Research on Rulebase Metamodel Construction and Management

Zhu, Hong; Wang, Shuang

With the implementation of big data strategy in many countries of the world, the data organization and analysis technology has become the main methods for data application and data governance capability. Since data is always organized by specific rules, how to organize information and construct the consolidated rules of data has become an important issue of big data application. However, at present, there is no mature theory of rule and rulebase construction, lack of high-level general rulebase model, and there is no efficient evaluation criteria system for the quality of rule base, which affects the establishment and high-quality management of rulebase. This paper studies how to model and management the rulebase of information resources. First, this paper analyses types of rules and rule relationships according to their functions and semantic properties. Then we propose the requirements for harmonization of rules in the same context. Second, we propose the metamodel of rulebase, and describe the classes and associations of rulebase metamodel. We introduce the internal identifier and composite identifier for rules. Thirdly, we define six measurements for quality control and propose the process of rulebase version control.