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Data

Guidance and regulation

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  • Use data more effectively by improving your technology, infrastructure and processes.

  • This page provides details about DSIT's portfolio of AI assurance techniques and how to use it.

  • Description of the data set showing known locations where a coal seam is near the surface.

  • The Code of Data Matching Practice explains the data matching work the NFI does.

  • Description of the data set showing underground coal workings whose depth is 30 metres or less from the surface.

  • Use a reference architecture to develop a public sector organisation’s technology and how it shares data across government.

  • 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.

  • Description of the dataset showing the area of the ground that might be affected if subsidence a mine entry occurs.

  • The Innovation Fellowship is 10 Downing Streets flagship initiative for bringing world class technical talent into government for high impact tours of duty.

  • Apply to use data available under licence from the Mining Remediation Authority and view the cost of the data.

  • Description of the data set showing likely extent of probable underground coal workings for which no recorded plans exist.

  • Description of the dataset showing extent of coal resources capable of being extracted by surface mining methods.

  • 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.

  • Description of the dataset showing areas of coal extracted by surface excavations in the past or currently being excavated.

  • An introductory guide for practitioners interested in finding out how assurance techniques can support the development of responsible AI.

  • A guide to some different ways of visualising data and their respective strengths and weaknesses.

  • A short guide to artificial intelligence (AI), data science and machine learning, explaining the terminology and helping you use and apply the latest advances.

  • Share your reference data for use in projects and services outside your organisation.

  • A simple guide to understanding and describing the trustworthiness of autonomous systems and associated artificial intelligence (AI) algorithms.

  • Programme introduction, dates, eligibility, how to apply and how to become a programme mentor.