IOSR Journal of Computer Engineering (IOSR-JCE) e-ISSN: 2278-0661,p-ISSN: 2278-8727, Volume 18, Issue 3, Ver. V (May-Jun. 2016), PP 89-93 www.iosrjournals.org DOI: 10.9790/0661-1803058993 www.iosrjournals.org 89 | Page Design of Layers in Knowledgebase for Expert Systems Yugandhara A. Nimbalkar 1, Dr. Justus S 2 1,2 School of Computer Science and Engineering VIT University Chennai, India Abstract: In any Expert System, Knowledge is the basic functional unit for building a knowledgebase [1]. Hence, Expert Systems are totally/partially depended on Knowledge bases for its intelligent functionality. In our proposed design of Knowledgebase, we have divided it into 3 layers: Logical or Design Layer, Knowledge Layer and Storage Layer.In Logical layer or Design layer a high-level statement or a file is the input, which is processed, and clauses (functional & predicate symbols) are extracted [3]. These will form the basic unit for designing a knowledge unit (KU). These KUs are validated for their scope with identified relations. Then we will create various set of domain-dependent predicates and functions to represent the Knowledge in the Knowledge layer. This representation will be converted to Object Relational Database and will be stored in Storage Layer [2]. Researchers working in design and development of Knowledgebase will be benefitted by this. I. Introduction Data is the collection of raw facts. The facts or the data about the world are put into Knowledgebase. Knowledgebase can be used to infer to various facts of the world with their proper reasoning. We use these facts, some logic rules and other logic forms to deduce new facts. We can also provide the inconsistencies of some facts available in knowledgebase. The Knowledgebase in Experts Systems are layered as follows: Design or Logical Layer, Knowledge Layer and Storage Layer. Design or Logical Layer gets its input from Knowledge Acquisition phase is completed by extracting the data or the raw facts from one source usually human experts and then organizing and storing this data. The next layer is an intelligent layer of the system-Knowledge Layer. In this layer, new facts are deduced from the existing facts and also some inconsistencies can be deduced from them. The third and the last layer of the system is Storage Layer. The extracted facts in acquisition phase are classified into types: Predicate Symbols, Functional Symbols and connectives. These symbols are then stored in the form of Object Relational Database Systems in the Storage Layer. All these symbols together form Ontology for an Organization. Figure 1.Knowledge Management System II. Related Work Three layered Database Management Systems is compared with Knowledge Management Systems and many similarities are found between their concepts. The Presentation Layer of the Database Management System can be compared with Design Layer of Knowledge Management System. In Knowledge Management Systems, Design Layer acts as an interface between the system and user while in Database Systems, Presentation Layer acts as interface [1]. Similarly, Application layer of DBMS is used to perform operations while Knowledge layer of KMS is used to deduce new facts from existing ones. Both Storage layer and Database layer of KMS and DBMS are used to store the knowledge and data. In the design layer of the KMS, knowledge is acquired from various trusted sources such as Experts in that particular field, various Magazines and Journals, meetings and Forums. The knowledge collected is then classified and stored. This knowledge can later be updated by Experts when needed using the concept of Knowledge Reuse [5]. Refer Figure 2.