@inproceedings{d127d57c51a441e998fc1f297b09fdbd,
title = "Query data inconsistency for business processes",
abstract = "Business processes are designed to achieve business goals under procedural rules by orchestrating tasks, information and documents. Managing data inconsistency in business processes is a challenging task. If not managed properly, business will face negative financial consequences. From literatures, BPMN modelling approaches deal with inconsistency problem by patterns; data provenance approaches analyze data generated in business process and investigate the reachability between data points. Although substantial works have been done, the data inconsistency problem has not been properly resolved. In particular, it is still lacking of modelling language and resolution for inconsistency caused by multiple starting points of business processes and dynamics of business processes execution. This paper provides data consistency solution in two aspects: a business process modelling in enriched business workflow notation with data states and temporal properties, and a workflow query algorithm to discovery data inconsistency issue.",
keywords = "BPMN, Business process, FSM, Inconsistency, Provenance, Query",
author = "Yongping Tang and Jian Yang and Jianwen Su",
year = "2019",
month = jul,
day = "1",
doi = "10.1109/SERVICES.2019.00117",
language = "English",
isbn = "9781728138527",
series = "IEEE World Congress on Services",
publisher = "Institute of Electrical and Electronics Engineers (IEEE)",
pages = "388--389",
editor = "Chang, \{Carl K.\} and Peter Chen and Michael Goul and Katsunori Oyama and Stephan Reiff-Marganiec and Yanchun Sun and Shangguang Wang and Zhongjie Wang",
booktitle = "Proceedings - 2019 IEEE World Congress on Services, SERVICES 2019",
address = "United States",
note = "2019 IEEE World Congress on Services, SERVICES 2019 ; Conference date: 08-07-2019 Through 13-07-2019",
}