registry, and the publishing and dynamic discovery of web-services offered by businesses;

Microsoft and IBM proposed WSDL (Web Service Definition Language) as an XML

language to describe interfaces to web-services registered with a UDDI database; the DAML

Services Coalition proposed DAML-S (Darpa Agent Markup Language - Service, 2001) as

an ontology to describe web-services; and OASIS and the United Nations developed ebXML

(Electronic Business XML Initiative, 2000) to describe business interactions from a workflow

perspective. A number of communication protocols have been developed for the invocation




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of web-services: Remote Procedure Call (Birrell & Nelson, 1984) is client/server

infrastructure that allows a client component of an application to employ a function call to

access a server on a remote system. The CGI (Common Gateway Interface) mechanism is a

standard for external gateway programs to interface with information servers such as HTTP

servers. CORBA (Common Object Request Broker Architecture) uses a registry to store

interfaces of distributed objects so that a client can invoke a method of a remote server object

without knowing its location, programming language, operating system and other system

aspects that are not part of the object's interface. SOAP (Simple Object Access Protocol) is a

protocol for the exchange of information in a distributed environment, in particular, the Web.

Using SOAP, one can describe the content of a message and the way to process it, define

application-dependent data types, and represent remote procedure calls and responses. SOAP

can potentially be used together with a variety of other protocols. Currently, its binding with

HTTP is supported. Java RMI (Java Remote Method Invocation) enables programmers to

develop Java applications in which a client can invoke a method of a remote Java Object. The

ACL (Agent Communication Language) developed by SRI International in the framework of

OAA (Open Agent Architecture) allows one to define and publish the capabilities of agents

so that a request can be matched with a server agent by the facilitators (brokers)

6.2 Agent-based distributed computing paradigm

The Semantic Web will use ontologies to describe various web resources; hence, knowledge

on the Web will be represented in a structured, logical, and semantic way. This will change

the way that agents navigate, harvest and utilize information on the Web. On one hand, the

Semantic Web is a web of distributed knowledge bases, and agents can read and reason about

published knowledge with the guidance of ontologies. On the other hand, the Semantic Web

is a collection of web-services described by ontologies like DAML-S (Darpa Agent Markup

Language - Services)) and this will facilitate dynamic matchmaking among heterogeneous

agents: service provider agents can advertise their capabilities to middle agents; middle

agents store these advertisements; a service requester agent can ask a middle agent whether it

knows of some provider agents with desired capabilities; and the middle agent matches the

request against the stored advertisements and returns the result, a subset of the stored

advertisements.

When agents are equipped with intelligence and mobility, the conventional client/server

computing paradigm might be replaced by an agent-based distributed computing paradigm, in




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which agents can migrate from one site to another, carrying their codes, data, running states

(including internal beliefs), and intelligence (specified by the users), and fulfil their missions

autonomously and intelligently. Many researchers have speculated that mobile agents are

inevitable for an open and distributed environment like the Semantic Web and have seen the

advantages of this new computing paradigm including:

• It reduces the network load.

• It overcomes the network latency.

• It supports the encapsulation of protocols.

• Agents execute asynchronously and autonomously.

• Agents adapt dynamically.

• Agents are naturally heterogeneous.

• Agents are robust and fault-tolerant.

A number of mobile agent systems have been developed .

6.3 Semantics-based web search engines

Search engines are among the most useful resources on the Web and currently there are two

types of search engines:

• Large-scale robot-based search engines. These systems rely on robots to retrieve Web

pages and store them in a centralized database. The advantage of this mechanism is

that it increases recall (the proportion of relevant documents that are actually

retrieved, since robots can almost retrieve all web pages on the Web, while the

disadvantage is the precision (the proportion of retrieved documents that are actually

relevant) of the search result might be low.

