IT trends-latest/recent trends in information technology: Semantic Web

What is the Semantic Web?

• The Semantic Web is a web that is able to describe things in a way that computers can understand.

The Beatles was a popular band from Liverpool.

John Lennon was a member of the Beatles.

"Hey Jude" was recorded by the Beatles.

• Sentences like the ones above can be understood by people. But how can they be understood by computers?

• Statements are built with syntax rules. The syntax of a language defines the rules for building the language statements. But how can syntax become semantic?

• This is what the Semantic Web is all about. Describing things in a way that computers applications can understand it.

• 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)

• The Semantic Web is 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.

Purpose

• 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.

• In particular, the semantic web is expected to revolutionize scientific publishing, such as real-time publishing and sharing of experimental data on the Internet.

The Resource Description Framework

• The RDF (Resource Description Framework) is a language for describing information and resources on the web.

• Putting information into RDF files, makes it possible for computer programs ("web spiders") to search, discover, pick up, collect, analyze and process information from the web.

• The Semantic Web uses RDF to describe web resources.

How can it be used?

• If information about music, cars, tickets, etc. were stored in RDF files, intelligent web applications could collect information from many different sources, combine information, and present it to users in a meaningful way.

Information like this:

Car prices from different resellers
Information about medicines
Plane schedules
Spare parts for the industry
Information about books (price, pages, editor, year)
Dates of events
Computer updates

Can it be understood?

• The Semantic Web is not a very fast growing technology.

• One of the reasons for that is the learning curve. RDF was developed by people with academic background in logic and artificial intelligence. For traditional developers it is not very easy to understand.

• One fast growing language for building semantic web applications is RSS.

Simple semantic web application:

Buying and selling used cars

• Suppose a semantic web system was built to administer the selling and buying of used cars over the Internet.

• The system would contain two main applications:

One for people who wanted to buy a car

One for people who wanted to put up a car for sale

• Let's call the Internet applications for IBA (I Buy Application), and ISA (I Sell Application).

IBA - The I Buy Application

• People who want to buy a car could use an IBA application much like this:

• In a "real live" application you would be asked to identify yourself the first time you used it. Your ID would be stored in an RDF file. Your ID would identify you as a person with name, address, email, and ID number.

• When you submitted the query, the application would return a list of cars for sale, and the list could be drilled down and sorted by year, price, location and availability. This information would be returned from a web spider continuously searching the web for RDF files.

ISA - The I Sell Application

• People who want to sell a car could use an ISA application much like this:

• When you submitted the form, the application would ask you for more information and store your ID and the information in an RDF file made available to the web.

• The RDF file would contain information like:

Your ID: Name, address, email, ID number.
Your selling item: type, model, picture, price, description.

Behind the scenes

• Behind the scenes, the "ISA" application creates an RDF file with a lot of RDF pointers.

• It creates an RDF pointer to a file with information about you, an RDF pointer to information about Volvo and Volvo models, an RDF pointer to Volvo dealers and resellers, about parts, about prices, and much more.

• An RDF pointer is a pointer (actually an URL) to information about things (like a knowledge database).

• The beauty about this is that you don't have to describe yourself, or the car model. The RDF application will sort it out for you.

Challenges

• Vastness: The World Wide Web contains at least 48 billion pages as of this writing (August 2, 2009). 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". Defeasible reasoning and paraconsistent 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 ameliorate this threat.

Semantic Web Agents

• The semantic web will not be searchable in free text. To search (or access) the semantic web, we will need some software to help us.

• To use the semantic web, we will need "Semantic Web Agents" or "Semantic Web Services". These "Agents" or "Services" will help us to find what we are looking for on the semantic web.

On the semantic web, we might want to look for information about: