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Tim Davies
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Adding learning section
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docs/components/index.md

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#### Related Components
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#### Related Patterns
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```eval_rst
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.. _component-dashboard:
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```
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### Dashboard (data publication statistics)
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#### Summary
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A single location for accessing reports on the number of publishers, status of current publication, validation errors, coverage of key fields, use of extensions and other key facts.
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#### Description
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A dashboard helps to answer questions like:
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* Who is publishing using the standard?
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* How many publishers are using version 1.0 or 1.1?
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* How many publishers are using this specific field?
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* What values are used in this specific field?
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* Which codelists are publishers using?
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* Which are the most common validation errors?
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* If we deprecate a particular field, which publishers will be affected?
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#### Examples
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* The [IATI Dashboard](http://dashboard.iatistandard.org/) fetches changed data on a nightly basis (based on data in the IATI registry) and builds a collection of statistical reports, as well as maintaining historical data to show change over time.
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#### Prioritisation Factors
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#### Deprioritisation Factors
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#### Related Components
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```eval_rst
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* :ref:`component-registry-of-datasets`
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```
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#### Related Patterns
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docs/development/documentation.md

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# Documentation
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Documentation is a vital part of any standard. In general, policy related open data standards need both:
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* **Technical reference documentation**
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and
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* **Supporting documentation**
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These need to be approached differently, as the patterns below outline.
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## Sphinx for documentation
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We make use of Sphinx to build documentation. The [sphinx-base](https://github.com/OpenDataServices/sphinx-base) project is generally used as the starting point for this.
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```eval_rst
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.. todo::
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```
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## Documentation patterns
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```eval_rst

docs/development/licensing.md

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docs/learning/index.md

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# Learning
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# Monitoring & learning
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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.
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There are many different aspects to monitoring and learning:
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* **Pipeline and publishers** - tracking how many organisations have expressed interest in the standard, started adopting it, or successfully published.
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* **Validation** - tracking how much of the data produced is valid against the standards schema, or against additional rulesets, and identifying common interoperability issues.
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* **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.
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* **Quality and usability** - tracking whether data is clear, accurate and usable, and being put into use.
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* **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.
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## Components
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The following components are often used as part of a monitoring strategy.
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```eval_rst
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* :ref:`component-online-validator`
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* :ref:`component-dashboard`
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* :ref:`component-registry-of-datasets`
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.. todo::
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```
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## Patterns
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The following approaches can form part of a monitoring strategy:
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* **Quality frameworks** - that can judge the 'level' of publication, and incentivise publishers to improve their data.
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* **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.
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* **Individual publisher feedback reports** - offering an opportunity for regular deep-dive engagement with publishers.
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* **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.
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```eval_rst
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.. todo::
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Create patterns for each of the monitoring and learning elements
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```

docs/patterns/policy.md

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# Policy design patterns
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This is a list of potential 'design patterns' for Policy Related Open Data Standards.
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This page will contain a list of potential patterns related to policy design.
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## Drivers
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```eval_rst
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.. todo::
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## Drivers
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* Translating principles into practical action
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* Focus on data usability
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* Meeting multiple user needs: aligning stakeholders
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* Building ecosystem
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* Enabling co-ordination and collaboration
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* Translating principles into practical action
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* Focus on data usability
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* Meeting multiple user needs: aligning stakeholders
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* Building ecosystem
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* Enabling co-ordination and collaboration
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What problem is this addressing?
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What problem is this addressing?
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What implications does this have for standards design?
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What implications does this have for standards design?
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What implications for organizational strategy?
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What implications for organizational strategy?
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## Methods
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## Methods
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* Monolithic standard
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* Modular standard
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* Rankings
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* Technical levels
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* Use-cases
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* Central registry
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* Central identifiers
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* Implementation profiles
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## Discussion to foster
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What's the implication of these different choices?
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* Monolithic standard
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* Modular standard
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* Rankings
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* Technical levels
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* Use-cases
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* Central registry
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* Central identifiers
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* Implementation profiles
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```

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