Robust Module based data management system

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  • Configuration:-H/W System Configuration:- Processor - Pentium –IIISpeed - 1.1 GhzRAM - 256 MB(min)Hard Disk - 20 GBFloppy Drive - 1.44 MBKey Board - Standard Windows KeyboardMouse - Two or Three Button MouseMonitor - SVGAS/W System Configuration:-Operating System :Windows95/98/2000/XP Application Server : Tomcat5.0/6.X Front End : HTML, Java, Jsp Scripts : JavaScript.Server side Script : Java Server Pages.Database : Mysql 5.0Database Connectivity : JDBC.
  • Sharing common understanding of the structure of information among people or software agents is one of the more common goals in developing ontologies.For example, a class of wines represents all wines. Specific wines are instances of this class. The Bordeaux wine in the glass in front of you while you read this document is an instance of the class of Bordeaux wines. A class can have subclasses that represent concepts that are more specific than the superclass. For example, we can divide the class of all wines into red, white, and ros� wines. Alternatively, we can divide a class of all wines into sparkling and non-sparkling wines.
  • Robust Module based data management system

    1. 1. ROBUST MODULE BASED DATABASE MANAGEMENT SYSTEM Presented by : Rahul Roi M. Sai Krupani P. Manasa Prem Kumar 10E51A0564 10E51A0566 10E51A0581 09E51A0563
    2. 2. ABSTRACT      The current trend for building an ontology-based data management system (DMS) is to capitalize on efforts made to design a preexisting wellestablished DMS (a reference system). The OWL Web Ontology Language is designed for use by applications that need to process the content of information instead of just presenting information to humans. OWL facilitates greater machine interpretability of Web content than that supported by XML, RDF, and RDF Schema (RDF-S) by providing additional vocabulary along with a formal semantics. It provides an introduction to OWL by informally describing the features of each of the sublanguages of OWL. Some knowledge of RDF Schema is useful for understanding this document, but not essential. RDF- Resource Description Framework is a family of world wide web consortium which is designed as metadata data model.
    3. 3. ONTOLOGY     Ontology core meaning within computer science is a model for describing the world that consists of a set of types, properties, and relationship types. There is also generally an expectation that the features of the model in an ontology should closely resemble the real world. In computer science and information science, an ontology formally represents knowledge as a set of concepts within a domain, using a shared vocabulary to denote the types, properties and interrelationships of those concepts Ontology's are the structural frameworks for organizing information and are used in artificial intelligence, the Semantic Web, systems engineering, software engineering, biomedical informatics ,etc
    4. 4. WHAT IS ONTOLOGY IN ENGINEERING? Ontology engineering in computer science and information science is a new field, which studies the methods and methodologies for building ontologies: Formal representations of a set of concepts within a domain and the relationships between those concepts. A large-scale representation of abstract concepts such as actions:  An ontology language is a formal language used to encode the ontology. OWL is a language for making ontological statements, developed as a follow-on from RDF and RDFS.  OWL is intended to be used over the World Wide Web, and all its elements (classes, properties and individuals) are defined as RDF resources, and identified by URIs.
    5. 5. Existing System The current trend for building an ontology-based data management system (DMS) is to capitalize on efforts made to design a preexisting well-established DMS (a reference system). The method amounts to extracting from the reference DMS a piece of schema relevant to the new application needs – a module –, possibly personalizing it with extra-constraints w.r.t. the application . Problems on existing system:  It is not easy to maintain.  Its related data can not be retrieved
    6. 6. Proposed System  Here, we extend the existing definitions of modules and we introduce novel properties of robustness that provide means for checking easily that a robust module-based DMS evolves safely w.r.t. both the schema and the data of the reference DMS.  We carry out our investigations in the setting of description logics which underlie modern ontology languages, like RDFS(Resource Description Framework), OWL.  Notably, we focus on the SQL-Lite: the W3C recommendation for efficiently managing large datasets. Advantages:  This is very useful to maintain Data.  Search and retrieve the data is very Easy.
    7. 7. Configuration:H/W System Configuration:•Processor •Speed •RAM •Hard Disk - Intel core 1.1 GHz(min) 256 MB(min) 20 GB(min) S/W System Configuration:•Operating System •Application Server •Front End • Scripts •Database •Database Connectivity : : : : : : Windows95/98/2000/XP /7 Tomcat5.0/6.X HTML, Java, Jsp , OWL JavaScript. SQL- Lite JDBC.
    8. 8. What ontology does? An ontology defines a common vocabulary for researchers who need to share information in a domain. It includes machine-interpretable definitions of basic concepts in the domain and relations among them. Why would someone want to develop an ontology? Some of the reasons are:  To share common understanding of the structure of information among people or software agents.  To enable reuse of domain knowledge.  To make domain assumptions explicit.  To separate domain knowledge from the operational knowledge.  To analyze domain knowledge.
    9. 9. Goal for developing Ontology : is Sharing common understanding of the structure of information among people or software agents .  For example, in java a super class has n number of sub classes. Where sub classes are the instances of the super class  A class can have subclasses that represent concepts that are more specific than the super class.  For example, we can divide the class of all wines into red, white, and rose wines.  Alternatively, we can divide a class of all wines into sparkling and non-sparkling wines.
    10. 10. In practical terms, developing an ontology includes:  defining classes in the ontology,  arranging the classes in a taxonomic (subclass super class) hierarchy.  defining slots and describing allowed values for these slots,  filling in the values for slots for instances

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