We have all been used to the term “Web 2.0”. It has been a great marketing brand, initially created by O’Reilly media group to group and highlights key technologies changing the user habits and usage of internet in the world. There has been a quantum increase in the number of users on the internet leading to huge amount of social, business, education as well as governance related functions being exposed through the internet.
Depending on the wide range of user patterns over the internet, wide ranges of innovative solutions were released to the user communities. Contrary to the reaction received by the initial “Internet Bubble”, these innovative solutions were well received by the user community and had converted these initial investments into multi-billion dollar industry.
Some of the common usage patterns or which Web 2.0 provides generic solutions is:
· Social Networking
· Blogging
· Personalization / Aggregation
· Filtering and Tracking
· Collaboration amongst communities
· Office online
· Content sharing
· Relevant Search
· Notifications
· Learning
Some of the popular terms which all of us go through infinite times in a day now are:
| Blogs | Simple webpage consisting of brief paragraphs of opinion, information, personal diary entries, or links, called posts, arranged chronologically with the most recent first, in the style of an online journal. Eg. http://wordpress.org/ http://www.blogger.com/ |
| Wiki’s | Collaborative tool that facilitates the production of a group work. Eg. http://meta.wikimedia.org/wiki/MediaWiki * http://www.socialtext.com/products/overview http://www.twiki.org/ |
| Tag’s / Bookmarking | A tag is a keyword that is added to a digital object (e.g. a website, picture or video clip) to describe it, but not as part of a formal classification system. Social bookmarking systems allow users to create lists of ‘bookmarks’ or ‘favourites’, to store these centrally on a remote service (rather than within the client browser) and to share them with other users of the system. Eg. http://www.digg.com/ |
| Folksonomy | Folksonomy is collaborative tagging and method of collaboratively creating and managing tags to annotate and categorize content. In it metadata is generated not only by experts but also by creators and consumers of the content. |
| Multimedia sharing | Biggest revolution in Web 2.0 has been triggered by the power of content sharing where users can share pictures and multimedia content to achieve any personal as well as business objective. Eg. http://www.youtube.com/ |
| Podcasting | Digital media files that can be downloaded from the internet and are used to share talks, lectures, and interviews. Eg. Apple ITunes, Microsoft Zune. |
| RSS Feeds | RSS is a family of formats which allow users to find out about updates to the content of RSS-enabled websites, blogs or podcasts without actually having to go and visit the site. Instead, information from the website is collected within a feed (which uses the RSS format) and ‘piped’ to the user in a process known as syndication. |
| Mashups | A mashup is a web page or application that combines data or functionality from two or more external sources to create a new service. The term mashup implies easy, fast integration, frequently using open APIs and data sources to produce results that were not the original reason for producing the raw source data. |
| Widgets | A web widget is a portable chunk of code that can be installed and executed within any separate HTML-based web page by an end user without requiring additional compilation. It is a capability using which we can expose/integrate an application or service to various available web-sites. |
There were obvious reasons why this paradigm was so popular and successful amongst the user:
1. Patterns identified were based on the actual usage and behavior.
2. Most of the solutions were open source which triggered innovative ideas, solutions and participation from the user community.
3. It was for the user community.
1.1.1. Technologies behind Web 2.0
Web 2.0 paradigm was widely successful in leveraging both internal and external synergies in the market place. Organizations were able to tie up their content, knowledge, information, people and processes better with Web 2.0. In the same way many new organizations have come out with commercial offerings with Web 2.0 paradigm redefining channels to deliver service and value to their customers.
All this has happened mainly due to the wide involvement of Open Source Paradigm. Open source has given Web 2.0 that agility which was not possible through the product companies. Wide acceptability against a very little investment is only possible with open source software due to community wide collaboration.
