The European Union's Common Agricultural Policy (CAP) plays a central role in shaping agricultural policies that affect agriculture, the environment and rural communities. The evaluation of these policies is crucial to understand their effectiveness, sustainability and potential adjustments.
The evaluation of CAP 23-27 poses new challenges for the evaluators involved. Increased expectations of the evaluation as well as larger amounts of data require targeted solutions and tools to efficiently solve current problems.
The data-related challenges include the integration of heterogeneous data sources from various agriculture-related areas such as environmental data, socio-economic indicators and more. This data is often available in different formats, structures and qualities. In preparation, methods of data integration, cleansing and analysis must be developed in order to ensure the quality, consistency and analytical capability of this data.
As part of the Datenpool project, the BAB has accumulated a wide range of knowledge in these areas. This knowledge, which can be summarized under the interdisciplinary term of data science, is now to be used to support the evaluation of the CAP 23-27 measures in their work.
Objective
Creation and design of the architecture of the GAP 23-27 data pool, including conception and use cases of the evaluation and access systems. The aim is to create an efficient and accessible structure that provides the necessary data for the evaluation of CAP measures and at the same time enables easy use and analysis by authorised users.
Provide technical expertise and support to Department II/1 and those responsible for CAP measures 23-27 in the area of data modelling and data management. This includes the development and management of an effective data model and the implementation of best practices for data management to ensure that the CAP data pool contains high quality and reliable data.
Providing technical advice and support to those responsible for CAP interventions in relation to sourcing data, seamless transfer of supplier data to relevant interfaces, efficient storage, data processing and smooth delivery to the CAP data pool.
Establish methods for data security and integrity, including ways to comprehensively document all stored data under CAP measures 23-27.
The focus is on creating a solid database that best supports evaluation and provides evaluators with relevant, well-documented information.
Status of the project
The database structures for the GAP data pool have been designed and implemented. In addition, systems for synchronising the data from the BAB data pool and for transforming the data for the GAP data pool have already been successfully implemented.
Systems for data documentation are ready.
Planned work for 2025
- Data access restrictions will be implemented at user group level
- The GAP database will be integrated into compartmentalised processing systems such as JupyterHub
- In addition, data will be exported from the database largely automatically in user-friendly formats such as CSV, Parquet or DuckDB... to make it easier to use for less technically savvy people
- Access to exported data is provided via platforms such as Nextcloud or similar systems with access control (ACL)
Schedule
Project start: 01/2024
Project duration: CAP Strategic Plan 2023-2027 accompanying long-term project
