Web 3.0 or The Semantic Web

By: Konrad SitCCT355

November 21st 2011

Web 1.0• Mostly flat information• Some databases but content very

functional• Little engagement or interactivity

Web 1.0• Web 1.0 design elements• Some typical design elements of a Web 1.0 site

include:• 1. Static pages instead of dynamic user-generated

content.• 2. The use of framesets.• 3. HTML forms sent via email. A user would fill in a

form, and upon clicking submit their email client would attempt to send an email containing the form's details.

Web 2.0• Greater interactivity• Growth of social media /social networking• Online communities• created / social capital

Web 2.0• Web 2.0

Web 3.0• Joining up of information• Data portability• Browsers and searchengines become more‘intelligent’

Differences

• Web 1.0 works but is clunky, not very efficient, technically limited

Differences• Web 2.0 is smoother, looks better, but

still lacks cohesion possibilities

• Web 3.0 has a greater scope of exploration, limitless potential and is smart

So how do they match up• Web 3.0 is the integration of data on the

internet

• (Web 1.0) - Data is online + Super Apps• (Web 2.0) - Sites share via API’s and social

networks • (Web 3.0) – Plugs into this massive amount of

data we have made available on the web

• We need to view the internet as a platform

Barriers to web 3.0• Building massively scalable data centers

that are secure, reliable, and highly available is very complex and vary expensive.

• Traditional client-server software development is still a painful and complex process

• Deployment of applications is still difficult and the cost of maintenance is expensive

Web 3.0• Web 3.0 can think for itself• Connect big collections of databases

on demand to allow for sorting of the vast amount of data on the internet

Web 3.0• Agreements are made on the structure of

data and the way data is described• where the data is located is irrelevant• Linking data is the power of web 3.0• Some believe that web 3.0 will be search

engine advancement just as web 2.0 was social network advancement

Web 3.0 as a platform• We will see data being integrated and applying it

into innovative ways that were never possible before

• Imagine The new shopping experience• Imagine The new travel experience• Major web sites will be transformed into web

services• Major web sites will expose information to the

world.

Web 3.0 With Global Development

• All you need to create an application is an idea, others can then add their talent

• Every developer around the world can access the same powerful cloud infrastructures

• Because code lives in the cloud, global talent pools can contribute to it

• Because it runs in the cloud, a truly global market can subscribe to it as a service

Web 3.0 the Semantic Web• The Semantic Web - coined by Tim Berners-Lee,

the man who invented the (first) World Wide Web• A place where machines can read Web pages

much as we humans read them• A place where search engines and software

agents can better troll the Net and find what we're looking for

• Web as a universal medium for data, information, and knowledge exchange

Some Challenges of Web 3.0

• Vastness: The World Wide Web contains at least 48 billion pages (as of August 2, 2009). 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.

Continued…• 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 .Deductive reasoning fails catastrophically when faced with inconsistency, because "anything follows from a contradiction“.

The End

Any Questions??