Key Standards and technologies, which were mainly sourced by the open source world and which powered the implementation of Web 2.0 are:
| Standards | Technologies |
| RSS | XML |
| RDF | Ajax |
| ATOM | DOJO |
| SOAP / REST | Flex |
| | Silverlight |
Having discussed Web 2.0 paradigm it becomes interesting to define the expectations out from Web 3.0, the next version of web. Though different flavors of Web 2.0 were launched i.e. Government 2.0, Enterprise 2.0 etc. the basic drawback which was identified in the model was its “static” nature. Web 2.0 was successful in standardizing and integrating the services provided over the Web, it lacks in defining a framework for semantic use of these services for a logical need. For example if we are looking for a house on rent and we have certain feature list to look for, very few individual web sites offer such metadata to be used for refinement of results. Over and above this, the metadata definition is not standardized in the current set of services being offered. Currently, a “Search” is mostly based on the keyword match with a basic sense of relevance and priority built into it.
So users need an element of intelligence or a layer to provide semantics as a placeholder for that intelligence, in the next version of web. This layer will be abstract and dynamic in nature with elements of artificial intelligence built into it. In simpler terms Web 3.0 can be defined as:
“It will not be a separate web but an extension of current one, in which information is given well defined meaning, better enabling computers and people to work in cooperation” Tim Berners-Lee2001
1.2.1. What it will take
In the introduction of Web 3.0 we have defined few terms which will become the basis of this new paradigm i.e.:
· Metadata
· Abstract and dynamic nature
· Artificial Intelligence.
In this section we will define how these elements are being addressed by the industry to fulfill the paradigm of Web 3.0.
Metadata
Metadata in layman’s term is data about data. In the same way on the web to make the available services and infrastructure to participate semantic outcome there will be a need to capture the data about the services in a standardized form. Resource Description format (RDF) is a metadata data model used for defining the data about the information available across World Wide Web. It is similar to classical modeling approaches such as E-R or OO approach based on subject-predicate-object expressions for e.g. “http://www.example.org/index.html has a creator whose value is John Smith”. In this statement subject is the web page “http://www.example.org/index.html” predicate is “creator” and the object is “John smith”.
Some more details about the example mentioned above can be represented in RDF as shown in the diagram above. XML representation of the diagram is as follows:
<?xml version="1.0"?> <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:exterms="http://www.example.org/terms/"> <rdf:Description rdf:about="http://www.example.org/index.html"><exterms:creation-date>August 16, 1999</exterms:creation-date>
</rdf:Description> </rdf:RDF>As we have seen in the example above RDF is mostly used to represent data. It uses the URI references to provide a hierarchal structure to the data.
While defining data and to build generic representation of data around us we definitely will need capabilities to define “type” of data or in OO terms “class” to characterize data. This will help us in building the vocabulary to represent data and information around us more structurally. RDF vocabulary description language also known as RDF-Schema, provides facilities to describe classes and their properties in RDF. RDF-Schema provides “Type” semantic to RDF. An example taken for RDF primer explains the RDF-Schema as shown below.
<?xml version="1.0"?><!DOCTYPE rdf:RDF [<!ENTITY xsd "http://www.w3.org/2001/XMLSchema#">]><rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#" xml:base="http://example.org/schemas/vehicles"> <rdf:Description rdf:ID="MotorVehicle"> <rdf:type rdf:resource="http://www.w3.org/2000/01/rdf-schema#Class"/></rdf:Description> <rdf:Description rdf:ID="PassengerVehicle"> <rdf:type rdf:resource="http://www.w3.org/2000/01/rdf-schema#Class"/> <rdfs:subClassOf rdf:resource="#MotorVehicle"/></rdf:Description> <rdf:Description rdf:ID="Truck"> <rdf:type rdf:resource="http://www.w3.org/2000/01/rdf-schema#Class"/> <rdfs:subClassOf rdf:resource="#MotorVehicle"/></rdf:Description> <rdf:Description rdf:ID="Van"> <rdf:type rdf:resource="http://www.w3.org/2000/01/rdf-schema#Class"/> <rdfs:subClassOf rdf:resource="#MotorVehicle"/></rdf:Description> <rdf:Description rdf:ID="MiniVan"> <rdf:type rdf:resource="http://www.w3.org/2000/01/rdf-schema#Class"/> <rdfs:subClassOf rdf:resource="#Van"/> <rdfs:subClassOf rdf:resource="#PassengerVehicle"/></rdf:Description> </rdf:RDF>Abstract and dynamic behavior
Using RDF and RDF-Schema we have given structure and shape to the data which we want to work upon. Abstract and dynamic behavior of the web i.e. semantic web is critical factor because of the variety of the services available as well as varied user usage patterns and demographics involved. Considering the infinite amount of static information stored in World Wide Web, we need semantic tool to make some logical sense out of it. We will take an example before we get into the details of this concept.
