Semantic Web

The Semantic Web is the extension of the World Wide Web that enables people to share content beyond the boundaries of applications and websites. Lt has been described in rather different ways: as a utopic vision, as a web of data, or merely as a natural paradigm shift in our daily use of the Web. Most of all, the Semantic Web has inspired and engaged many people to create innovative semantic technologies and applications.

        The word semantic itself implies meaning or understanding. As such, the fundamental difference between Semantic Web technologies and other technologies related to data (such as relational databases or the World Wide Web itself) is that the Semantic Web is concerned with the meaning and not the structure of data.This fundamental difference engenders a completely different outlook on how storing, querying, and displaying information might be approached.  Some applications, such as those that refer to a large amount of data from many different sources, benefit enormously from this feature.  Others, such as the storage of high volumes of highly structured transactional data, do not.

The Semantic Web consists primarily of three technical standards:

• RDF (Resource Description Framework): The data modeling language for the Semantic Web. All Semantic Web information is stored and represented in the RDF.
• SPARQL (SPARQL Protocol and RDF Query Language): The query language of the Semantic Web. It is specifically designed to query data across various systems.
• OWL (Web Ontology Language) The schema language, or knowledge representation (KR) language, of the Semantic Web. OWL enables you to define concepts composably so that these concepts can be reused as much and as often as possible. Composability means that each concept is carefully defined so that it can be selected and assembled in various combinations with other concepts as needed for many different applications and purposes.

Introduction

Business Intelligence is the future of efficient management and improves profitability in today’s industry. Semantic web technologies provide much flexible knowledge gathering and processing platform on data. Data can be gathered and processed using various available technologies to find relationships base on reason. This knowledge can be stored and processed using RDF/OWL technologies and can quire by languages like SPARQL with available technology frameworks. Processing large amounts of unstructured data can be quite computation intensive process. This challenge can be overcome by parallelism and using techniques like Google Map Reduce.
Further by including Natural Language Processing the information analysis can be greatly eased out for the end user of the system. This will help the end users to make quick decisions which can lead to profitability in an organization.
The semantic web (SW) has been conceived as a means to build semantic spaces over web published contents so that web information can be effectively retrieved and processed by both humans and machines in a great variety of tasks
SW Formats: RDF(S) and OWL
In RDF there are three kinds of elements resources, literals, and properties. Resources are web objects (entities) that are identified through a URI, literals are atomic values such as strings, dates, numbers, etc.,
The ontology web language (OWL) mainly differs from RDFS in the underlying semantic formalism, which is founded in description logics (DL) . Indeed, OWL languages provide RDF/XML serializations of different DL languages.