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A short guide to artificial intelligence (AI), data science and machine learning, explaining the terminology and helping you use and apply the latest advances.
This notice sets out how we will use your personal data, and your rights.
Spreadsheets are a common way to share data. Use this information to help you avoid common errors, improve interoperability and create more accessible spreadsheets.
Consistent and standards-based comma-separated values (CSV) files help make data more effective and easier to share across government.
Use data more effectively by improving your technology, infrastructure and processes.
This page collates the various existing ethical principles for data and AI, developed by government and public sector sector bodies. It intends to provide clarity and guidance for public servants working with data and/or AI.
A simple guide to understanding and describing the trustworthiness of autonomous systems and associated artificial intelligence (AI) algorithms.
Use a reference architecture to develop a public sector organisation’s technology and how it shares data across government.
Description of the dataset showing the area of the ground that might be affected if subsidence a mine entry occurs.
Description of the data set showing known locations where a coal seam is near the surface.
A mission statement setting out the UK approach to adequacy assessments and international data transfers, along with the UK manual for undertaking assessments, guidance for the UK manual for undertaking assessments and a map…
How to choose data tools and infrastructure that are flexible, scalable, sustainable and secure.
These standards should be used for publishing geospatial data in accordance with the National Data Strategy and in compliance with the recommendations of the Data Standards Authority.
Sets out the role and approach of the DSA to improve the adoption of common data standards across government over the next 3 years.
A simple guide and framework for thinking about artificial intelligence (AI) and autonomy from a systems perspective.
Description of the data set showing underground coal workings whose depth is 30 metres or less from the surface.
Programme introduction, dates, eligibility, how to apply and how to become a programme mentor.
Description of the dataset showing areas of coal extracted by surface excavations in the past or currently being excavated.
A short guide to understanding and valuing data, from defining the different types of data to dealing with bad data and bias.
All essential shared data assets (ESDA) must be assessed for data quality issues, made findable and be available through APIs.
Don’t include personal or financial information like your National Insurance number or credit card details.
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