**1.1 Knowledge management and the semantic web**

The current version of the Web could only be processed through human intelligence. Though the Internet technologies have taken a huge leap forward since it evolved, the fact is the information within the technology still needs to be interpreted by human brain. However, in his paper (Berners-Lee et al., 2001), Tim Berners-Lee and coauthors have envisaged the next generation of the Web which they call "the Semantic Web". In this Web the information is given with well-defined meaning, better enabling computers and people to work in cooperation. Adding on, the Semantic Web aims at machine-processable information enabling intelligent services such as information brokers, search agents and information filters, which offer greater functionality and interoperability (Decker, et al., 2000). Since then the technology has moved forward significantly and has opened the possibility of sharing and combining information in more efficient way.

The association of knowledge with Semantic Web has provided a scope for information management through the knowledge management. Since both the technologies use ontology to conceptualize the scenarios, Semantic Web technology could provide a platform for developments of knowledge management systems (Stojanovi & Handschuh, 2002). We believe the framework has adopted the knowledge technologies as sub technologies within. The ontologies are core underlying knowledge technologies within this Semantic Web framework. These ontologies are defined through XML based languages and the advanced forms of them.

The major context behind this project is the use of knowledge in order to manage huge sets of heterogeneous dataset in a Web based environment. It primarily focuses on the spatial dataset and its management through the available spatial technologies incorporated within the knowledge technology. As the Web technologies get matured through the Semantic Web, the implementation of knowledge in this domain seems even more appropriate. This research paper puts forward the views and results of the research activities within the backdrop of the Semantic Web technologies and the underlying knowledge technologies.

## **1.2 Knowledge representation and ontologies**

Knowledge representation has been described in five distinct roles it plays in (Davis et al., 1993). Those roles are

	- The representation's fundamental conception of intelligent reasoning
	- The set of inferences the representation sanctions; and
	- The set of inferences it recommends

152 Semantics – Advances in Theories and Mathematical Models

languages could be inferred through different inference mechanisms in order to infer

The current version of the Web could only be processed through human intelligence. Though the Internet technologies have taken a huge leap forward since it evolved, the fact is the information within the technology still needs to be interpreted by human brain. However, in his paper (Berners-Lee et al., 2001), Tim Berners-Lee and coauthors have envisaged the next generation of the Web which they call "the Semantic Web". In this Web the information is given with well-defined meaning, better enabling computers and people to work in cooperation. Adding on, the Semantic Web aims at machine-processable information enabling intelligent services such as information brokers, search agents and information filters, which offer greater functionality and interoperability (Decker, et al., 2000). Since then the technology has moved forward significantly and has opened the

The association of knowledge with Semantic Web has provided a scope for information management through the knowledge management. Since both the technologies use ontology to conceptualize the scenarios, Semantic Web technology could provide a platform for developments of knowledge management systems (Stojanovi & Handschuh, 2002). We believe the framework has adopted the knowledge technologies as sub technologies within. The ontologies are core underlying knowledge technologies within this Semantic Web framework. These ontologies are defined through XML based languages and the advanced

The major context behind this project is the use of knowledge in order to manage huge sets of heterogeneous dataset in a Web based environment. It primarily focuses on the spatial dataset and its management through the available spatial technologies incorporated within the knowledge technology. As the Web technologies get matured through the Semantic Web, the implementation of knowledge in this domain seems even more appropriate. This research paper puts forward the views and results of the research activities within the backdrop of

Knowledge representation has been described in five distinct roles it plays in (Davis et al.,

 A surrogate for the thing itself used to enable an entity to determine consequences by thinking rather than acting, i.e., by reasoning about the world rather than acting it. A set of ontological commitments, i.e., an answer to the question: In what terms should

A fragmentary theory of intelligent, reasoning, expressed in terms of three components

The representation's fundamental conception of intelligent reasoning

The set of inferences the representation sanctions; and

the Semantic Web technologies and the underlying knowledge technologies.

**1.2 Knowledge representation and ontologies**

The set of inferences it recommends

**1.1 Knowledge management and the semantic web**

possibility of sharing and combining information in more efficient way.

knowledge.

forms of them.

1993). Those roles are

I think about the world?


Semantic Web technologies use these roles to represent knowledge. The first and the last roles are primarily theoretical roles through which knowledge could be better understood. The remaining roles are conceptual roles which are being implemented within the technology. If those roles are carefully evaluated, it could be seen that knowledge representation begins with ontological commitments. That is selecting a representation means and making a set of ontological commitments (Brachman et al., 1978). Thus defining ontology is a major activity with the process of the Semantic Web.

The term Ontology is being used for centauries to define an object philosophically. The core theme of the term remains the same in the domain of computer. Within the computer science domain, ontology is a formal representation of the knowledge through the hierarchy of concepts and the relationships between those concepts. In theory ontology is a formal, explicit specification of shared conceptualization (Gruber, 1993) In any case, ontology can be considered as formalization of knowledge representation and Description Logics (DLs) provide logical formalization to the ontologies (Baader et al., 2003).

