• Business process modeling is a complex, time consuming and error prone task. Model design requires determining the activities that need to be performed, ordering of their execution, handling exceptional cases that might occur, etc. In many cases, variants of process models need to be created in respond to special business situations. For instance, there could several insurance claim handling process. One process is designed for people with special working environment conditions, another for people over seventy years, etc. With the rapid growth in the number of process models developed by different process designers, providing business process designers with a framework for reusing previously designed business process models and for making the best use of them is of great practical value.


  • In order to simplify and improve the business process modeling task, process models need to be highly reusable, favoring process flexibility and minimizing designs made from scratch. Moreover, reusing can effectively increase the quality and the maturity of the newly developed process models.


  • QBP (Querying Business Process) is a framework which aims of supportting business process designers to achieve an effective modeling task by querying and reusing existing process models. In particular, we summarize the current strengths of our system as follows:
    • The framework is based on a novel, intuitive and visual query language for business process models, BPMN-Q. It allows users to define their business process models and their queries using a very similar set of notations. Moreover, it supports the notion of paths between nodes in the process graph and supports different way of navigation through the process structures to answer the user queries.
    • The framework is enhanced with a semantic query expansion component of BPMN-Q queries. This component employs an ontological dimension in the query matching process and tackles the problem of applying different terminologies when modeling processes. Ontology construction does not assume a priori semantic tagging or semantic description of process models.
    • To achieve an efficient and scalable performance, the SQL-backend query processor makes use of the robust indexing infrastructure typically available by RDBMS and uses a novel decomposition-based and selectivityaware translation mechanism of business process graph queries into efficient SQL scripts.
    • The framework architecture is designed in a very flexible front-end/back-end fashion. On the front-end, it uses BPMN for modeling business processes, BPMN-Q for querying business processes and standard SQL relational processor as its back-end. However, the proposed framework can be easily adapted to other modeling notations such as: EPCs, UML ADs.
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