# Metrics in Beta

Our goal is to provide high quality, mathematically sound and vetted metrics in the SDMetrics library, and we recognize that synthetic data is a new space undergoing active research. So to encourage discussion and collaboration, we've introduced a metrics in Beta section for anyone wanting to explore with us.

We envision many new metrics may start out in Beta before being validated and adopted by the wider community. 

## What can cause a metric to be in Beta?

A metric can be experimental for many reasons, including the ones below.

**The mathematical concepts are too new.** Synthetic data is an area of active research. The research might be so new that it would benefit from more validation through the open source community before wider adoption.

**The metric isn't robust.** Some metrics may not be reliable for every dataset. They may fluctuate widely based on built-in randomness or they may heavily depend on external algorithms that aren't optimized for every dataset.

**The interpretation isn't clear.** Metric scores should have a clear interpretation. Even if a metric uses a well-known mathematical method, it may lack clarity in the context of synthetic data. It may be possible to "trick" the metric or there may be multiple, conflicting interpretations for it.

## FAQs

<details>

<summary>What is the process upgrading these metrics from Beta?</summary>

We can upgrade some metrics from Beta after addressing the underlying concern. For example:

* If the metric has multiple interpretations it may make sense to split it into 2 metrics (one for each interpretation)
* If the metric is highly variable based on an external algorithm, there may be other basic, statistics that are not as variable.&#x20;

You are welcome to start a discussion about a metric in Beta. To get started, please [visit our forum](https://forum.datacebo.com/).

If you'd like to contribute changes, see the [Contributions](https://docs.sdv.dev/sdmetrics/resources/contributions) section.

</details>