Examining Data Governance to Determine How Democratic Data Management Can Be Achieved in Organizations

In this age of data-driven decision-making and a data-centric environment, robust data governance is vital for organisational performance and for upholding democratic and fair data practices. Managing data is increasingly challenging with large volumes across systems, evolving regulations, diverse stakeholder interests, and different implementation methods. The research gap is embedded in the realization that data governance is crucial in any organisation, but its implementation faces the demand need to address the horizontal relationships among data providers. The research question is how can democratic data governance (DDG) be implemented by institutions and organisations to better serve the interests of data providers? Employing a systematic literature review, this study is steered by the populations, exposures, and outcomes (PEO) framework to define the review’s boundaries. The databases used were Web of Science, ProQuest, and EbscoHost. The PRISMA framework was used to ensure a transparent, structured, and exhaustive examination of the selected literature. The inclusion criteria are articles in English, and peer-reviewed literature specifically about democratic data governance. Through thematic analysis, this study explores the obstacles and opportunities of DDG implementation in the 27 articles included. The key findings are grouped into three themes; data-driven societal challenges, aspects of data governance needed for democratic data governance, and challenges with adapting data governance. Addressing the horizontal relationship between data providers contributes to the policy as it engages with GDPR. The research contributes to the body of knowledge on data governance and the role of privacy.