• Small-scale reviewer-based search engines. A category hierarchy is created and each

category is described by a set of keywords. Reviewers will review each web page

(submitted by web page authors) and associate it with appropriate categories. The

advantage is that precision is increased, but the disadvantage is that recall might be

low since it is impossible to review and include every single relevant web page on the

Web.

Both types of search engines are based on keywords, and hence are subject to the two well-

known linguistic phenomena that strongly degrade a query's precision and




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recall: polysemy (one word might have several meanings) and synonymy (several terms, i.e.

words or phrases, might designate the same concept). A number of stemming algorithms)

have been developed to address the synonymy issue including suffice removal, strict

truncation of character strings, word segmentation, letter bigrams and linguistic morphology.

The idea is that different derivations of a word are similar to each other in their forms (e.g.

they have the same prefix) and can be traced back to the same root (stem) using these

stemming methods. However, these methods are subject to the following stemming errors:

words with different meaning might be reduced to the same root. For example,

words general, generous, generation, and generic might be reduced to the same root. On the

other hand, different words with the same meaning cannot be reduced to the same root. For

example, an automobile and a car. The situation becomes worse for the large-scale robot-

based search engines. Only limited semantics can be derived from

the lexical or syntactic content of the web pages.

Several systems have been built to overcome these problems based on the idea of annotating

Web pages with special HTML tags to represent semantics, including SHOE (Simple HTML

Ontology Extensions) system, GDA system. However the limitation of these systems is that

they can only process web pages that are annotated with these HTML tags, and so far there is

no agreement upon a universally acceptable set of HTML tags.

XML is a promising technique since it keeps content, structure, and representation apart and

is a much more adequate means for knowledge representation. However, XML can represent

only some semantic properties through its syntactic structure. XML queries need to be aware

of this syntactic structure. With the advent of the Semantic Web, resources on the Web will

be represented semantically in ontologies. Semantics-based web search engines can be built

in which each query is executed within the context of some ontology. The guidance from

ontologies will increase recall and precision of the search result. For example, one might pose

a query "return all the reviewers for book 'The Semantic Web: an Introduction'" to a

semantics-based web search engine, then the engine will return only reviewers for this book

instead of returning web pages that contain keyword "reviewer" and/or term "The Semantic

Web: an Introduction". For another example, if one pose query "return all the chairs", with

the guidance of a furniture ontology, only those furniture chairs are returned; and with the

guidance of a person ontology, only people who are chairs of some organizations will be

returned. In contrast, Keyword-based search engines will return web sites that contain

keyword "chairs", including chairs that refer to furniture and chairs that refer to people. It is




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worth mentioning that some systems that use ontologies to enhance web search engines have

been developed. Since ontologies are built on a domain basis, web search engines might be

also built on a domain basis, and hence metasearch engines, which interface with multiple

remote search engines and select and rank remote search engines intelligently, might be very

useful.

6.4 Semantics-based digital libraries

Digital multimedia data in various formats has increased tremendously in recent years on the

Internet. With the development of digital photography, more and more people are able to

store their personal photographs on their PCs. Sharing of picture albums and home videos on

the Internet become more and more popular. Furthermore, many organizations have largeimage and video collections in digital format available for online access. Film producers want

to advertise movies through interactive preview clips. Travel agencies are interested in digital

achieves of holiday resorts photographs. Hospitals would like to build medical image

databases. These emerging applications for multimedia digital libraries require

interdisciplinary research in the areas of image processing, computer vision, information

retrieval and database management. Semantics-based retrieval of multimedia digital content

is important for efficient use of the multimedia data repositories. Traditional content-based

multimedia retrieval techniques describe images/videos based on low level features (such as

colour, texture, and shape) and support retrieval based on these features. However, human

typically does not view images/videos in terms of low-level features. A semantics-based

query capability is highly desirable. For example, one might want to formulate a query like

"return all the scenes in clip 1 in which a boy is riding a bicycles". Retrieving images/videos

based on low-level features cannot provide satisfactory results. Effective and precise

multimedia retrieval by semantics remains an open and challenging problem.

