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KSA PDPL – Article 27 (Data Processing for Scientific, Research, and Statistical Purposes without Consent)

KSA PDPL – Article 27

Abstract Of KSA PDPL – Article 27

This paper explores Article 27 of the Kingdom of Saudi Arabia Personal Data Protection Law (KSA PDPL), which permits the collection and processing of personal data for scientific, research, and statistical purposes without the data subject’s consent under specific conditions. The paper discusses the key provisions of the article, including the anonymity of the data subject, the destruction of identity evidence, and legal or contractual obligations for processing such data. This work further outlines strategic steps and technologies required to comply with the regulations of this article, providing practical insights for organizations involved in research and data processing.

PDPL provides for restrictions on the use of non-anonymized sensitive data for scientific, research,
or statistical purposes (as per Art. 27 of the PDPL).

Keywords

KSA PDPL; Article 27; Data Privacy; Data Processing; Research Data; Scientific Data; Data Anonymization

Introduction Of KSA PDPL – Article 27

The Kingdom of Saudi Arabia’s Personal Data Protection Law (PDPL) has established a comprehensive framework for safeguarding personal data, balancing the need for data protection with the requirements of research and scientific progress. Article 27 of the KSA PDPL specifically addresses situations where personal data may be collected or processed for scientific, research, or statistical purposes without the consent of the data subject. This article sets forth conditions that ensure the data subject’s privacy is respected while enabling necessary data activities for societal and academic advancement. This paper aims to provide an in-depth analysis of Article 27, its strategic implications, and the key methodologies for enabling compliant data processing practices.

Explanation Of KSA PDPL – Article 27

Article 27 of the KSA PDPL allows personal data to be collected or processed for scientific, research, or statistical purposes under three key conditions: if it does not specifically identify the data subject, if the data subject’s identity is destroyed before disclosure to other entities, and if such data collection or processing is required by law or a prior agreement involving the data subject. These conditions ensure that while personal data can be used for critical research purposes, privacy is maintained.


Detailed Discussion Of KSA PDPL – Article 27

Key Strategic Points

The strategic points involved in implementing Article 27 include understanding the conditions under which data processing is allowed without consent, ensuring the anonymity of data subjects, and determining legal obligations. Organizations must ensure compliance with the provisions of the article while enabling the use of personal data in scientific research.

General Activation Steps

  • Identify the data to be collected and processed for research purposes.
  • Ensure that the data does not directly identify any data subject.
  • Develop a process to destroy any identifying information prior to data disclosure.
  • Verify that data processing is either mandated by law or covered by a prior agreement.
  • Ensure compliance with any additional regulations specified by the PDPL regarding the use of sensitive data.

Enablement Methodology Of KSA PDPL – Article 27

Enablement of Article 27 compliance requires organizations to develop robust data anonymization and de-identification techniques. This can be achieved through data masking, encryption, and the adoption of technologies that ensure personal data remains non-identifiable before disclosure. Additionally, organizations must implement policies that define the destruction of identifiable data and ensure such practices are auditable.

Use Cases

Several use cases demonstrate the importance of Article 27, such as in public health research, where data on large populations is required but individual privacy must be maintained. Another example is academic research where data from multiple sources is combined, and the data subjects must remain anonymous.

Dependencies

  • Compliance with other legal frameworks, both national and international.
  • Access to appropriate anonymization and de-identification technologies.
  • Strong internal policies for data handling, anonymization, and destruction of identity markers.

Tools/Technologies

  • Data anonymization software such as ARX or SDC Micro.
  • Encryption tools to protect data during processing.
  • Data masking technologies that allow sensitive information to be hidden.
  • Auditing tools to ensure compliance with Article 27’s destruction requirements.

Challenges & Risks Of KSA PDPL – Article 27

  • Difficulty in fully anonymizing data, especially in complex data sets.
  • Risk of re-identification if anonymization is not properly implemented.
  • Ensuring compliance with data protection laws across jurisdictions.
  • Balancing the need for detailed data in research with privacy concerns.

Conclusion

Article 27 of the KSA PDPL plays a critical role in allowing the advancement of research and scientific knowledge without compromising the privacy of individuals. By setting out clear conditions under which personal data can be processed without consent, the law provides a framework that balances the needs of researchers and the rights of data subjects. Organizations involved in research must adopt robust anonymization and de-identification practices to ensure compliance with Article 27 while continuing to pursue valuable scientific discoveries.


References

Saudi Data & Artificial Intelligence Authority (SDAIA). (2023). Kingdom of Saudi Arabia Personal Data Protection Law (PDPL). https://sdaia.gov.sa/ndmo/pdpl.html
Alzahrani, H. (2022). Data Privacy and Security Regulations in Saudi Arabia: An Overview of the PDPL. Journal of Middle Eastern Studies, 15(2), 12-30.


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Things</a> </li> <li class="cat-item cat-item-43"><a href="https://mdmteam.org/category/iso-iec-27001/">ISO/IEC 27001</a> </li> <li class="cat-item cat-item-20"><a href="https://mdmteam.org/category/databases/json-database/">JSON Database</a> </li> <li class="cat-item cat-item-25"><a href="https://mdmteam.org/category/databases/nosql/key-value-database/">Key-Value Database</a> </li> <li class="cat-item cat-item-24"><a href="https://mdmteam.org/category/databases/nosql/key-value-store/">Key-Value Store</a> </li> <li class="cat-item cat-item-46"><a href="https://mdmteam.org/category/data-modeling/knowledge-modeling/">Knowledge Modeling</a> </li> <li class="cat-item cat-item-32"><a href="https://mdmteam.org/category/kpis/kpi-key-performance-indicator/">KPI – Key Performance Indicator</a> </li> <li class="cat-item cat-item-31"><a href="https://mdmteam.org/category/kpis/">KPIs</a> </li> <li class="cat-item cat-item-84"><a 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href="https://mdmteam.org/ksa-ndmo-personal-data-protection-pdp-plan-pdp-1-2-p1/">KSA NDMO – Personal Data Protection – PDP Plan – PDP.1.2 P1</a> </li> <li> <a href="https://mdmteam.org/ksa-pdpl-article-8-processor-selection-and-monitoring/">KSA PDPL – Article 8 (Processor Selection and Monitoring)</a> </li> <li> <a href="https://mdmteam.org/ksa-pdpl-article-5-data-subject-consent-and-withdrawal-rights/">KSA PDPL – Article 5 (Consent Management and Withdrawal Mechanism)</a> </li> <li> <a href="https://mdmteam.org/ksa-pdpl-article-6-exemptions-from-consent-for-data-processing/">KSA PDPL – Article 6 (Exemptions from Consent for Data Processing)</a> </li> <li> <a href="https://mdmteam.org/ksa-ndmo-personal-data-protection-pdp-training-pdp-2-1-p1/">KSA NDMO – Personal Data Protection – PDP Training – PDP.2.1 P1</a> </li> </ul> </div></div> </div> </div> <div class="copy"> <div class="container"> <div class="row"> <div class="col-md-6"><p>Copyright © 2025 <a href="https://mdmteam.org/" 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