Data Governance

Data is a critical raw material for the economy, public administration, and innovation, serving as a key enabler for the development of digital services, the improvement of policymaking, and the enhancement of competitiveness. The national data strategy currently under development focuses on creating a reliable, interoperable, and secure framework that enables the use of data from the public and private sectors, with full respect for fundamental rights and European values.

Data governance refers to the set of rules, institutional roles, and mechanisms that regulate access to, use of, and flow of data. It includes institutional structures at the national and European levels that support decisions regarding which data can be utilized, by which entities, for what purposes, and under what standards, taking into account sector-specific characteristics. In the European context, this approach is reinforced by regulatory tools such as the Data Act, the Open Data Directive, and the Data Governance Act, which promote the creation of a single data market.

The data strategy promotes the free availability of public sector data in machine-readable format, while adopting internationally recognized FAIR principles (Findability, Accessibility, Interoperability, and Reusability). This ensures that data does not remain isolated but is utilized within broader ecosystems of knowledge and innovation, fostering the development of innovative services, particularly in sectors such as mobility, energy, and health.

At the same time, emphasis is placed on developing modern data infrastructures and central governance mechanisms for the entire public administration, with the aim of improving the quality, efficiency, and transparency of services. Finally, particular emphasis is placed on the country’s participation in the development of Common European Data Spaces (CEDS), which facilitate the cross-border use and exchange of information. This approach strengthens European cooperation, promotes the digital single market, and creates new opportunities for digital transformation at the national and European levels.

The distinction between open and protected data is a key element of a modern data governance strategy. Open data includes public sector datasets that are freely available at no cost, in machine-readable format, allowing for their free reuse by citizens, businesses, and research institutions. Making this data available enhances transparency, accountability, and the development of new services, particularly by small and medium-sized enterprises and startups.

The value of open data is multiplicative, as it generates secondary benefits through interconnection and reuse. In this context, particular importance is attached to high-value datasets, such as geospatial, meteorological, statistical, or mobility data, which have particularly high economic and social value, as they can be reused by businesses, researchers, and public bodies to develop innovative services and applications.

The availability of open data through single access points, in Greece the national open data portal data.gov.gr, ensures that it is easy to search for and utilize this data, thereby strengthening the digital single market.

The data strategy is not limited to promoting openness but recognizes that a significant portion of public sector data has high economic and strategic value and cannot be made available without conditions. Protected data primarily concerns personal data, which is subject to strict protection rules, such as the General Data Protection Regulation (GDPR), as well as data subject to commercial or statistical confidentiality, which is covered by intellectual property rights.

The modern approach is not based on prohibiting use, but on the controlled exploitation of this data. Access to and reuse of such data are permitted under clear conditions that ensure a level playing field, prevent abuse, and protect their value and control, particularly for research and innovation purposes. At the same time, techniques such as anonymization and pseudonymization, as well as secure processing environments, allow for their exploitation in a fair and beneficial manner.

The primary objective of the data strategy is to establish a balanced framework that combines protection with the active use of data for the benefit of growth and innovation.

Data is the foundation for the development of Artificial Intelligence and the key factor determining the quality, reliability, and effectiveness of its applications. The competitiveness of the European Union and its member states depends mostly on the availability of large, high-quality, and interoperable datasets. Today, the main challenge is not only the quantity but primarily the fragmentation, uneven quality, and the limited reusability of data, which diminish their practical value.

The use of open data, combined with the development of Common European Data Spaces, is a key tool for addressing these limitations. These spaces create a framework for cooperation and data exchange in critical sectors such as health, energy, and mobility, facilitating their cross-border use and enabling the development of AI applications on a larger scale.

Open data can feed AI systems with large volumes of diverse information, enabling the detection of complex patterns and improving the accuracy of predictions. Through their analysis, AI can identify complex patterns and generate more accurate predictions, for example in natural disaster prevention or in optimizing production processes. The variety of data also helps reduce errors and biases, improving how models perform in real-world conditions.

At the same time, the development of AI cannot rely exclusively on open data. A broader governance framework is required that allows for the secure and controlled use of other categories of data. In this context, the data strategy treats data as a strategic resource and seeks to create an organized repository of information that can be utilized securely and consistently.

In this context, simplifying rules and creating coherent governance frameworks is critical for the broader adoption of AI. Greece is aligning with this direction by investing in infrastructure, high-value data, and governance mechanisms that enable the secure and effective use of data, thereby fostering innovation and a sustainable digital transition.