Data Interoperability Using Smart Data Models and NGSI-LD for the Norwegian Agrifood Sector

The growing adoption of digital technologies in agriculture has led to a proliferation of heterogeneous data from sources such as drones, robotic platforms, and IoT sensors.However, the lack of interoperability across these data streams poses major challenges for integration into decision support systems.This paper presents an approach to harmonising such data using NGSI-LD and Smart Data Models, developed within the Norwegian research project SMARAGD.We demonstrate how domain-specific semantic models and linked data principles can be applied to standardise and enrich geospatial and temporal metadata across three key agritech domains: aerial imagery, robotic sensing, and environmental monitoring.The resulting information assets are integrated into a shared, FIWAREcompatible data space, enabling cross-platform visualisation, querying, and reuse.This work contributes to the development of an open, standards-based digital infrastructure for interoperable, data-driven agriculture in Norway and beyond.