Interoperability of Integrated Administration and Control System (IACS) and LUCAS soil data at EU scale

Abstract The interoperability of agricultural data, particularly between the Common Agricultural Policy’s Integrated Administration and Control System (IACS) and the Eurostat’s Land Use and Coverage Area Frame Survey (LUCAS) topsoil datasets, is critical for advancing sustainable agricultural management and environmental policies in the European Union (EU). This work aims at developing a methodology and a validation framework for integrating soil and agricultural parcels data at the EU scale, using the commonly agreed approach of the European Interoperability Framework (EIF) and adhering to the Infrastructure for Spatial Information in Europe (INSPIRE) directive standards. In the EIF four layers (hereafter “dimensions”) of interoperability are defined as legal, organizational, semantic and technical. The proposed methodology combines systematic literature analysis carried out in SCOPUS and Web of Knowledge (PRISMA), policy review, and a technical and semantic interoperability test, employing Python and geospatial libraries (Pandas, GeoPandas, Psycopg2). The interoperability test, developed as a proof of concept, successfully integrated 11,542,238 agricultural parcels across Belgium (2009–2024) with 317 LUCAS topsoil data (2009–2018), establishing correspondences between 65 LUCAS land-cover classes and the hierarchical crop and agriculture taxonomy (HCAT) categories. Using the available IACS and LUCAS datasets and the proposed process, interoperability can be achieved for most EU Member States, except in a few cases where data are not yet available. The literature review revealed significant growth in peer-reviewed articles and policy documents, demonstrating the increasing interest toward interoperability after the EIF Communication (COM(2017) 134 final). A total of 82 publications were retrieved, showing a steady upward trend, particularly after 2020. The review of literature predominantly emphasizes the technical dimension while gradually recognizing the importance of organizational and semantic dimensions. Legal interoperability remains relatively underexplored, indicating a key area for future research. The proposed methodology demonstrates a concrete and reproducible workflow to technically and semantically integrate IACS parcel data (geometries and crops) and LUCAS topsoil properties under existing EU interoperability framework. The research highlights the effectiveness of current harmonization standards and data governance practices mandated by European frameworks. This work provides actionable insights and recommendations for enhancing interoperability strategies, supporting sustainable agriculture, and informing data-driven policies aligned with EU sustainability objectives. • Develops methodology to integrate EU-scale for agro-environmental data sources • Leverages European Interoperability Framework and INSPIRE standards • Python-based method ensures IACS-LUCAS interoperability • Enhance interoperability for sustainable agriculture, and EU policies • Generate actionable recommendations for real-world interoperability scenarios