Hybrid Modeling: An Instrument for Conceptual Interoperability

Hybrid Modeling: An Instrument for Conceptual Interoperability

Robert Woitsch (BOC Asset Management, Austria)
DOI: 10.4018/978-1-4666-5142-5.ch005
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Abstract

Enterprise Interoperability can be identified on cultural, rule, process, data, software, object, social network, services, knowledge, electronic ID, cloud, and ecosystem level, whereas the challenge is the conceptual integration across those layers in a flexible way. Meta Modeling as a concept is a proven technology to enable such conceptual integration for both machine computation and human-oriented interpretation for information value creation. Hybrid Modeling is a realization approach to merge different meta models and hence enable the interoperability between conceptual models. Stability is provided by the meta modeling platform whereas flexibility is ensured by hybrid modeling via a holistic integration framework. This approach has been successfully implemented in a list of EU-research projects. This chapter introduces (a) concept models as an instrument for interoperability, (b) a meta model approach as a flexible but stable platform, and (c) hybrid modeling as an approach to flexibly compose the conceptual integration. After discussing this theoretical background, the chapter introduces different realization scenarios of hybrid modeling. Each scenario is supported differently by the underlying meta modeling platform ADOxx®. Here, the experience of a list of EU-research projects is explained and reflected to enterprise interoperability requirements. Sample solutions are introduced, showing different hybrid modeling implementations. Technical overviews of the ADOxx® meta modeling platforms are introduced and references to open development communities are provided to invite readers to realize their own modeling solutions.
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2. Interoperability And Conceptual Background

This section introduces the application domain enterprise interoperability. Hence the characteristics of enterprise interoperability is briefly introduced but mainly referenced to publications of the FInES Cluster and corresponding projects. Some practical samples from current and past research projects are elaborated.

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