"Low-tech" metadata schemas
For many use cases metadata concepts are complex. Producing and consuming such metadata involves sophisticated tooling, which implies a considerable technical threshold for adopting metadata-focused workflows.
The schemas provided here aim to lower this threshold with an approach to expressing rich and semantically precise metadata in relatively simple data structures -- data structures that can be reasonably read from files and processed in scripts with loops and conditionals, rather than requiring databases and specific query languages implemented in targeted libraries.
All schemas are implemented in LinkML, connecting to a rich ecosystem for data modeling, validation, and transformation. LinkML bridges between the worlds of structured data in plain text files, relational databases and knowledge graphs if and when needed, so metadata workflows can stay as simple as possible.
Latest schema releases
- Things (v1): foundational schema to describe any "thing"
Schema development
ALL CONTENT HERE IS UNRELEASED AND MAY CHANGE ANY TIME
- Thing schema
- Properties schema
- Identifiers schema
- Roles schema
- Spatial schema
- Temporal schema
- Provenance schema
- Data distribution schema
- DataLad dataset schema
- Scientific data distribution schema
See sources on GitHub
Knowledge base/graph dump specification
This specification is a companion of the Things schema and its derivatives and extensions. It defines a data structure for dumping arbitrarily complex information, expressed in these data models, in a version-controllable fashion directly on a filesystem.