IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v10y2018i1p95-d125163.html
   My bibliography  Save this article

Data Governance Taxonomy: Cloud versus Non-Cloud

Author

Listed:
  • Majid Al-Ruithe

    (Cloud Computing and Applications Research Lab, School of Computing and Digital Technologies, Staffordshire University, Stoke-on-Trent ST4 2DE, UK)

  • Elhadj Benkhelifa

    (Cloud Computing and Applications Research Lab, School of Computing and Digital Technologies, Staffordshire University, Stoke-on-Trent ST4 2DE, UK)

  • Khawar Hameed

    (Cloud Computing and Applications Research Lab, School of Computing and Digital Technologies, Staffordshire University, Stoke-on-Trent ST4 2DE, UK)

Abstract

Forward-thinking organisations believe that the only way to solve the data problem is the implementation of effective data governance. Attempts to govern data have failed before, as they were driven by information technology, and affected by rigid processes and fragmented activities carried out on a system-by-system basis. Until very recently, governance has been mostly informal, with very ambiguous and generic regulations, in siloes around specific enterprise repositories, lacking structure and the wider support of the organisation. Despite its highly recognised importance, the area of data governance is still underdeveloped and under-researched. Consequently, there is a need to advance research in data governance in order to deepen practice. Currently, in the area of data governance, research consists mostly of descriptive literature reviews. The analysis of literature further emphasises the need to build a standardised strategy for data governance. This task can be a very complex one and needs to be accomplished in stages. Therefore, as a first and necessary stage, a taxonomy approach to define the different attributes of data governance is expected to make a valuable contribution to knowledge, helping researchers and decision makers to understand the most important factors that need to be considered when implementing a data governance strategy for cloud computing services. In addition to the proposed taxonomy, the paper clarifies the concepts of data governance in contracts with other governance domains.

Suggested Citation

  • Majid Al-Ruithe & Elhadj Benkhelifa & Khawar Hameed, 2018. "Data Governance Taxonomy: Cloud versus Non-Cloud," Sustainability, MDPI, vol. 10(1), pages 1-26, January.
  • Handle: RePEc:gam:jsusta:v:10:y:2018:i:1:p:95-:d:125163
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/10/1/95/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/10/1/95/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Eric Buffenoir & Isabelle Bourdon, 2012. "Reconciling complex organizations and data management," Working Papers hal-00744410, HAL.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. repec:mth:ijmis8:v:4:y:2019:i:1:p:1-19 is not listed on IDEAS
    2. Marzieh Derakhshannia & Carmen Gervet & Hicham Hajj-Hassan & Anne Laurent & Arnaud Martin, 2020. "Data Lake Governance: Towards a Systemic and Natural Ecosystem Analogy," Future Internet, MDPI, vol. 12(8), pages 1-16, July.
    3. Patricia Ordóñez de Pablos & Miltiadis Lytras, 2018. "Knowledge Management, Innovation and Big Data: Implications for Sustainability, Policy Making and Competitiveness," Sustainability, MDPI, vol. 10(6), pages 1-7, June.
    4. Olena Liakh, 2021. "Accountability through Sustainability Data Governance: Reconfiguring Reporting to Better Account for the Digital Acceleration," Sustainability, MDPI, vol. 13(24), pages 1-18, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Haneem, Faizura & Kama, Nazri & Taskin, Nazim & Pauleen, David & Abu Bakar, Nur Azaliah, 2019. "Determinants of master data management adoption by local government organizations: An empirical study," International Journal of Information Management, Elsevier, vol. 45(C), pages 25-43.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:10:y:2018:i:1:p:95-:d:125163. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.