Coordinating Decision-Making in Data Management Activities: A Systematic Review of Data Governance Principles

Paul Brous, Marijn Janssen, R. Vilminko-Heikkinen

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

17 Citations (Scopus)

Abstract

More and more data is becoming available and is being combined which results in a need for data governance - the exercise of authority, control, and shared decision making over the management of data assets. Data governance provides organizations with the ability to ensure that data and information are managed appropriately, providing the right people with the right information at the right time. Despite its importance for achieving data quality, data governance has received scant attention by the scientific community. Research has focused on data governance structures and there has been only limited attention given to the underlying principles. This paper fills this gap and advances the knowledge base of data governance through a systematic review of literature and derives four principles for data governance that can be used by researchers to focus on important data governance issues, and by practitioners to develop an effective data governance strategy and approach.
Original languageEnglish
Title of host publicationProceedings of the International Conference on Electronic Government and the Information Systems Perspective
PublisherSpringer
Pages115-125
ISBN (Electronic)978-3-319-44421-5
ISBN (Print)978-3-319-44420-8
DOIs
Publication statusPublished - 2016
EventInternational Conference on Electronic Government and the Information Systems Perspective - Guimarães, Portugal
Duration: 5 Sep 20168 Sep 2016

Publication series

Name Lecture Notes in Computer Science (LNCS)
PublisherSpringer
Volume9820

Conference

ConferenceInternational Conference on Electronic Government and the Information Systems Perspective
Abbreviated titleEGOVIS 2016
CountryPortugal
CityGuimarães
Period5/09/168/09/16

Keywords

  • data governance
  • e-Governance
  • data quality
  • data management

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