Modeling and In-Database Management of Relational, Data-Aware Processes

Proc. of the 31st Int. Conf. on Advanced Information Systems Engineering (CAiSE 2019). Volume 11483 of Lecture Notes in Computer Science. 2019.

It is known that the engineering of information systems usually requires a huge effort in integrating master data and business processes. Existing approaches, both from academia and the industry, typically come with ad-hoc abstractions to represent and interact with the data component. This has two disadvantages: (i) an existing database (DB) cannot be effortlessly enriched with dynamics; (ii) such approaches generally do not allow for integrated modelling, verification, and enactment. We attack these two challenges by proposing a declarative approach, fully grounded in SQL, that supports the agile modelling of relational data-aware processes directly on top of relational DBs. We show how this approach can be automatically translated into a concrete procedural SQL dialect, executable directly inside any relational DB engine. The translation exploits an in-database representation of process states that, in turn, is used to handle, at once, process enactment with or without logging of the executed instances, as well as process verification. The approach has been implemented in a working prototype.

@inproceedings{CAiSE-2019,
   title = "Modeling and In-Database Management of Relational, Data-Aware
Processes",
   year = "2019",
   author = "Diego Calvanese and Marco Montali and Fabio Patrizi and
Andrey Rivkin",
   booktitle = "Proc. of the 31st Int. Conf. on Advanced Information Systems
Engineering (CAiSE 2019)",
   pages = "328--345",
   volume = "11483",
   publisher = "Springer",
   series = "Lecture Notes in Computer Science",
   doi = "10.1007/978-3-030-21290-2_21",
}