Benefits of Multi-Level Modelling in Ecosystem Interoperability
Sprache des Titels:
Englisch
Original Kurzfassung:
Large-scale interoperability is a major challenge in industry. Inadequate in-teroperability is estimated to cost the US Capital Facilities and the Construc-tion and Engineering Industry about $15.8 billion per year. To reduce these costs one need to address the different problems in interoperability. They involve data management with different terminology, perspectives, meta-models, abstraction levels, representations, standards and software tools, which cause heterogeneities.
We propose the application of multi-level modelling to reduce the complexity in software eco-system interoperability. Compared to traditional model-driven approaches, multi-level modelling incorporates an arbitrary number of abstrac-tion levels. This feature can be used extensively to simplify the representation of specifications and data mappings, and consequently support data interop-erability. The approach is currently evaluated in multiple real life industry cas-es from the oil and gas industry supported by ISO TC 184. These address in particular the hand-over of design documents of very large physical assets to the operation and maintenance side. To support the industry, the use cases are based on two industry standards, each being adopted in a different eco-systems: (1) the CAD design and (2) the engineering ecosystem, where each covers a number of industry partners.
Preliminary results have shown that the approach not only simplifies data models but can also be used to find inconsistencies in the specifications and support the end user in specifying mappings between the standards. So far, multi-level modelling has not been applied by other authors in a similar com-plex environment. Herewith we provide an overview of how multi-level modelling can support and benefit the life-cycle of a standards-based interop-erability solution, provide current results of the evaluation and identify open-issues for future research in the area.
Forschungs-