To help ensure that the open analytics taxonomy will enable data scientists to collect better data and model more effectively, we’ve created a set of core principles. Any new development or update will be checked against these principles.
The open analytics taxonomy should:
- Give data scientists the best possible data to work with for modeling.
- Be supported by tooling to implement it, with as little manual work as possible.
- Be covered by automated validation.
- Work for any website, web-app or app built on modern, well adopted frameworks.
- Be consistent across events, contexts, frameworks, and platforms.
- Have a clear intended instrumentation & modeling use for each element.
- Never create unnecessary complexity or inheritance.
These principles are a starting point and we’ll adapt them along the way if that proves to be necessary to reach the taxonomy goals. They are open to feedback and contribution.