For much of the tree of life, data on functional trait diversity and distributions are grossly incomplete. These trait data form links between the evolutionary history of organisms, their assembly into communities, and the functioning of ecosystems, with the need for functional trait data outstripping the speed at which they can be collected. Digitized paleo- and neo- biocollections records contain a trove of trait data measured directly from individuals, but this content remains hidden and highly heterogeneous, impeding discovery and use. Similarly, legacy trait data from decades of studies are locked in publication tables, plots, supplementary flat files, and unpublished author spreadsheets. The initial stage of FuTRES was a proof-of-concept that targeted body length and mass data found in already digitized specimen records, demonstrating that large scale extraction, harmonization, and re-provisioning of specimen-level trait data are possible. The critical next steps are to extend this work to gather other trait data from digitized records of all sorts, to engage the community of functional trait researchers to liberate legacy data, and to develop a more complete workflow for effective use of these data in research. FuTRES (Functional Trait Resource for Environmental Studies) is a workflow for assembling functional trait data measured at the specimen level, and a database to serve that data. It is based on a semantic model and is powered by extensible parsers, a backend database, and an API. A key aspect of FuTRES is the ability to collect, store, aggregate, and share data at the individual or specimen and higher levels without loss of information. FuTRES will provide access to trait data via popular data portals (e.g., VertNet) and software such as R, opening the data to scientists in biodiversity and other domains. The toolkit will be tested with mammalian use cases that leverage the massive scale of the unlocked data.