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Abstract Automated processing of environmental data is hindered by the wide array of unit representations provided in the metadata of digital datasets. For example, gm/m2, g/m2, gm-2, g/m^2, g.m-2 and gramPerMeterSquared are all representations of a single complex unit that might be human-readable but are not machine-interpretable. Connectingad hocunits to a single unit concept in an ontology permits the identification of datasets sharing units and provides additional information regarding labels, definitions, dimensions and transformations provided in the ontology. Here we use successive string transformations to linkad hocunit representations to units in the QUDT ontology (e.g., unit: GM-PER-M2). Although only 896 of 7,110 distinct units in a corpus of ecological metadata from DataONE, the Environmental Data Initiative and the U.S. National Ecological Observatory Network were matched, 324,811 unit uses (instances) out of 355,057 of total unit uses were successfully mapped to QUDT units (91%). The resulting lookup table was used to enable a web service and R functions for adding annotation elements to Ecological Metadata Language documents. 

In the metadata of digital environmental datasets, automated processing is hindered by the wide variety of representations for unit that may be human-readable, but may not be unambiguous or machine-interpretable, (e.g., grams per square meter, gm/m2, g/m2, gm-2, g/m^2, g.m-2, g m-2 and gramPerMeterSquared). Matching disparate representations of the same unit into a single unit concept from an ontology assists with interpretation and reuse by providing a linkage to a complete unit definitions with label, description, dimensions. Datasets with shared units can be identified during searches, and are more suitable for automating analyses and potential transformation. This dataset contains data and code associated with a project to map units in ecological metadata collected between 2013 and 2022 by DataONE, the Environmental Data Initiative and the U.S. National Ecological Observatory Network to the QUDT ontology using successive string transformations. Data entities include a) raw metadata as received (355,057 unit instances); b) integrated raw data; c) substitution tables for string transformations; d) resulting lookup table for 896 distinct units matched to QUDT units; e) associated R code used for QUDT matching plus a web service and R functions for adding annotation elements to Ecological Metadata Language metadata documents. Using these substitutions and code, 91% of unit instances in the raw metadata could be matched to QUDT. Data and results are discussed in “Porter JH, M O’Brien, M Frants, S Earl, M Martin, C Laney. (in review) Using a Units Ontology to Annotate Pre-Existing Metadata. Submitted to Scientific Data.