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Business Provenance – A Technology to Increase Traceability of End-to-End Operations

  • Francisco Curbera
  • Yurdaer Doganata
  • Axel Martens
  • Nirmal K. Mukhi
  • Aleksander Slominski
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5331)

Abstract

Today’s enterprise applications span multiple systems and organizations, integrating legacy and newly developed software components to deliver value to business operations. Often business processes rely on human activities that may not be predicted in advance, and information exchange is heavily based on e-mails or attachments where the content is unstructured and needs discovery. Visibility of such end-to-end operations is required to manage compliance and business performance. Hence, it becomes necessary to develop techniques for tracking and correlating the relevant aspects of business operations as needed without the cost and overhead of a fully fledged data and process reengineering. Our business provenance solution provides a generic data model and middleware infrastructure to collect and correlate information about how data was produced, what resources were involved and which tasks were executed. Business provenance gives the flexibility to selectively capture information required to address a specific compliance or performance goal. Additionally, a powerful correlation mechanism yields a representation of the end-to-end operation that puts each business artifact into the right context, for example, to detect situations of compliance violations and find their root causes.

Keywords

Business Process Business Operation Business Process Management Business Rule Customer Engagement 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Francisco Curbera
    • 1
  • Yurdaer Doganata
    • 1
  • Axel Martens
    • 1
  • Nirmal K. Mukhi
    • 1
  • Aleksander Slominski
    • 1
  1. 1.IBM T J Watson Research CenterHawthorneUSA

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