Artifacts

What is an Artifact?

An artifact is a reusable result created by a plugin or workflow.

Examples include:

• a trained model;

• a prediction table;

• a training curve;

• an active-learning query batch;

• an image cutout;

• a spectrum or SED;

• an annotation summary;

• an exported report.

Artifact Metadata

An artifact may record:

• its type and identifier;

• the source dataset;

• related row identifiers;

• parameters used to create it;

• a small inline payload or a file location;

• additional provenance metadata.

Viewing Artifacts

Plugins can register viewers for artifact types. For example, a cutout artifact can be opened without repeating the original archive request.

Promoting an Artifact

A tabular artifact may be promoted into a dataset when it becomes a working input for later analysis.

Note

Artifacts are not live services. An API client belongs in context.services, while the result returned by that client normally belongs in context.artifacts.

Persistence

The artifact interface is designed for reusable outputs, but the exact persistence guarantees may depend on the current storage backend. Important research products should also be exported to a known project location.