[Back]

F. Ekaputra, R. Sabou, E. Kiesling, E. Serral Asensio, S. Biffl:
"Ontology Based Data Integration in Multi-Disciplinary Engineering Environments: A Review";
Open Journal of Information Systems, 4 (2017), 1; 26 pages.

Today´s industrial production plants are complex mechatronic systems. In the course of the production plant
lifecycle, engineers from a variety of disciplines (e.g., mechanics, electronics, automation) need to collaborate in
multi-disciplinary settings that are characterized by heterogeneity in terminology, methods, and tools. This collaboration yields a variety of engineering artifacts that need to be linked and integrated, which on the technical
level is reflected in the need to integrate heterogeneous data. Semantic Web technologies, in particular ontologybased data integration (OBDI), are promising to tackle this challenge that has attracted strong interest from the
engineering research community. This interest has resulted in a growing body of literature that is dispersed across
the Semantic Web and Automation Systems Engineering research communities and has not been systematically
reviewed so far. We address this gap with a survey reflecting on OBDI applications in the context of Multi-Disciplinary Engineering Environment (MDEE). To this end, we analyze and compare 23 OBDI applications from both
the Semantic Web and the Automation System Engineering research communities. Based on this analysis, we (i)
categorize OBDI variants used in MDEE, (ii) identify key problem context characteristics, (iii) compare strengths
and limitations of OBDI variants as a function of problem context, and (iv) provide recommendation guidelines
for the selection of OBDI variants and technologies for OBDI in MDEE.

multi-disciplinary engineering, ontologies, data integration