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With the increase in demand of services in the automotive industry, automotive enterprises prefer to collaborate with other qualified cross-domain partners to provide complex automotive functions (or services), such as autonomous driving, OTA (Over The Air) vehicle update, V2X (Vehicle-to-Vehicle communication), etc. One key element in cross-domain enterprise collaboration is the mutual agreement between interfaces of software components. In this context, model-to-model mappings of software component models of heterogeneous frameworks for automotive services and to explore the synergies in their interface semantics, have become an essential factor in improving the interoperability among the automotive and other cross-domain enterprises. However, one of the challenges in achieving cross-domain component interface model-to-model mappings at an application level lies in detecting the interface semantics and the semantic relations that are conveyed in different component models in different frameworks. This paper addresses this challenge using a Model Driven Architecture (MDA) based analytical approach to explore interface semantic synergies in the cross-domain component meta-models that are used for automotive services. The approach applies manual semantic checking measurements at an application interface level to understand the meanings and relations between the different meta-model entities of cross-domain framework software components. In this research, we attempt to ensure that interface description models of software components from heterogeneous frameworks can be compared, correlated and re-used for automotive services based on semantic synergies. We have demonstrated our approach using component meta-models from cross-domain enterprises, that are used for the automotive application domain.
In recent years, mapping of application software components’ ontologies semantically emerged as a big research challenge in automotive application domain that manipulates several cross-enterprise synergy knowledge application frameworks. The same knowledge formalized by different experts in different vehicle application frameworks leads to heterogeneous representations of components’ interface data. Consequently, this causes the most daunting impediment in semantic interoperability between the service components in cooperative automotive systems. From a modeling perspective, in the absence of standardized domain-based unified modeling techniques, the orchestration and resolution of semantic data interoperability between various vehicle application frameworks’ components’ interface models remain a challenge. However, this challenge could be addressed using ontological metamodeling by specifying semantic associations between components’ interface model concepts based on the domain knowledge. Apart from the semantic mapping of interface ontological metamodels, this work also defines quality metrics to determine the degree of semantic alignment achieved between the various interface ontologies. Additionally, to reduce development time and cost towards semantic interoperability, this work proposes a semi-automated plugin tool for the applicability of the evaluated quality metrics to semantic mapping of real-world components’ interface models.