A Self-Adaptive Middleware for Attaining Semantic Self-Interoperation Property

Abstract

Developing specific standards and taxonomies and their enforcement for data exchange is a common approach applied by many regulators all around the word. Although these standards and taxonomies can enhance the interoperability and understandability of information to a significant extent, they are limited to a specific scope. This limitation arises the need for extending these taxonomies and standards. The differences between various extended taxonomies and between a base taxonomy/standard and others, can itself become an interoperability bottleneck. The majority of existing researches for this issue, concentrate on only mappings for overcoming inconsistencies between information elements. These mappings usually involve complex and inaccurate transformations to ontologies. However, in this research, it is intended to utilize the capabilities of autonomic computing and self-adaptation paradigm to overcome interoperability challenges. In order to make use of autonomic computing in field of semantic interoperability, a new self-* property named self-interoperation is introduced and a self-adaptive middleware is proposed in order to achieve it. For this purpose, MAPE-K loop is utilized for overcoming Interoperability challenges through actualizing this loop for domain of self-interoperation. Moreover, many required contributions for enabling this loop are considered. All of these contributions are novel approaches, which include all the necessary steps for applicable adaptation to inconsistencies and enhancement of interoperability. Indeed, this research can lead to development of a new research area related to fields of self-adaptation and interoperability. The contributions will be evaluated by selecting well-known taxonomies and instances from actual applications.