EThis article describes the evolution of the Glossary of Digital Learning into a linked data resources that can be accessed by algorithms and data models. "Each concept now has a stable identity, source provenance, machine-readable JSON-LD and Turtle representations, and a place within a queryable semantic model." I get the intent of this - we want the model to depend on a reliable data set to inform its understanding of basic terms and concepts. What concerns me (and it is a theoretical concern only; I have no particular issues with this glossary) is how we come to define and formalize these terms and concepts. Do we leave it to expert bodies to define them a priori? Do we employ a mechanism that bases the definitions in actual usage? Is a semantical representation the best way to do this, or does it create sharp edges where fuzziness would be preferred?
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