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Interoperability between LUCAS and IACS
The interoperability of agricultural data, particularly between the Integrated Administration and Control System (IACS) and the 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 these heterogeneous data sources at the EU scale. Utilizing the European Interoperability Framework (EIF) and adhering to INSPIRE directive standards, the research combines comprehensive literature analysis, policy review, and a practical interoperability test. The literature review carried out in SCOPUS and Web of Knowledge revealed significant growth in research and policy interest toward interoperability, predominantly emphasizing technical standards while gradually recognizing the importance of organizational and semantic dimensions. Legal interoperability remains relatively underexplored, indicating a key area for future research. The methodology, employing Python and geospatial libraries (Pandas, GeoPandas, Psycopg2), demonstrates successful semantic and technical interoperability between IACS agricultural parcel (AP) data and LUCAS topsoil properties. Key challenges identified include semantic inconsistencies, variations in ontology adoption, and organizational and regulatory complexities. Nonetheless, the study underscores the effectiveness of existing harmonized standards and data governance practices mandated by European frameworks. This work provides actionable insights and recommendations for enhancing interoperability strategies, supporting sustainable agriculture, optimizing resource utilization, and informing data-driven environmental policies aligned with EU sustainability objectives.
2026-06-01
ELSEVIER SCI LTD
JRC143452
1873-2267 (online),   
https://www.sciencedirect.com/science/article/pii/S2949911926000110,    https://publications.jrc.ec.europa.eu/repository/handle/JRC143452,   
10.1016/j.farsys.2026.100207 (online),   
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