Enhancing data integrity in governance of collaborative research: blockchain, regulatory compliance, and challenges in Kenya and Africa
DOI:
https://doi.org/10.65466/9arkq638Keywords:
Data Integrity; Blockchain Governance; Collaborative Research; Regulatory Compliance; Agricultural Data SystemsAbstract
The increasing reliance on data-intensive collaborative research has intensified concerns regarding data integrity, governance, and regulatory compliance, particularly in multi-institutional and cross-border environments. This study critically examines how blockchain technology can enhance data integrity within collaborative research governance, with a focus on Kenya Agricultural and Livestock Research Organization (KALRO) and comparative African contexts. A qualitative systematic review methodology was employed, drawing on peer-reviewed journal articles (2022–2025) sourced from Scopus, Web of Science, African Journals Online (AJOL), and Google Scholar. Inclusion criteria focused on studies addressing blockchain, data governance, and regulatory compliance in research and data-intensive environments. Findings indicate that key challenges to data integrity include inconsistent data validation, fragmented data systems, jurisdictional regulatory conflicts, and weak enforcement of governance frameworks. While blockchain presents opportunities through immutability, traceability, and decentralized control, its application introduces tensions with legal frameworks such as the Kenya Data Protection Act (2019) and the General Data Protection Regulation, particularly regarding the right to erasure. Evidence from Kenyan and broader African studies demonstrates that permissioned blockchain systems, combined with smart contracts, can enhance auditability, enforce compliance, and mitigate disputes over data ownership in collaborative research. The study concludes that blockchain is not a standalone solution but a complementary governance tool that must be integrated with robust legal, institutional, and technical frameworks. It recommends the development of standardized data governance protocols, regulatory harmonization across jurisdictions, and capacity building within research institutions to ensure sustainable adoption.
References
Aldoseri, A., Al-Khalifa, K. N., & Hamouda, A. M. (2023). Re-Thinking Data Strategy and Integration for Artificial Intelligence: Concepts, Opportunities, and Challenges. Applied Sciences, 13(12), 7082. https://doi.org/10.3390/app13127082
Al-Mamun, A., Yan, F., & Zhao, D. (2021). SciChain: Blockchain-enabled Lightweight and Efficient Data Provenance for Reproducible Scientific Computing. In 2021 IEEE 37th International Conference on Data Engineering (ICDE) (pp. 1853–1858). IEEE. https://doi.org/10.1109/ICDE51399.2021.00166
Charles, W. M., Waal, M. B. van der, Flach, J., Bisschop, A., Waal, R. X. van der, Es-Sbai, H., & McLeod, C. J. (2024). Blockchain-Based Dynamic Consent and its Applications for Patient-Centric Research and Health Information Sharing: Protocol for an Integrative Review. JMIR Research Protocols, 13(1), e50339. https://doi.org/10.2196/50339
Chichaibelu, B. B., Baumüller, H., & Matschuck, M. A. (2023). Protecting the data of African agricultural producers: A review of national laws, compliance and perceptions. Law, Innovation and Technology, 15(2), 617–661. https://doi.org/10.1080/17579961.2023.2245673
GoK. (2019). The Data Protection Act [Laws of Kenya]. Government of Kenya. Retrieved from https://www.kentrade.go.ke/wp-content/uploads/2022/09/Data-Protection-Act-1.pdf
Grossman, R. L., Boyles, R. R., Davis-Dusenbery, B. N., Haddock, A., Heath, A. P., O’Connor, B. D., Resnick, A. C., Taylor, D. M., & Ahalt, S. (2024). A Framework for the Interoperability of Cloud Platforms: Towards FAIR Data in SAFE Environments. Scientific Data, 11(1), 241. https://doi.org/10.1038/s41597-024-03041-5
Hamba, L. A., Kangethe, B. M., & Odoyo, W. O. (2024). Empowering Sustainable Startups in Kenya Through Blockchain Technology. IC-ITECHS, 5(1), 1035–1038. https://doi.org/10.32664/ic-itechs.v5i1.1682
Hussain, M. I., Bhuiyan, K. I., Sumon, S. A., Akter, S., Hossain, M. I., & Akther, A. (2024). Enhancing Data Integrity and Traceability in Industry Cyber Physical Systems (ICPS) through Blockchain Technology: A Comprehensive Approach. Advances in Artificial Intelligence and Machine Learning; Review, 4(4), 2883–2907.
Li, W., Wu, J., Cao, J., Chen, N., Zhang, Q., & Buyya, R. (2021). Blockchain-based trust management in cloud computing systems: A taxonomy, review and future directions. Journal of Cloud Computing, 10(1), 1–34. https://doi.org/10.1186/s13677-021-00247-5
Nielsen, J., Flanagan, M., Gurrin, L. C., Thornton, J., & Mol, B. W. (2025). Concerns about data integrity across 263 papers by one author. Journal of Gynecology Obstetrics and Human Reproduction, 54(6), 102794. https://doi.org/10.1016/j.jogoh.2024.102794
Numajiri, H., & Hayashi, T. (2024). Analysis on open data as a foundation for data-driven research. Scientometrics, 129(10), 6315–6332. https://doi.org/10.1007/s11192-024-04956-x
Nyachiro, A., Ondimu, K., & Mafura, G. (2023). Adoption Strategy for Cloud Computing in Kenyan Research Institutions. International Journal of Innovative Research and Development, 12(2), 42–107. https://doi.org/10.24940/ijird/2023/v12/i2/FEB23001
Ondiek, J. O., & Onyango, G. (2024). Blockchain technologies in digital governance: The Kenyan experience with promoting public accountability. In The Routledge International Handbook of Public Administration and Digital Governance (pp. 112–124). Taylor and Francis Inc. https://doi.org/10.4324/9781003458081-9
Saleh, A. M. S. (2024). Blockchain for secure and decentralized artificial intelligence in cybersecurity: A comprehensive review. Blockchain: Research and Applications, 5(3), 100193. https://doi.org/10.1016/j.bcra.2024.100193
Ugochukwu, A. I., & Phillips, P. W. B. (2024). Open data ownership and sharing: Challenges and opportunities for application of FAIR principles and a checklist for data managers. Journal of Agriculture and Food Research, 16, 101157. https://doi.org/10.1016/j.jafr.2024.101157
Wen, B., Wang, Y., Ding, Y., Zheng, H., Qin, B., & Yang, C. (2023). Security and privacy protection technologies in securing blockchain applications. Information Sciences, 645, 119322. https://doi.org/10.1016/j.ins.2023.119322
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