A structured approach to identify and resolve semantic conflicts between independently developed information systems

In today’s world an enterprise’s success not only depends on its internal productivity and performance, but also on its ability to partner with others. In order to remain competitive, enterprises thus need to share information with buyers and suppliers so that processes can be aligned, and there is maximum information availability to support business decisions. Interoperability is the concept at which organizations have achieved such connectivity. Semantic conflicts are an important barrier to overcome when aiming for interoperability. When two or more independently developed information systems are connected, semantic conflicts occur. These differences in the meaning and understanding of exchanged information can lead to wrong business decisions and have high impact, and thus have to be avoided. In this research we make a first attempt to create a methodology that guides the problem holder in this process of semantic conflict identification and resolution. The methodology we developed consists of four stages. In the first stage the problem holder formalizes the objectives of the interoperability project and defines the concepts to be exchanged. In the second step these concepts are isolated in each participating information system and expressed in an Entity Relationship diagram. In the third step the concepts in the different systems are compared at four different levels: the entity-, attribute-, data format-, and data value level. At each level we indicate the potential semantic conflicts and provide tools to identify them. In the fourth stage the user creates a visual overview of all discovered conflicts. Finally, we propose conflict resolution techniques for each conflict identified by the methodology. To validate the usability of the methodology in practice, we applied it to a data integration project of Dienst Uitvoering Onderwijs and the SUWI Gegevensregister in the Netherlands. The results indicate that the methodology is well capable of identifying semantic conflicts between two systems. Compared to the findings from the case holder itself, we discovered similar semantic relationships and conflicts. A few differences indicate suggestions for improvement, most importantly a confirmation of the results after each stage with a domain expert. Further validation was performed by an expert review to measure the general belief in the usefulness of the methodology. Results indicate that the general structure of the method was found to be useful, but that further development is needed to increase its ability to recognize semantically similar concepts in the different systems. This research makes a first attempt to develop a standard approach for the identification of semantic conflicts, and thereby contributes to the framework for interoperability by targeting the conceptual barriers at the service level. It also provides a new way to categorize semantic conflicts. Instead of segregating by the characteristics of the conflict, we categorize by the entity-, attribute-, data format-, and data value level. Furthermore, the methodology presented in this research help organizations aiming for interoperability to identify semantic conflicts in a more efficient way, and provides suggestions for how to resolve each type of conflict. Finally, we suggest further research for the development of instrument guidelines and tools to support the user in the use of the methodology.