Authors:
Joe Y.-C Lin
and
Shazia Sadiq
Affiliation:
School of Information Technology & Electrical Engineering, The University of Queensland, Australia
Keyword(s):
Business Process Management, Data Flow, Constraint Modelling.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Business Process Management
;
e-Business
;
Enterprise Engineering
;
Enterprise Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Management and Information Sharing
;
Knowledge-Based Systems
;
Modeling Concepts and Information Integration Tools
;
Modeling Formalisms, Languages and Notations
;
Symbolic Systems
Abstract:
Business Process Management (BPM) and related tools and systems have generated tremendous advantages for enterprise systems as they provide a clear separation between process, application and data logic. In spite of the abstraction value that BPM provides through explicit articulation of process models, a seamless flow between the data, application and process layers has not been fully realized in mainstream enterprise software, thus often leaving process models disconnected from underlying business semantics captured through data and application logic. The result of this disconnect is disparity (and even conflict) in enforcing various rules and constraints in the different layers. In this paper, we propose to synergise the process and data layers through the introduction of data dependency constraints, that can be modelled at the process level, and enforced at the data level through a (semi) automated translation into DBMS native procedures. The simultaneous and consistent specifica
tion ensures that disparity between the process and data logic can be minimized.
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