Description logics (DLs) [(Calvanese et al., 2001); (Baader & Sattler, 2000)] are a family of knowledge representation languages that can be used to represent knowledge of an application domain in a structured and formally well-understood way. The term "Description Logics" can be broken down into the terms description and logic. The former would describe the real world scenario with the real world objects and the relationships between those concepts. More formally these objects are grouped together through unary predicates defined by atomic concepts within description logics and the relationships through binary predicates defined by atomic roles. The term logic adds the fragrance of logical interpretations to the description. Through these logics one could reason the description for generating new knowledge from the existing one.

As the Semantic Web technologies matured, the need of incorporating the concepts behind description logic within the ontology languages was realized. It took few generations for the ontology languages defined within Web environment to implement the description language completely. The Web Ontology Language (OWL) (Bechhofer, et al., 2004); (Patel-Schneider et al., 2004)] is intended to be used when the information contained in documents needs to be processed by applications and not by human (McGuinness & Harmelen, 2004). The OWL language has direct influence from the researches in Description Logics and insights from Description Logics particularly on the formalization of the semantics (Horrocks et al., 2004).

The horn logic more commonly known the Horn clauses is a clause with at most one positive literal. It has been used as the base of logic programming and Prolog languages (Sterling & Shapiro, 1994) for years. These languages allow the description of knowledge with predicates. Extensional knowledge is expressed as facts, while intentional knowledge is defined through rules (Spaccapietra et al., 2004). These rules are used through different Rule Languages to enhance the knowledge possess in ontology. The Horn logic has given a platform to define Horn-like rules through sub-languages of RuleML (Boley, 2009).

Spatialization of the Semantic Web 155

reasoning to enhance the knowledge base. It is widely noticed there is the lack of a known, robust geospatial reasoners. Furthermore, it has been argued that while geospatial reasoning is an ever-evolving field of research, spatial data constructs are not yet accommodated within most current Semantic Web languages as the OWL language (Reitsma & Hiramatsu, 2006).

The seamless integration of spatial components within Semantic Web technologies is the major topic of this research project. Hence, the approach in which this component is integrated within the global framework of the Semantic Web technology is covered extensively within this research project. Additionally, it discusses different components

It has been seen that in the previous section that the ontology engineering has not gained enough momentum to assist spatial activities through ontology. Hence, this project work utilizes the existing potentiality of spatial extensions within the current database system to

Most of the database systems support spatial operations and functions through their spatial extensions. Over the past decade, as Relational DataBase Management System (RDBMS) has seen a huge growth in the database technology. Likewise, the spatial components within them also seen a tremendous improvement in their functionalities. In early days, spatial data were organized in dual architectures which consist of separate administrative data for data management in a RDBMS and spatial data for a GIS system. This could easily result in data inconsistency hence all the database systems today maintain the spatial component in a

In order to have a common standard among different database systems, they implement their spatial performance accordance to the Open Geospatial Consortium (OGC 1998) Simple Features Specifications for SQL (OGC 1999). Since OGC Simple Feature Specifications are built within simple spatial features in 2D space, most of the spatial operations are restricted to 2D spatial data. It is also possible to store, retrieve and visualize 3D data but it does not follow OGC simple feature specifications. Some RDBMS system

According to OGC specification any object is represented spatially following two structures – geometrical and topological. The geometrical structure is the feature providing the direct access to the coordinates of the objects. The topological structure provides the information about the spatial relationships of the objects. The database systems store the geometrical information of the objects and not their topology. They then use their spatial operations to

It is a general fact that technologies always shift for the betterment and the components of the previous technologies must be upgraded to the shifting technology. The world is experiencing a shift in technology from the database oriented Information technology to ontology oriented knowledge technology and thus each individual technology that have matured under previous technology requires to be shifted to this emerging technology. The

retrieve topological relationships between these geometries (Hellerstein et al., 1995).

involved in spatial activities within the framework.

**1.4 Spatial components on database systems**

carry out the spatial activities within the ontology.

today also supports certain 3D spatial queries as well.

**1.5 Aims and the motivation of the project**

single RDBMS.

Summarizing, it could be said that ontology defines the data structure of a knowledge base and this knowledge base could be inferred through various inference engines. These inference engines can be perform under Horn logic through Horn-like rules languages.

Semantic Web technology is slowly revolutionizing the application of knowledge technologies. Knowledge technologies though existed before the Semantic Web, the implementation in their fullness is just being realized. This research benefits from the existing inference engines through the inference rules and reasoning engines to reason the knowledge. However in current stage, the research works moves beyond semantic reasoning and semantic rule processing and attempts to integrate the spatial reasoning and spatial rule inference integrating spatial components in its structure. This research project introduces the approach on achieving the spatial functionalities within those inference engines.
