On the Social Network Based Semantic Annotation of Conceptual Models

The semantic annotation of conceptual visual models permits to leverage the contained semantic information to a machine processable level. At the same time the intuitive and non-technical nature of graphical models can be maintained. Although this leads to direct benefits in terms of potential analysis functionalities, the addition of annotations for large model corpora requires quite some effort by the modelers. In order to contribute to the efficiency when adding semantic annotations, we propose an approach that links information on semantic annotations to information available from social network applications. In this way the addition of semantic annotations can be facilitated in terms of communication support, economic benefits, and technical opportunities. For the design of the approach we use a specifically developed modeling method, which allows to reason about the requirements at a high abstraction level and permits to add more formal specifications, e.g. to define behavior. A first prototype of the modeling method has been implemented using the freely available ADOxx meta modeling platform based on the SeMFIS toolkit.