Use of data within government

I work for a consultancy which has a large number of public sector clients. Recently one of the directors said this key but brief Slack message

Data Quality is critical to all businesses and more so in public sector as Architects, Engineers and Consultants we should be at the forefront of the drive to improve DQ in everything we do.

He was saying this as the UK government has recently published the Government Data Quality Framework. This got me motivated to dig around and see what other guidance is currently provided by the government in regards to all things data. A very quick search came up with the following 5 bits of information.

1. The Government Data Quality Framework

An informative piece of guidance around a new framework for data quality management within Government, designed by the Government Data Quality Hub. It dives into why government should have a data quality framework, expressing that data is often of unknown or questionable quality which can lead to poorly informed decisions.

It is split into two parts:

1. Data quality principles, data lifecycle and data quality dimensions
2. Data quality action plans, root cause analysis, metadata guidance, communicating quality guidance and data maturity models.

Data Quality principles

I’m not going to summarise the whole of this framework and will limit it to the high level principles below:

• Commit to data quality - Create a sense of accountability, embed data management and governance, create a data quality capability.
• Know your users and their needs - Ensure data is fit for purpose by getting user needs and determining data quality requirements
• Assess quality throughout the data lifecycle - Adopt appropriate data quality tests and assessments throughout each stage of the data lifecycle, the earlier bad data is found the easier it is to fix.
• Communicate data quality clearly and effectively - Provide coherent data quality information and explain it’s impact, create standards and communicate them to all stakeholders involved. Generate data documentation and metadata
• Anticipate changes affecting data quality - Through communication, change management, perform analysis on system changes which may impact data quality and determine how that impacts downstream data users.

2. National Data Strategy - Policy Paper

Looks into how government can leverage data. This strategy consists of 4 core pillars:

1. Data Foundations - Ensure value can be got out of data by making it findable, accessible, interoperable and reusable whilst improving the quality of the data
2. Data Skills - Ensure data skills are delivered through the education system
3. Data Availability - Ensure data is accessible and encourage the sharing of data
4. Responsible Data - Ensure data is used ethically, lawfully, securely and fairly whilst being sustainable and accountable

From these pillars they have identified five key missions:

1. Unlocking the value of data across the economy.
2. Securing a pro-growth and trusted data regime.
3. Transforming government’s use of data to drive efficiency and improve public services.
4. Ensuring the security and resilience of the infrastructure on which data relies.
5. Championing the international flow of data.

Finally they’ve determined five key opportunities for data to improve the UK:

1. Boosting productivity and trade
2. Supporting new businesses and jobs
3. Increasing the speed, efficiency and scope of scientific research
4. Driving better delivery of policy and public services
5. Creating a fairer society for all

3. The Aqua Book: guidance on producing quality analysis for government

A good practice guide to those working with analysis and analytical models

4. Code of Practice for Statistics

Three pillars and respective principles for each one which should be followed when publishing data and statistics

1. Trustworthiness
   • Honesty and integrity
   • Independent decision making and leadership
   • Orderly release
   • Transparent processes and management
   • Professional capability
   • Data governance
2. Quality
   • Suitable data sources
   • Sound methods
   • Assured quality
3. Value
   • Relevance to users
   • Accessibility
   • Clarity and insight
   • Innovation and improvement
   • Efficiency and proportionality

5. Data Standards Authority

The Data Standards Authority (DSA) works to improve how the public sector manages data. The DSA does this by establishing standards to make it easier and more effective to share and use data across government.