lancedb-column-metadata

You can add column-level metadata to LanceDB tables by using the REST API to inspect the table schema and persist descriptive tags. This process automates annotating, grouping, and categorizing columns for governance and ML workflows.

Column metadata tagging in LanceDB works by reading the existing table schema via the REST API and merging updates. It applies semantic tags like field_type, model, project_id, and version to columns without overwriting existing values unless explicitly requested.

Yes, you can group versioned columns into logical families in LanceDB by applying semantic metadata tags. This allows you to categorize related columns across tables to support data discovery and ML governance workflows.

Applying column metadata in LanceDB does not overwrite existing values unless explicitly requested. The REST API merges updates safely, ensuring your governance and documentation processes preserve prior annotations during schema discovery.

To annotate LanceDB table schemas via the REST API, you need a connected LanceDB deployment and access to the table schema. The environment must support reading existing metadata and merging updates to persist column-level documentation.

You need to document column metadata for LanceDB ML workflows when managing schema discovery, governance, and data discovery. Tagging columns with semantic information like field_type and project_id ensures consistent documentation across versioned tables.