Semantic Model Alignment for Business Process Integration

Business process models describe an enterprise’s way of conducting business and in this form the basis for shaping the organization and engineering the appropriate supporting or even enabling IT. Thereby, a major task in working with models is their analysis and comparison for the purpose of aligning them. As models can differ semantically not only concerning the modeling languages used, but even more so in the way in which the natural language for labeling the model elements has been applied, the correct identification of the intended meaning of a legacy model is a non-trivial task that thus far has only been solved by humans. In particular at the time of reorganizations, the set-up of B2B-collaborations or mergers and acquisitions the semantic analysis of models of different origin that need to be consolidated is a manual effort that is not only tedious and error-prone but also time consuming and costly and often even repetitive. For facilitating automation of this task by means of IT, in this thesis the new method of Semantic Model Alignment is presented. Its application enables to extract and formalize the semantics of models for relating them based on the modeling language used and determining similarities based on the natural language used in model element labels. The resulting alignment supports model-based semantic business process integration. The research conducted is based on a design-science oriented approach and the method developed has been created together with all its enabling artifacts. These results have been published as the research progressed and are presented here in this thesis based on a selection of peer reviewed publications comprehensively describing the various aspects

dexesESC: Development and EXpansion of Existing Services Associated with the EUROPEAN STUDENT CARD, EUt+ Sofia Week, 18-10 January, 2023

THE EUROPEAN STUDENT CARD INITIATIVE An initiative to help students and higher education institutions on Erasmus+ exchanges by simplifying administrative processes and enhancing digitalisation. It is also crucial to promoting student participation in educational and cultural activities in line with the vision to create a European Education Area by 2025

Context-Sensitive Referencing for Ontology Mapping Disambiguation

Abstract. Ontologies can be used for e-business integration, for example by describing existing e-business standards as ontologies. If cooperating parties use different ontologies, ontology mappings are needed, which can be ambiguous, thus making ontology mapping disambiguation necessary. Different disambiguation strategies exist, such as community-driven or context-sensitive referencing of ontologies, where the latter is what we developed in our project. In this paper, we show that community-driven referencing can be realized using a context-sensitive referencing service in a way that the user administration is transparent to the referencing system