Essential Biodiversity Variables (EBVs) are state variables that lie between primary measurements and high-level indicators, and are necessary for assessment of the health and prognosis of Earth’s biosphere. EBVs represent the complete spectrum of biological diversity from genes to ecosystems, and so are based on observations which themselves are highly diverse, and typically human-collected or analyzed. What is now sorely needed are structured dictionaries of biological measurements that data collectors, curators and nascent biodiversity programs can reference at all stages of planning and data organization. Similarly, analysts working with data defined according to these measurement dictionaries, require assurance that their results are comparable across scales and institutions. Full understanding of primary measurements will ideally require machine-readable, interpretable, and interoperable descriptions of the measurement contents, collection methods, data-typing, dimensions and associated units for physical quantities, and specification of appropriate temporal and spatial scales, plus the relationships among those attributes and facets of the ecosystem. Formal ontologies, i.e. vocabularies built using modern Semantic Web technologies, now provide the ideal tools and protocols for structuring and operationalizing EBV primary measurements. Here we illustrate an approach to apply these to existing data sets (both primary and harmonized intermediates) using community-accepted measurement ontologies under development. Such techniques can streamline the discovery and integration of observations, assist with calibration/validation checks required for automated or remote data collection, and enable rigorous structured definitions for modeled or remotely-sensed EBVs as these are developed.