Impact of the General Data Protection Regulation on national regulation of scientific research and statistics
Impact of the General Data Protection Regulation on national regulation of scientific research and statistics
Impact of the General Data Protection Regulation on national regulation of scientific research and statistics
Impact of the General Data Protection Regulation on national regulation of scientific research and statistics
Summary of key points:
Scientific research and statistics have a significant social and economic value. It is, therefore, important that research and statistics can also utilize personal data, while ensuring data confidentiality. If this type of data is left unused, we might lose the possibility to achieve results that have a direct impact on, for example, well-being and health. However, adequate privacy and data security must be ensured. CSC supports the restrictions and the protections of the restrictions set out in the report under Article 89 (2). It is essential that in national legislation relating to the application of the Regulation, the national margin allowed by the Regulation is sufficiently utilized in regards to Article 89.
- The national data protection regulation should enable the seamless cooperation between the data owner, data repository, and the data user along with enabling the interoperability of their services. Research also requires that the archives, libraries, museums and research infrastructures serving public interest operate seamlessly. National data protection regulation should enable this.
- In accordance with the General Data Protection Regulation, data protection aspects must be ensured by default and by design in processes and tools. This must be visible when implementing the Regulation on the national level.
- CSC suggests that when implementing the General Data Protection Regulation on the national level, the assessment of data security risks of information systems and processes used for handling data is carefully taken into account.
- It is imperative to create principles for the minimization, pseudonymization, and anonymization of data in a way that maintains the balance between freedom and openness of research as well as the confidentiality of individuals under research.