# Monitoring & learning

It is important to monitor the adoption and use of standards: particularly those with a policy goal. Through monitoring, and reflecting on adoption, there are opportunities to identify ways to improve the standard, it's documentation and associated tools, and to develop interventions that create a thriving ecosystem of publishers and users around a standard.

There are many different aspects to monitoring and learning:

* **Pipeline and publishers** - tracking how many organisations have expressed interest in the standard, started adopting it, or successfully published.

* **Validation** - tracking how much of the data produced is valid against the standards schema, or against additional rulesets, and identifying common interoperability issues.

* **Coverage** - tracking the relative levels of use for particular fields, data elements and codelists, as well as looking at the use of extensions or additional fields in standards that support this.

* **Quality and usability** - tracking whether data is clear, accurate and usable, and being put into use.

* **Community** - tracking the size and levels of activity in the community around the standard, identifying whether or not a market is emerging around it, and looking at the range of contributors to standard development. 

## Components

The following components are often used as part of a monitoring strategy.

```eval_rst

* :ref:`component-online-validator`
* :ref:`component-dashboard`
* :ref:`component-registry-of-datasets`

.. todo::

```

## Patterns

The following approaches can form part of a monitoring strategy:

* **Quality frameworks** - that can judge the 'level' of publication, and incentivise publishers to improve their data. 
* **Setting targets** - for the number of publishers, valid data, or number of community contributions. Measuring against targets can help keep engagement and implementations on track.
* **Individual publisher feedback reports** - offering an opportunity for regular deep-dive engagement with publishers.
* **Tool certification** - either self-certified, or with external certification - as a means to engage tool developers, check and learn from the way data is being used. 

```eval_rst

.. todo::

    Create patterns for each of the monitoring and learning elements

```