Recently, ontologies begin to be used in the context of digital libraries. For example,

ScholOnto is an ontology-based digital library that supports scholarly interpretation and

discourse, and ARION, another ontology-based digital library that supports search and

navigation of geospatial data sets and environmental applications.

We believe that various digital libraries will become another major web resource of the

Semantic Web. The challenges here are: (1) The development of efficient and effective

classification and indexing mechanism for each type of digital library, and (2) The semantic




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interoperability between digital libraries of similar types and between a digital library and the

Semantic Web.

7.Semantic Web Advantages

Predictions and Actions:

Subsequent practitioners of Semantic Web have also been making possible of their

predictions and actions in a variety of ways. For instance, with the application of Semantic

Web technologies, it is possible to automate operations, say, from completing all that you

need for a travel to updating of your personal records. Semantic Web then can be defined as a

web of information on the Internet and Intranet that contains characteristics of annotation

which enables accessing of precise information that you need.

Semantic Web in action has been conferring advantages in an ongoing basis and in initial

stages had proved beneficial in sophisticated operations as logistics planning in military

operations. The US military was the first one to adopt it; however it has been extending such

benefits to other applications also some of which are presented below:

Health Care and Life Sciences:

In Health Care and Life Sciences its application is advantageous because these disciplines

have to deal with data from multiple sources, which have multiple applications and there is

no completeness in such data.

Engineering Analysis:

Semantic Web could be applied to engineering analysis by availing innumerable advantages

it offers. Engineering analysis involves handling complicated data sets in countless formats.

Semantic Web in particular confers the following advantages to engineering analysis.

• The data would not be lost in the servers

• There is no need for an expensive Product Date Management (PDM) system




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• The data could be tailored to return in a uniform manner across the companies

• A variety of checklist analysis could be conducted simultaneously

Data Warehousing:

In data warehousing it has specific functional utilities. There is no need for a data base

schema; this means you can dispense away the necessity to make a decision about the

structure and recording of data; in addition data can be distributed over the Web, because

Semantic Web is neutral to data security.

It has cost advantages too for business operations, for the businesses can precisely define the

processes suited for them and the system would do exactly what that business specifies and

nothing more and nothing less. This makes technology affordable for small businesses also.

Specific Semantic Web Technology:

Semantic Web has developed specific Semantic Web Technologies that could be

implemented free of cost that could result in huge savings in the way the Web functions. An

example of this is SPARQL, a query language

It would however be erroneous to assume that Semantic Web is something that has descended

from nowhere to usher in a rethinking in everything. One may be tempted to use such terms

as that a revolutionary mind set would be needed to its application etc. or it represents a

paradigm shift which are all not correct and would only confuse and mask the real advantages

it is offering. It is neither a total replacement nor would it substitute all that has come before

it, which would and continue to exist. No doubt, there could be changes, but, these changes

would build and bridge the gap by leveraging the existing assets rather than replacing them.




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8.Conclusion

In this paper, we reported a survey of recent research on the Semantic Web. In particular, we

presented the opportunities that this new revolution will bring to us, and the challenges that

we are facing during the development of the Semantic Web. We hope that this paper will

shed some light on the direction of future work.

The Semantic Web is still a vision. We believe that the Web will grow towards this vision in

a way like the development of the real world: Semantic Web communities will appear and

grow first, and then the interaction and interoperation among different communities will

finally interweave them into the Semantic Web.




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References:

http://en.wikipedia.org/wiki/Semantic_Web

http://orange.eserver.org/issues/3-2/emonds-banfield.html

http://www.semanticfocus.com/blog/entry/title/introduction-to-semantic-web-vision-and-technologies-part-4-protege-101-screencast/

http://en.wikipedia.org/wiki/Semantic_Web_Stack

http://anale.feaa.uaic.ro/anale/resurse/info5svarlan.pdf











