FAIR data principles are fundamental to data science to enable open data. The implementation of FAIR principles requires robust metadata standards, such as the World Meteorological Organization (WMO) Integrated Global Observing System (WIGOS) Metadata Representation. The application of data science principles, however, remains a challenge. For example, the complexity of some physical measurements can make traditional ontological approaches ambiguous to use. In recent years, collaborations between physical scientists and data scientists have made strides towards more robust metadata standards. Two examples of this are through the Open Geospatial Consortium and Research Data Alliance InteroperAble Descriptions of Observable Property (I-ADOPT) who both have created frameworks to help bridge existing gaps and improve end-to-end data chains. This session intends to facilitate discussions on metadata standards and their practical application in different FAIR perspectives from data providers and users. This session also solicits presentations on machine-actionability use cases.

• IN - Informatics