A Flexible, Extensible, Machine-Readable, Human-Intelligible, and Ontology-Agnostic Metadata Schema (OIMS) - Kruseman, Gideon (Frontiers in Sustainable Food Systems, 2022)
This paper presents a light-weight flexible, extensible, machine readable and human-intelligible metadata schema that does not depend on a specific ontology. The purpose of the schema is to enhance data interoperability. The lack of interoperability of especially messy socio-economic data sets that contain a mixture of structured, semi-structured and unstructured data means that many data sets are underutilized. By adding a minimum set of rich metadata and describing new and existing data dictionaries in a standardized way goes a long way to making these high variety data sets interoperable and reusable and hence allows timely and actionable information to be gleaned from those datasets.