Data Protection#

Introduction#

The protection of Personally Identifiable Information (PII) has become a fundamental requirement for governments when implementing digital public infrastructure. Data is constantly being collected, processed, and shared within a country as well as across borders, making it crucial to implement strong data protection measures. While regulations such as the General Data Protection Regulation (GDPR) provide legal frameworks (or similar frameworks specific to the country), the focus should remain on the principles of responsible data management to build trust and ensure long-term digital security.

Data protection is not just a legal obligation. It is essential for maintaining privacy, security, and trust when Digital Public Infrastructure is implemented. Governments that fail to implement adequate safeguards risk exposing sensitive information, leading to financial losses, reputational damage, and legal consequences. Individuals, too, must be aware of how their data is used and have control over their personal information.

Key Principles of Data Protection#

Effective data protection relies on several core principles, including:

  1. Lawfulness, fairness, and transparency - Governments/organizations should collect and process personal data only for legitimate purposes. Transparency about data collection practices ensures that individuals understand how their information is used.

  2. Purpose limitation - Data should only be collected for specified, explicit, and legitimate purposes. Once the purpose is fulfilled, unnecessary data should not be retained.

  3. Data minimization - Governments/organizations should collect only the data that is strictly necessary for a given purpose. This reduces the risk of exposure and improves overall security.

  4. Accuracy - Ensuring that data remains accurate and up to date is essential. Inaccurate data can lead to incorrect decisions and potential harm to individuals.

  5. Storage limitation - Personal data should not be kept for longer than necessary. Governments/organizations should establish clear policies on data retention and secure deletion methods.

  6. Confidentiality and integrity - Data security must be prioritized through encryption, access controls, and cybersecurity best practices. Unauthorized access or breaches can have serious consequences.

  7. Accountability and compliance - Businesses and institutions must take responsibility for ensuring data protection. Regular audits, training, and clear policies help reinforce compliance.

Implementing Strong Data Protection Measures#

With the increasing importance of digital public infrastructure, Governments/organizations must take a proactive approach to protecting personal data. As an example, the General Data Protection Regulation (GDPR) establishes a framework that enforces strict standards for data collection, processing, and storage. Failure to comply with GDPR can lead to severe financial penalties, reputational damage, and loss of consumer trust. All stakeholders including governments, individuals all have a role in ensuring data is handled responsibly. By embedding security-by-design and privacy-by-design principles governments/organizations can minimize risks and uphold the rights of individuals.

Key measures include:

  1. Data protection by design and default - Security should be embedded into systems and processes from the outset rather than being added later. Privacy-focused design principles help minimize risks.

  2. Employee awareness and training - Human error is a leading cause of data breaches. Regular training ensures that employees understand data security protocols and how to handle sensitive information.

  3. Secure data transfers and encryption - Data in transit and at rest should be encrypted to prevent unauthorized access. Secure communication channels and strict access controls are essential.

  4. Third-party risk management - When working with vendors or service providers, organizations must ensure that they comply with data protection standards. Contracts should include clear security and compliance requirements.

  5. Regular risk assessments and audits - Conducting frequent risk assessments helps identify potential vulnerabilities. Internal audits ensure that data protection policies remain effective and up to date.

  6. Data minimization and retention policies – Collect only what’s necessary, store it securely, and delete it when it’s no longer needed. This limits exposure in case of a breach.

  7. Strong user authentication and authorization – Implement robust credential management, multi-factor authentication, and least-privilege access to reduce unauthorized data exposure.

  8. Incident response and breach notification plan – Have a clear roadmap for identifying, containing, and reporting security incidents. Quick response minimizes damage and demonstrates accountability.

  9. Transparency and user rights – Clearly communicate data practices and respect individuals’ rights (e.g., access requests, consent withdrawal). This enables trust and complies with regulatory requirements.

  10. Dedicated data governance team – Centralize oversight of data handling, ensuring policies are consistently applied and compliance is closely monitored.

The list above is a starting point but by no means exhaustive. Every government/organization has unique needs and risks, so these measures should be adapted and expanded based on context.

Exceptions to the Right to Erasure#

While individuals have the right to request the deletion of their personal data, certain situations require data to be retained for legal, public interest, or security reasons. These exceptions ensure that critical government functions, research, and legal obligations are not disrupted.

  • Governments and organizations are required to retain certain types of data for compliance with legal obligations. This applies to government databases and social registries, which store identity records and beneficiary information. Additionally, auditing and fraud prevention measures often necessitate the preservation of data for verification and accountability purposes..

  • Data retention is also allowed when necessary for public interest and research. This includes cases where information is needed for health and safety, such as tracking epidemics or maintaining medical records. Scientific, historical, or statistical research also relies on long-term data collection to generate valuable insights that benefit society.

  • Another key exception is the protection of legal rights. Data cannot be erased when it is required for legal claims, including fraud investigations and social protection disputes. Additionally, preserving evidence is crucial to ensuring fairness in legal proceedings, making data retention a necessity in such cases.

  • Certain public services, particularly those involving digital public infrastructure such as identity management, also rely on long-term data retention. National digital ID systems require records for identity verification, while welfare and social protection programs depend on accurate data to verify eligibility and ensure proper benefit distribution.

Finally, the right to erasure depends on whether data processing is based on consent or legal obligation. If data is collected solely based on consent, individuals can request its deletion unless an exemption applies. However, if data processing is mandated by law, organizations may be required to retain the data and deny erasure requests. Understanding these exceptions helps individuals and organizations balance privacy rights with broader societal and legal responsibilities.

Conclusion#

Data protection is a shared responsibility between governments/organizations and individuals. By adopting proper security practices and adhering to key principles, governments/organizations can enhance trust, improve compliance, and safeguard sensitive information.