Paper Info
Title
Verifying the Consistency between Business Process Model and Data Model
Abstract
Business process model and data model play important roles in information system construction. They represent two different perspectives of business knowledge, and are closely related. A trouble to the model quality is the inconsistency between business process model and data model, which can often conduce to interaction errors. While finding such inconsistency is a meaningful problem, it receives little attention in available verification methods. We concentrate on this problem and identify some consistency anomalies between process model and data model. In our paper, a verification method PDGV is proposed to verify the consistency between process model and data model. Implemented prototype reveals that our scheme can detect consistency anomalies effectively.
Year
DOI
Venue
2009
10.1109/JCAI.2009.122
JCAI
Keywords
Field
DocType
implemented prototype,business process model,information systems,available verification method,process model,consistency,consistency anomaly,interaction error,business process,verification method pdgv,verification,meaningful problem,data models,data model,consistency anomaly detection,business knowledge,information system construction,business data processing,model quality,process-data graph verification,data integrity,formal verification,artificial intelligence,data mining,prototypes,process design,unified modeling language,information system,error correction,logic gates,business,data visualization
Artifact-centric business process model,Data mining,Data modeling,Business process,Computer science,Semi-structured model,Logical data model,Artificial intelligence,Consistency model,Business process modeling,Data model,Machine learning
Conference
ISBN
Citations 
PageRank 
978-0-7695-3615-6
2
0.38
References 
Authors
10
5
Name
Order
Citations
PageRank
Lei Wang171.88
Hongyan Li226964.39
qiang qu38312.15
Huaqiang Zhang4112.46
Bin Zhou55416.55