Consider the next few lines as an example for a scenario. Assume system has following set of data already encoded in it using standards like RDF & RDF-Schema.
· Sandeep is a team member for “Genesis” Account.
· Raman is the project manager of “Genesis” account.
· Team member reports to Project manager of a project.
If we want to know “Whom does Sandeep reports to?” we should be able to get the answer “Sandeep reports to Raman” from the information which we have.
Two languages which are pre-dominantly being used to build this semantic over the data are:
· OWL: Web Ontology Language
· SPARQL: RDF Query language
OWL, Web Ontology language, allows us to define basic infrastructure for computer programs to make inferences based on the semantic defined in it. OWL is used to define ontology for the data present or to be represented by web. Ontology is a term used for the capability for defining Entities as well as relationship between them. It is inherently based on the RDF and RDF-Schema specifications which uses URL references for such representation. OWL encodes basic rules in it based on which new inferences can be made out of the data which exists within one document or multiple distributed documents across the system.
OWL as a language supports following attributes provided by the programming languages vis-Ã -vis ontology to be defined using it:
· Property and data types
o Transitive
o Symmetric
o Functional
o Inverse of
o Inverse functional
· Property restrictions
o All Values
o Some Value
o Cardinality
o Has value
· Equivalence between classes and properties
· Difference between classes
· Complex classes
o Intersection of
o Union of
o Complement of
· Enumeration
· Disjoint classes
· Versioning
SPARQL, Query language for RDF, is another tool which helps in building the semantic rules over the data stored using RDF. SPARQL is like SQL for RDF. It supports most of the features supported by SQL i.e. value testing and constraints.
Artificial Intelligence
There has been debate on whether Web 3.0 is another implementation of Artificial intelligence or it is totally disjoint from it. If yes, then how? Till now we have discussed the need of semantic web, ways to document data and its metadata and how to build capability of making new inferences in the data. Artificial intelligence capabilities will obviously be required by the entities who will be the eventual user of this data. There would be organizations, businesses, governments, educational institutions as well as communities which will be thriving on this data. Each having its own ontologies, there will be a need of integration of these ontologies. AI powered Inference engines / Agents will be required to process the data documented in RDF, RDF-Schema and OWL ontology to serve millions of users over the World Wide Web. Diagram below will give a pictorial view of how WWW will function under Web 3.0 paradigm.
1.2.2. Web 3.0 implementations
Some of the popular implementations of Web 3.0 are provided below:
| The Friend of a Friend (FOAF) project is creating a Web of machine-readable pages describing people, the links between them and the things they create and do; it is a contribution to the linked information system known as the Web. FOAF defines an open, decentralized technology for connecting social Web sites, and the people they describe | |
| OntoWiki facilitates the visual presentation of a knowledge base as an information map, with different views on instance data. It enables intuitive authoring of semantic content, with an inline editing mode for editing RDF content, similar to WYSIWIG for text documents. |
| Web sites | Details |
| SPARQL specification | |
| Web 3.0 introduction. | |
| OWL features | |
| Resources for RDF | |
| RDF-Schema specification | |
| RDF primer |
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