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Managing Extended Organizations and Data Governance

  • Conference paper
Digital Enterprise Design and Management 2013

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 205))

Abstract

These last years, main IT companies have build software solutions and change management plans promoting data quality management within organizations concerned by the enhancement of their business intelligence system. These offers are closely similar data governance schemes based on a common paradigm called Master Data Management. These schemes appear generally inappropriate to the context of complex extended organizations. On the other hand, the community-based data governance schemes have shown their own efficiency to contribute to the reliability of data in digital social networks, as well as their ability to meet user expectations. After a brief analysis of the very specific constraints weighting on extended organization’s data governance, and of peculiarities of monitoring and regulatory processes associated to management control and IT within these, we propose a new scheme inspired by Foucaldian analysis on governmentality: the Panopticon data governance paradigm.

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Author information

Authors and Affiliations

  1. UMR 5221 CNRS, Montpellier, France

    Eric Buffenoir

  2. Montpellier Research Management, Montpellier University 2, Montpellier, France

    Isabelle Bourdon

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  1. Eric Buffenoir
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  2. Isabelle Bourdon
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Correspondence to Eric Buffenoir .

Editor information

Editors and Affiliations

  1. , CRG, Ecole Polytechnique, Palaiseau Cedex, 91128, France

    Pierre-Jean Benghozi

  2. , LIX / DIX, Ecole Polytechnique, Palaiseau Cedex, 91128, France

    Daniel Krob

  3. , Institut d'Economie et, Université de Nantes, Chemin de la Censive du Tertre, Nantes Cedex 3, 44322, France

    Frantz Rowe

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Buffenoir, E., Bourdon, I. (2013). Managing Extended Organizations and Data Governance. In: Benghozi, PJ., Krob, D., Rowe, F. (eds) Digital Enterprise Design and Management 2013. Advances in Intelligent Systems and Computing, vol 205. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37317-6_12

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  • DOI: https://doi.org/10.1007/978-3-642-37317-6_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37316-9

  • Online ISBN: 978-3-642-37317-6

  • eBook Packages: EngineeringEngineering (R0)

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