Integrating Agricultural Semantic Models with Data Spaces for Enhanced Interoperability

摘要

Digitalization is transforming agriculture by boosting productivity, sustainability, and efficiency. Yet, the potential of technologies like IoT, AI, Big Data analytics, and robotics is limited by interoperability challenges, including fragmented data sources and heterogeneous models. In this work, we explore how data spaces can enhance interoperability and secure data sharing in agriculture. Within the AgriDataValue (ADV) project, we leverage the Agricultural Information Model (AIM) and integrate it with the International Data Spaces (IDS) Information Model. Our approach adapts AIM in pilot activities and establishes mappings to IDS, aiming to develop a unified ADV data model for seamless cross-pilot data sharing. By promoting standardized data models and governance frameworks, data spaces foster collaboration, improve decision-making, and drive sustainable, data-driven innovation in the agri-food sector. We demonstrate, in the context of ADV, how data spaces are able to reimagine agricultural ecosystems in a manner that promotes sustainability, efficiency, and innovation.