Microbiology

Database Systems and Knowledge base Systems share many common principles. Data &
Knowledge Engineering (DKE) stimulates the exchange of ideas and interaction between these
two related fields of interest. DKE reaches a world-wide audience of researchers, designers,
managers and users. The major aim of this paper is to identify, investigate and analyze the
underlying principles in the design, implementation and effective use of Knowledge
Representation in AI. DKE achieves this aim by publishing original research results, technical
advances and news items concerning data engineering, knowledge engineering, and the interface
of these two fields.

Today’s web browsers serve as an easy access to numerous sources of text and multimedia data. More than a billion pages are indexed by search engines, and finding the desired information is not an easiest task. Over the last decade, there is an explosive growth in the information available on the World Wide Web(WWW). The objective of this paper is to provide an outline of web mining, its various classifications, its subtasks, and to give a perspective to the research community about the potential of applying techniques to extract meaningful patterns. This paper also gives information in the area of web services, semantic web mining and comparison of traditional web applications and semantic web applications thereby providing the guidelines for future research in the area of web services using web mining and semantic web.

Database, XML and its schema languages do not express structures with nesting information but without semantics. OWL represent different document structures with richer semantics. Though syntactic structures can carry meanings that are independent of specific words with semantic means, this research work provides an ontology-based framework that aims from multi-platform databases to develop multiple XML documents that indeed export OWL that intemperate at the semantic level while retaining their nesting structure. Various level are pretended, the first level is considered with XML conversion, second inclusion of converted XML documents and third with generation of OWL Ontology . This generated OWL ontology unifies the query access and establishes semantic connections among the underlying individual databases. The Utilization and the difference is shown creating SQL for database and SPARQL for Ontology using Protégé. However individual database query recognizes their dependence in larger consideration compared with OWL query languages.