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Data standards and architectures

Practical insights and inspiration for achieving better public service outcomes. Data lies at the heart of what we do. This collection seeks to help local public service organisations unlock the potential of data, whilst protecting the people and communities that they are there to serve.

Authors and contributors: Martin Ferguson, Jos Creese

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Data in a compatible and recognised format is easier to link, share, match and correct for errors. Yet much data is still collected and sorted in different formats and indexing systems, even when standards such as the Unique Property Reference Number exist. Often this is because of a history of working in silos – a specific department that has always collected citizen or property data in a particular way for example. But it is also perpetuated by software suppliers, either because their software demands proprietary formats, or because they consciously or unconsciously design solutions that require non-standard data formats for competitive advantage or lock-in.

Public service organisations need to resist these pressures. Failure to adopt standard data structures increases risks from poor data quality, mismatches when sharing data and unnecessary manual intervention. Opting for a holistic approach to common data standards and architectures, such as citizen identity and address data, and making it clear to IT suppliers that non-standard data formats are unacceptable are essential requirements for the future of personalised and place-based local public services.

“In most cases, we can learn from real world behaviour by looking at how existing services are used. Let data drive decision-making, not hunches or guesswork. Keep doing that after taking your service live, prototyping and testing with users then iterating in response. Analytics should be built-in, always on and easy to read. They’re an essential tool.”

Source: UK Government Digital Design Principles – Number 3

Principles to adopt

  1. Use standard data formats and referencing for all data sets and plan to retire or adjust all systems data that does not conform.
  2. Cleanse and match legacy data sets to common referencing systems.
  3. Prioritise open data, linked data and open application programming interfaces (APIs).
  4. Adopt common and open standards for data and avoid closed solutions (such as pdf – easy to consume but maintain data lock-in) where possible in favour of portable data formats (such as CSV files – open and shareable).
  5. Ensure standard data formats and referencing systems are covered in all digital and IT systems procurements, particularly anticipating data linkages and the potential value from open data in the public domain.
  6. Ensure all suppliers adopt open data standards and good practices in data handling and storage. This includes cloud hosting and ensuring data can readily be unlocked from systems for reuse or retrieved when contracts end.
  7. Adopt good practices for maintaining data quality, processing and use in accordance with the Government Design Principles (GOV.UK) and Local Public Services Data Handling Guidelines (NLAWARP)
  8. Develop common data architectures to ensure value can be maximised, risks can be managed and linkages can be made to share data safely and securely.

“Collaborate on data standards not software. Create and iterate standards by designing and building for user needs, but don’t focus on shared software, focus on coalescing around common data standards. Common data architectures are the new public service institutions.”

Source: Paul Brewer, Director for Digital & Resources, Adur and Worthing councils

Case Studies