Data model used by the bluesky ecosystem.
A primary design goal of bluesky is to enable better research by recording rich metadata alongside measured data for use in later analysis. Documents are how we do this.
This repository contains the formal schemas for bluesky's streaming data model and some Python tooling for composing, validating, and transforming documents in the model.
For the full details and schema please see the data_model section. This is a very quick guide to where
you should look for / put different kinds of information
- Information about your sample that you know before the measurement → Start Document
- What experiment you intended to do → Start Document
- Who you are / where you are → Start Document
- References to external databases → Start Document
- The Data™ → Event Document
- Detector calibrations, dark frames, flat fields , or masks → Event Document (probably in its own stream)
- The shape / data type / units of The Data™ → Event Descriptor Document in the data_keys entry
- Anything you read from the controls system that is not device configuration → Event Document
- Device configuration data → Event Descriptor Document in the configuration entry
See https://bluesky.github.io/event-model for more detailed documentation.