Lehrstuhl für Empirische Pädagogik und Pädagogische Psychologie (EN)

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Knowledge Management

MUSING = MUlti – industry Sematic-based next generation business INtelliGence (01.04.2006 - 30.04.2010)

MUSING is an FP6-funded Integrated EU Research Project that develops and demonstrates technologies for the combined usage of both structured and unstructured data for Business Intelligence. Based on a SOA/BPM system that allows a dynamic orchestration and choreography of all the necessary services, MUSING increases the precision, consistency and agility of business decisions through knowledge management and information extraction technology, advanced predictive analytics and  intelligent access to third party data. Researchers in statistics, ontology, semantics and machine learning contribute to this field. In particular, MUSING addresses the fields of Financial Risk Management, Internationalisation Services, and IT Operational Risk Measurement and Mitigation.

Selected Publications

  • Spies, M., Schacher, M., & Gubser, R. (2010). Intelligent Regulatory Compliance. In R. Kenett & Y. Raanan (Eds.), Operational Risk Management: A practical approach to intelligent data analysis. (pp. 215-238). New York: Wiley.
  • Spies, M. (2010). An ontology modeling perspective on business reporting. Information Systems, 35(1), 404-416.
  • Leibold, C., Krieger, U., & Spies, M. (2010). Ontology based Modelling and Reasoning in Operational Risks. In R. Kenett & Y. Raanan (Eds.), Operational Risk Management: A practical approach to intelligent data analysis (pp. 41-60). New York: Wiley.
  • Spies, M. (2009). Towards modelling operational risks in service networks. In Italian Statistical Society (Ed.), Statistical Methods for the Analysis of large data sets (pp. 253-258). Padova: Cop. Libraria Editrice Università di Padova.
  • Spies, M. (2008). A model for assessment of organisational knowledge based on financial risk management In K. O'Sullivan (Ed.), Proc. 5th International Conference on Intellectual Capital, Knowledge Management & Organisational Learning (pp. 471-478). Reading, UK: Academic Publishing Ltd.
  • Graml, T., Bracht, R., & Spies, M. (2008). Patterns of business rules to enable agile business processes. Enterprise Information Systems, 2(4), 385 - 402.

Cooperation Partners

  • in Great Britain: University von Sheffield
  • in Israel:
    Tadiran Telecom – Communication Services in Israel LTDKenett – Preminger Associates LTD
  • in Romania: Numerica SA
  • in Germany: Verband der Vereine Creditreform e.V., NeussDeutsches Forschungszentrum für Kuenstliche Intelligenz GmbH
  • in Ireland: CI Consultancy LimitedUniversity von Limerick
  • in Austria: Leopold-Franzens-University, Innsbruck
  • in Belgium: European Business Register E.E.I.G.
  • in Italy: University of PisaUniversity of PaviaMPS.NET S.P.A.


Prof. Dr. Marcus Spies was technical director of this project in 2008-2010.