Abstract
A profound analysis of all relevant business data in a company is necessary for optimizing business processes effectively. Current analyses typically run either on business process execution data or on operational business data. Correlations among the separate data sets have to be found manually under big effort. However, to achieve a more informative analysis and to fully optimize a company’s business, an efficient consolidation of all major data sources is indispensable. Recent matching algorithms are insufficient for this task since they are restricted either to schema or to process matching. We present a new matching framework to (semi-)automatically combine process data models and operational data models for performing such a profound business analysis. We describe the algorithms and basic matching rules underlying this approach as well as an experimental study that shows the achieved high recall and precision.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Agrawal R et al (1998) Mining process models from workflow logs. In: Schek H-J, Saltor F, Ramos I, Alonso G (eds) 6th international conference on extending database technology, advances in database technology – EDBT’98, Valencia, 23–27 Mar 1998
Bernstein PA, Haas LM (2008) Information integration in the enterprise. Commun ACM 51(9):72–79
Bruckner RM, List B, Schiefer J (2002) Striving towards near real-time data integration for data warehouses. In: 4th international conference on data warehousing and knowledge discovery, DaWaK 2002, Aix-en-Provence, 4–6 Sept 2002
Cardoso J, Sheth AP (2006) Semantic web services, processes and applications. Springer, New York
Casati F et al (2007) A generic solution for warehousing business process data. In: Koch C et al (eds) Proceedings of the 33rd international conference on very large data bases, University of Vienna, Vienna, 23–27 Sept 2007
Castellanos M, Casati F, Dayal U, Shan M-C (2004) A comprehensive and automated approach to intelligent business processes execution analysis. Distrib Parallel Databases 16(3):239–273
Corrales JC et al (2008) BeMatch: a platform for matchmaking service behavior models. In: Kemper A et al (eds) 11th international conference on extending database technology EDBT 2008, Nantes, 25–29 Mar 2008
Do H, Melnik S, Rahm E (2003) Comparison of schema matching evaluations. In: Web, web-services, and database systems. Springer, Berlin/Heidelberg/New York
Do H, Rahm E (2002) COMA – a system for flexible combination of schema matching approaches. In: Proceedings of 28th international conference on very large data bases VLDB 2002, Hong Kong, 20–23 Aug 2002
Doan A et al (2004) Ontology matching: a machine learning approach. In: Handbook on ontologies (International Handbook on Information Systems). Springer, Berlin/Heidelberg
Dong X et al (2004) Similarity search for web services. In: Nascimento MA et al (eds) (e)Proceedings of the thirtieth international conference on very large data bases, Toronto, 31 Aug–3 Sept 2004
Hepp M et al (2005) Semantic business process management: a vision towards using semantic web services for business process management. In: Lau FCM, Lei H, Meng X, Wang M (eds) 2005 IEEE international conference on e-business engineering, ICEBE 2005, Beijing, 18–21 Oct 2005
Madhavan J, Bernstein PA, Rahm E (2001) Generic schema matching with Cupid. Technical report, Microsoft Research
Radeschütz S, Mitschang B (2008) An annotation approach for the matching of process variables and operational business data models. In: Harris FC Jr (ed) Proceedings of the ISCA 21st international conference on computer applications in industry and engineering, CAINE 2008, Honolulu, 12–14 Nov 2008
Radeschütz S et al (2010) BIAEditor – matching process and operational data for a business impact analysis. In: Manolescu I et al (eds) 13th international conference on extending database technology EDBT 2010, Lausanne, 22–26 Mar 2010
Radeschütz S, Vrhovnik M, Schwarz H, Mitschang B (2011) Exploiting the symbiotic aspects of process and operational data for optimizing business processes. In: Proceedings of the IEEE international conference on information reuse and integration, IRI 2011, Las Vegas, 3–5 Aug 2011. IEEE Systems, Man, and Cybernetics Society
Rahm E, Bernstein PA (2001) A survey of approaches to automatic schema matching. VLDB J 10(4):334–350
Rubin V et al (2007) Process mining framework for software processes. In: Wang Q, Pfahl D, Raffo DM (eds) International conference on software process, software process dynamics and agility ICSP 2007, Minneapolis, 19–20 May 2007
Sayal M, Casati F, Dayal U, Shan M-C (2002) Business process cockpit. In: Proceedings of 28th international conference on very large data bases VLDB 2002, Hong Kong, 20–23 Aug 2002
Schiefer J, Jeng J-J, Bruckner RM (2003) Real-time workflow audit data integration into data warehouse systems. In: Ciborra CU et al (eds) Proceedings of the 11th European conference on information systems, ECIS 2003, Naples, 16–21 June 2003
van der Aalst WMP (2001) Re-engineering knock-out processes. Decis Support Syst 30(4):451–468
van der Aalst WMP (2011) Process mining: discovery, conformance and enhancement of business processes. Springer, Berlin/Heidelberg/New York
Vrhovnik M et al (2007) An approach to optimize data processing in business processes. In: Koch C et al (eds) Proceedings of the 33rd international conference on very large data bases, University of Vienna, Vienna, 23–27 Sept 2007
W3C (2007) Semantic annotations for WSDL and XML schema. Available: http://www.w3.org/TR/sawsdl/
Weerawarana S et al (2005) Web services platform architecture. Prentice Hall, Upper Saddle River
zur Muehlen M (2004) Workflow-based process controlling. Logos, Berlin
zur Muehlen M, Shapiro R (2009) Business process analytics. In: Handbook on business process management, vol 2. Springer, Berlin
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Wien
About this chapter
Cite this chapter
Radeschütz, S., Schwarz, H., Vrhovnik, M., Mitschang, B. (2013). A Combination Framework for Exploiting the Symbiotic Aspects of Process and Operational Data in Business Process Optimization. In: Özyer, T., Kianmehr, K., Tan, M., Zeng, J. (eds) Information Reuse and Integration in Academia and Industry. Springer, Vienna. https://doi.org/10.1007/978-3-7091-1538-1_2
Download citation
DOI: https://doi.org/10.1007/978-3-7091-1538-1_2
Published:
Publisher Name: Springer, Vienna
Print ISBN: 978-3-7091-1537-4
Online ISBN: 978-3-7091-1538-1
eBook Packages: Computer ScienceComputer Science (R0)