High Level List of Objectives:

• Implement a standard “evaluation” directory structure and high-level evaluation class to interact with it.
• Update the data schema to utilize the “concept of foreign keys” and include domain/emum tables, and schema and data validation to improve data integrity.
• Setup “cloneable” studies on S3 and convert existing “protocols” to v0.4 schema.
• Switch to Spark for data analytics to allow easier addition of more complex metrics including uncertainty bootstrapping.
• Add larger selection of metrics, including metrics that require user input (e.g., a threshold), and change the way users select which metrics to include to use Pydantic models that will provide a better user experience (i.e., autocomplete of metrics and options through and IDE/Jupyter)
• Add “teehr” DataFrame accessor and “attach” standard summary and plot methods to the DataFrames returned from get_xxx() methods.
• Drop unused features (web frontend and web API)