A Language and Methodology based on Scenarios, Grammars and Views, for Administrative Business Processes Modelling

International audienceIn Business Process Management (BPM), process modelling has been solved in various ways. However, there are no commonly accepted modelling tools (languages). Some of them are criticized for their inability to capture both the lifecycle, informational and organizational models of processes. For some others, process modelling is generally done using a single graph; this does not facilitate modularity, maintenance and scalability. In addition, some of these languages are very general; hence, their application to specific domain processes (such as administrative processes) is very complex. In this paper, we present a new language and a new methodology, dedicated to administrative process modelling. This language is based on a variant of attributed grammars and is able to capture the lifecycle, informational and organizational models of such processes. Also, it proposes a simple graphical formalism allowing to model each process's execution scenario as an annotated tree (modularity). In the new language, a particular emphasis is put on modelling (using "views") the perceptions that actors have on processes and their data

A Continuous Query Language for Stream-based Artifacts

International audienceArtifacts not only combine data and process into the same semantic entities that evolve according to precise state-based lifecycles, but they also provide casual users with a simple and intuitive framework for modeling, exe- cuting, and managing business processes. Despite the surge in interest, artifacts still lack effective languages and tools to define, manipulate and interrogate their instances. Most existing artifact languages and notations focuses only on modeling and executing artifact-based processes in which data have discrete values and fail to handle artifacts in which their data include continuous data streams. In this paper, we present the Continuous Artifact Query Language (CAQL) for modeling stream-based artifacts and semantically manipulating and interrogating their instances