Business process integration has become prevalent as business is increasingly crossing organizational boundaries. While workflow technology is a standard solution for business process management, it is imperative for workflow management systems to provide effective and efficient support for collaboration. To address the issue of protecting organizations' competitive knowledge and private information while also enabling business-to-business (B2B) collaboration, past research has focused on customized public and private process design and structure correctness of the integrated workflow. However, dataflow is important for business process integration because data is always sensitive when conducting inter-organizational business and data errors could still happen even given syntactically correct activity dependence. This paper presents a data flow perspective. It gives art approach to define a "public data set" for each involved organization exemplifying the integrated workflow that is needed in order to be free from data anomalies e.g., missing data and redundant data errors.
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