Tier 3 model-based Monitoring, Reporting, and Verification systems require a large number of input data to calibrate, run and validate the applied models. The efficient and accurate sharing and use of those data requires systematic collection and storage, applying standard formats and vocabularies and aggregation or disaggregation at appropriate scales. Standardisation is at the basis of reusability, which is one of the FAIR principles, and is a prerequisite for interoperability and harmonisation, that is, those procedures which eventually can permit to minimize the errors, in case data collected with different standards is combined. MRV systems require data of soil, land use and management, and climate, as well as collected using different data collection techniques (in field, lab, remote sensing). The different domains require different standards and tooling, developed and maintained by different groups. This session explores data standardisation and harmonisation for Tier 3 model-based MRV (Monitoring, Reporting, and Verification) systems, which require large, diverse datasets for calibration, running, and validation. Efficient use and sharing of soil, land use, management, and climate data—collected via field, lab, or remote sensing—depend on systematic collection, standard formats, vocabularies, and appropriate aggregation or disaggregation. Standardisation underpins FAIR principles, enabling reusability, interoperability, and harmonisation, which reduce errors when combining datasets from different sources. The session presents recent advancements and best practices, with introductory presentations by experts covering MRV data assessment, benchmark sites, sampling design, and the operationalisation of standardised vocabularies. Participants will engage in breakout groups to discuss challenges and co-develop solutions, followed by a plenary wrap-up. The session aims to foster interaction among stakeholders and advance the alignment of standards and tools, supporting more reliable, efficient, and interoperable MRV systems for carbon and soil monitoring.
Fantappiè et al. (Thu,) studied this question.