A Systematic Review of Recent Literature on Data Governance (2017-2023)
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F24%3A39922242" target="_blank" >RIV/00216275:25410/24:39922242 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10707270" target="_blank" >https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10707270</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ACCESS.2024.3476373" target="_blank" >10.1109/ACCESS.2024.3476373</a>
Alternative languages
Result language
angličtina
Original language name
A Systematic Review of Recent Literature on Data Governance (2017-2023)
Original language description
In today's rapidly changing environment, organizations are fighting a decisive battle for the most effective use of data. Owing to technological innovation, the volume, velocity, variety, variability, and veracity of data gathered, stored, and processed by organizations in electronic systems are rapidly growing. Analytics, process mining, and artificial intelligence are among the modern application domains of data, enabling data-driven decision making and process innovation for an operating advantage. Data governance, encompassing standards, policies, responsibilities, and relations for managing data, is essential for organizations to maximize the value of the use of data in an effective, cost-efficient, safe, and compliant way. Although data governance has matured as a scientific and business discipline in recent years, the formal definition of data governance and its implementation practices in organizations are still facing ambiguity. New regulations in data protection (e.g., the European Union's General Data Protection Regulation) and safe and ethical data processing (e.g., the European Union's Artificial Intelligence Act) further increase the pressure for compliance and conformity in organizations' management of their data assets. Applying the systematic literature review approach, our objective was to capture state-of-the-art data governance research. The literature review provides an incremental analysis of the most relevant published work on data governance in the period from 2017 to 2023, complementing and enhancing previous systematic literature reviews. The study examines in detail 38 publications, refreshing scientific knowledge and providing further orientation for a growing community of scholars and practitioners in the dynamically evolving data governance discipline.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10200 - Computer and information sciences
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
IEEE ACCESS
ISSN
2169-3536
e-ISSN
2169-3536
Volume of the periodical
12
Issue of the periodical within the volume
Neuveden
Country of publishing house
US - UNITED STATES
Number of pages
14
Pages from-to
149875-149888
UT code for WoS article
001338158500001
EID of the result in the Scopus database
2-s2.0-85207292347