Automatic mapping of logistics data

Achieving interoperability eventually results in the task of mapping different data formats and so-called schema matching. At present, this task is carried out manually. Prior research has proven this task difficult to fully automate, because it requires knowledge of designers and schemas do not necessarily capture all semantics of the data. Early research indicates that intervention can improve mapping results. Validated research in this area however is still in its infancy.

Contribution

The main contribution of this research is a reference architecture and prototype using the hybrid integration platform eMagiz and Microsoft machine learning studio. Our research provides a starting point, and a set of guidelines for developing smarter interoperability applications based on automatic schema matching, the concepts of Intelligence Amplification, and machine learning techniques. Preliminary results of the first design and development cycle are encouraging but require additional development and thorough validation.

Methodology

This research is conducted based on the Design Science Research Methodology for Information Systems Research of Peffers et. al. Using available literature, the problem is investigated and existing approaches have been evaluated. Eventually, a reference architecture for Intelligence Amplification driven schema matching is modelled using the ArchiMate specification and language. The developed prototype demonstrates that it is possible to develop a collaborative approach to schema matching, utilizing the knowledge of the designer and machine intelligence.

Authors and resources

This research is performed by @Sebastian Piest, @Lucas Meertens of CAPE Groep and former Business Information Technology Master student @Johan Buis, @Maria Iacob and @Marten van Sinderen of the University of Twente as part of the TKI Dinalog project Autonomous Logistics Miners for Small and Medium-sized Businesses. The illustrated poster and related research output is made available via ResearchGate.

• The illustrated poster Automatic mapping of logistics data
• The Paper presentation Smarter interoperability based on automatic schema matching and intelligence amplification
• The Master thesis Applying Intelligence Amplification to the problem of Schema Matching
• The public report of the TKI Dinalog project

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