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Towards Federated, Semantics-Based Supply Chain Analytics

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Business Information Systems (BIS 2016)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 255))

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Abstract

Supply Chain Management aims at optimizing the flow of goods and services from the producer to the consumer. Closely interconnected enterprises that align their production, logistics and procurement with one another thus enjoy a competitive advantage in the market. To achieve a close alignment, an instant, robust and efficient information flow along the supply chain between and within enterprises is required. However, less efficient human communication is often used instead of automatic systems because of the great diversity of enterprise systems and models. This paper describes an approach and its implementation SCM Intelligence App, which enables the configuration of individual supply chains together with the execution of industry accepted performance metrics. Based on machine-processable supply chain data model (the SCORVoc RDF vocabulary implementing the SCOR standard) and W3C standardized protocols such as SPARQL, the approach represents an alternative to closed software systems, which lack support for inter-organizational supply chain analysis. Finally, we demonstrate the practicality of our approach using a prototypical implementation and a test scenario.

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Notes

  1. 1.

    https://scn.sap.com/community/developer-center/hana/blog/2014/12/10/sap-hana-sps-09-new-developer-features-rest-api, https://blogs.oracle.com/stevenChan/entry/introducing_oracle_e_business_suite.

  2. 2.

    Linked valUe ChaIn Data, http://www.lucid-project.org/.

  3. 3.

    https://www.w3.org/Press/RDF.

  4. 4.

    http://www.apics.org/sites/apics-supply-chain-council/frameworks/scor.

  5. 5.

    https://github.com/vocol/scor/blob/master/scor.ttl.

  6. 6.

    https://www.w3.org/TR/html5/.

  7. 7.

    http://jquery.com/.

  8. 8.

    http://visjs.org/.

  9. 9.

    https://github.com/EIS-Bonn/SCMApp.

  10. 10.

    https://www.eccenca.com/en/products/linked-data-suite.html.

  11. 11.

    http://tools.ietf.org/html/rfc6749.

  12. 12.

    https://vocab.eccenca.com/auth/.

  13. 13.

    https://rawgit.com/EIS-Bonn/SCMApp/master/scm-app.html.

  14. 14.

    http://www.gartner.com/newsroom/id/3050617.

  15. 15.

    http://help.sap.com/saphelp/_scm700/_ehp03/helpdata/en/58/d4cc537cbf224be10000000a174cb4/frameset.htm.

  16. 16.

    http://www.gs1.org/edi.

  17. 17.

    http://www.iso.org/iso/standards_development/technical_committees/list_of_iso_technical_committees/iso_technical_committee.htm?commid=54158.

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Acknowledgments

This work has been supported by the German Ministry for Education and Research funded project LUCID, and by the European Commission under the Seventh Framework Program FP7 for grant 601043 (http://diachron-fp7.eu).

Author information

Authors and Affiliations

  1. Fraunhofer Institute for Intelligent Analysis and Information Systems (IAIS), Sankt Augustin, Germany

    Niklas Petersen, Christoph Lange & Sören Auer

  2. Enterprise Information Systems (EIS), University of Bonn, Bonn, Germany

    Niklas Petersen, Christoph Lange & Sören Auer

  3. University of Leipzig, Leipzig, Germany

    Marvin Frommhold

  4. eccenca GmbH, Leipzig, Germany

    Marvin Frommhold & Sebastian Tramp

Authors
  1. Niklas Petersen
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  2. Christoph Lange
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  3. Sören Auer
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  4. Marvin Frommhold
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  5. Sebastian Tramp
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Corresponding author

Correspondence to Niklas Petersen .

Editor information

Editors and Affiliations

  1. Department of Information Systems, Poznan Univ of Economics and Business, Poznan, Poland

    Witold Abramowicz

  2. Institut für Wirtschaftsinformatik, Universität Leipzig, Leipzig, Sachsen, Germany

    Rainer Alt

  3. Information System Institute, University of Leipzig, Leipzig, Germany

    Bogdan Franczyk

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Petersen, N., Lange, C., Auer, S., Frommhold, M., Tramp, S. (2016). Towards Federated, Semantics-Based Supply Chain Analytics. In: Abramowicz, W., Alt, R., Franczyk, B. (eds) Business Information Systems. BIS 2016. Lecture Notes in Business Information Processing, vol 255. Springer, Cham. https://doi.org/10.1007/978-3-319-39426-8_34

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