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 lightweight, flexible, extensible, machine readable and human-intelligible metadata schema that does not depend on a specific ontology. The metadata schema for metadata of data files is based on the concept of data lakes where data is stored as they are. The purpose of the schema is to enhance data interoperability. The lack of interoperability of messy socio-economic datasets that contain a mixture of structured, semi-structured, and unstructured data means that many datasets are underutilized. Adding a minimum set of rich metadata and describing new and existing data dictionaries in a standardized way goes a long way to make these high-variety datasets interoperable and reusable and hence allows timely and actionable information to be gleaned from those datasets. The presented metadata schema OIMS can help to standardize the description of metadata. The paper introduces overall concepts of metadata, discusses design principles of metadata schemes, and presents the structure and an applied example of OIMS.