Rule extraction ontology generation from an adaptive IoT ecosystem database
JungHyen Ahn, Young B. Park · 2017
The emergence of a new paradigm such as ubiquitous or IoT implies that the members of future software systems can vary dynamically, rather than being predetermined according to the purpose of the system. Unlike in the case of the conventional systems, in order to give adaptability to systems that change dynamically, the system rules should be designed and applied considering the dynamic changes of members in addition to environmental dynamic parameters. However, the resolution for this is complicated in terms of process and unstructured in terms of information structure, because the information of the participants is distributed among the system components. In an adaptive system, the information concerning the environment and the participants is stored in a relational database, and ontologies should be used to create models and rules that can integrate information from the various participants. In this paper, we propose a method to generate an ontology through a database schema to simplify and formalize the rule design and the application for the participants in an adaptive system. Moreover, we describe the process required to create the ontology from the database schema and the rules related to the creation, and demonstrates the experimental results that the ontology can be generated successfully from the example of an actual database schema.