Autocompletion for business process modelling

Abstract

This paper presents an idea and prototype of the semantic-based autocompletion mechanism supporting development of business process models. Currently available process modelling tools support business analysts by suggesting elements that may be incorporated in the process, validating modelled processes, providing additional descriptions easing automation, etc. However, these solutions based mainly on syntactic data, disregard proper identification and usage of previously modelled process fragments. The mechanism described in this paper analyses context and annotations of process tasks (also on the semantic level) in order to deliver a list of suggestions for possible successor tasks: process fragments that may complete the model being developed. We argue that the proposed autocompletion mechanism has an ability to improve the efficiency of the modelling process by among others reducing modelling errors and shortening the duration of the modelling process. © 2011 Springer-Verlag.