Abstract Data interoperability implies data exchanges among intra and inter enterprises collaborating with information systems (IS). The multiplicity of these exchanges and the increasing number of data exchanged generates complexity and brings out the needs for control to avoid dysfunctions with a negative impact on the overall performance of the systems. Indeed, actually, interoperability has become a necessary performance lever that thus requires particular attention. Being at a low level in the enterprise interoperability concerns, data interoperability is mainly automated, which leads us to question: Is it possible to evaluate data interoperability performance and security based on inspection and analysis of ongoing data exchanges? We therefore endeavored to answer this question by establishing monitoring and analysis systems. In this paper, we present a research work which addresses services provided by a messaging‐based communication system. In order to collect information on Information System interactions allowing one to assess their level of data interoperability, we propose a messaging metamodel that aggregates the collected information. It provides a single point of control and enables one to determine indicators of potential interoperability problems. The approach is validated on two case studies. An industrial case study of interactions among existing systems is presented to showcase the feasibility and interest of the approach. It is proposed on top of RabbitMQ and allows our partner to identify some issues in the studied information system. The second case study shows that the approach can integrate other protocols, by reading MQTT messages. The approach is implemented using Moose, a software analysis platform.

International audience