Towards a taxonomy of research areas in open government data
ISSN: 1468-4527
Article publication date: 20 April 2023
Issue publication date: 15 January 2024
Abstract
Purpose
This study aimed to develop a taxonomy of research areas in open government data (OGD) through a bibliometric mapping tool and a qualitative analysis software.
Design/methodology/approach
In this study, the authors extracted metadata of 442 documents from a bibliographic database. The authors used a bibliometric mapping tool for familiarization with the literature. After that, the authors used qualitative analysis software to develop taxonomy.
Findings
This paper developed taxonomy of OGD with three research areas: implementation and management, architecture, users and utilization. These research areas are further analyzed into seven topics and twenty-eight subtopics. The present study extends Charalabidis et al. (2016) taxonomy by adding two research topics, namely the adoption factors and barriers of OGD implementations and OGD ecosystems. Also, the authors include artificial intelligence in the taxonomy as an emerging research interest in the literature. The authors suggest four directions for future research: indigenous knowledge in open data, open data at local governments, development of OGD-specific theories and user studies in certain research themes.
Practical implications
Early career researchers and doctoral students can use the taxonomy to familiarize themselves with the literature. Also, established researchers can use the proposed taxonomy to inform future research. Taxonomy-building procedures in this study are applicable to other fields.
Originality/value
This study developed a novel taxonomy of research areas in OGD. Taxonomy building is significant because there is insufficient taxonomy of research areas in this discipline. Also, conceptual knowledge through taxonomy creation is a basis for theorizing and theory-building for future studies.
Keywords
Acknowledgements
The authors would like to acknowledge the valuable comments provided by reviewers in publishing this article. An earlier version of this paper was published at the Hawaii International Conference on Systems Sciences (Mohamad et al., 2022). The authors are grateful for the feedback received during the conference.
Erratum: It has come to the attention of the publisher that the article, Mohamad, A.N., Sylvester, A. and Campbell-Meier, J. (2023), “Towards a taxonomy of research areas in open government data”, Online Information Review, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/OIR-02-2022-0117, omitted author Mohamad, A.N's affiliation institution.
School of Information Science, Universiti Teknologi MARA, Shah Alam, Malaysia is the correct first affiliation and replaces School of Information Science, College of Computing, Informatics and Media, Shah Alam, Malaysia.
This error was introduced in the editorial process and has now been corrected in the online version. The publisher sincerely apologises for this error and for any inconvenience caused.
Citation
Mohamad, A.N., Sylvester, A. and Campbell-Meier, J. (2024), "Towards a taxonomy of research areas in open government data", Online Information Review, Vol. 48 No. 1, pp. 67-83. https://doi.org/10.1108/OIR-02-2022-0117
Publisher
:Emerald Publishing Limited
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