Abstract
The discovery, representation and reconstruction of Business Networks (BN) from Network Mining (NM) raw data is a difficult problem for enterprises. This is due to huge amounts of fragmented data representing complex business processes within and across enterprise boundaries and heterogeneous technology stacks. To remain competitive, the visibility into the enterprise and partner networks on different, interrelated abstraction levels is desirable. We show the data management capabilities of a novel data discovery, mining and network inference system, called Business Network System (BNS) that reconstructs the BN - integration and business process networks - from raw data, hidden in the enterprises’ landscapes. The paper covers both the foundation and key data management characteristics of BNS.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
van der Aalst, W.: Process Mining: Discovery, Conformance and Enhancement of Business Processes (2011)
Abiteboul, S.: Distributed data management on the web. In: Datalog 2.0 Workshop, Oxford (2010)
Bizer, C., Heath, T., Berners-Lee, T.: Linked Data – The Story so Far. International Journal on Semantic Web and Information Systems 5(3), 1–22 (2009)
Bizer, C.: The Emerging Web of Linked Data. IEEE Intelligent Systems 24(5), 87–92 (2009)
Chowdhury, N.M.M.K., Boutaba, R.: Network virtualization: state of the art and research challenges. IEEE Communications Magazine (2009)
Hohpe, G., Woolf, B.: Enterprise Integration Patterns: Designing, Building, and Deploying Messaging Solutions. Addison-Wesley Longman, Amsterdam (2003)
Motik, B.: Using Datalog on the Semantic Web. In: Datalog 2.0 Workshop, Oxford (2010)
O’Neill, P., et al.: Topic Overview – IT Service Management. Technical Report, Forrester Research (2006)
Polleres, A.: Using Datalog for Rule-Based Reasoning over Web Data: Challenges and Next Steps. In: Datalog 2.0 Workshop, Oxford (2010)
Ritter, D., Ackermann, J., Bhatt, A., Hoffmann, F.O.: Building a business graph system and network integration model based on BPMN. In: Dijkman, R., Hofstetter, J., Koehler, J. (eds.) BPMN 2011. LNBIP, vol. 95, pp. 154–159. Springer, Heidelberg (2011)
Ritter, D.: From Network Mining to Large Scale Business Networks. In: International Workshop on Large Scale Network Analysis (WWW Companion), Lyon (2012)
Ritter, D.: The Business Graph Protocol. In: The 18th International Conference on Information and Software Technologies (ICIST), Kaunas (2012)
Ritter, D.: Towards a Business Network Management. In: The 6th International Conference on Research and Practical Issues of Enterprise Information Systems, Confenis, Ghent (2012)
Ritter, D., Rupprich, S.: A Data Quality Approach to Conformance Checks for Business Network Models. In: The 6th IEEE International Conference on Semantic Computing (ICSC), Palermo (2012)
Ritter, D.: A Logic Programming Approach for the Reconstruction of Integration Networks. In: The 26th Workshop on Logic Programming (WLP), Bonn (2012)
SAP Process Integration (2012), http://www.sap.com/germany/plattform/netweaver/components/pi/index.epx
SAP System Landscape Directory (2012), http://scn.sap.com/docs/DOC-8042
Ullman, J.D.: Principles of Database and Knowledge-Base Systems, vol. I. Computer Science Press (1988)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ritter, D. (2013). The Business Network Data Management Platform. In: Gottlob, G., Grasso, G., Olteanu, D., Schallhart, C. (eds) Big Data. BNCOD 2013. Lecture Notes in Computer Science, vol 7968. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39467-6_20
Download citation
DOI: https://doi.org/10.1007/978-3-642-39467-6_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-39466-9
Online ISBN: 978-3-642-39467-6
eBook Packages: Computer ScienceComputer Science (R0)