DEALING WITH HETEROGENEITY OF DATA AND KNOWLEDGE USING OBJECT MODELING

Integration of a large amount of heterogeneity of data and knowledge sources is the biggest challenge in Knowledge representation. In many cases while integrating different types of data, objects and knowledge sources is larger than the sum of its parts. We are integrating data to gain valuable insights produced by different scientific experiments. In this research we examine some of the issues in semantic heterogeneity and propose a novel architecture for resolving such problems. The approach involves the use of Artificial Intelligence tools and techniques to construct "object oriented models, " that is data and knowledge representations of the constituent databases and an overall domain model of the semantic interactions among the databases. These domain models are represented as Knowledge Sources (KSs) in blackboard architecture. This architecture lends itself to an opportunistic approach to query processing and goal-directed problem solving. We introduce the notion of Data/Knowledge packets as a means of supporting both operational and structural semantic heterogeneity. Using object modeling approach we are able to integrate the data and knowledge which will not be redundant and much complex. It will improve the decision making techniques in business domains