Ethics and transparency

In considering how mature your organisation’s data practices are around collecting, maintaining and publishing data, you should also consider the impacts of your work with data may affect others

Organisations should consider data ethics – a branch of ethics that evaluates data practices with the potential to impact on people and society – in data collection, sharing and use.

The Data Ethics Maturity Model is a tool for anyone who collects, uses and shares data. It helps assess and benchmark how widely embedded data ethics culture and practices are across your organisation, and helps you to consider what your future ambitions might be.

The themes of the Data Ethics Maturity Model align with the themes of the Open Data Maturity Model, but break down in a slightly different way:

  • Organisational governance and internal oversight – highlights the need for an organisation to have a clear strategy around ethical data practices, and a leadership with responsibility and capacity to deliver that strategy

  • Skills and knowledge – highlights the steps required to create a culture where ethical data practices are embedded by identifying the knowledge sharing, training and learning required within an organisation

  • Data management risk processes – identifies key business processes that underpin ethical collection, use and sharing of data, focusing on identifying and assessing risks of harm to individuals and communities

  • Funding and procurement – highlights the need for organisations to invest in embedding ethical data practices, and to reflect requirements in procurement processes

  • Stakeholder and staff engagement – addresses the need for organisations to engage both with communities reflected in, or impacted by, data they are collecting, using or sharing, and organisations they are sharing data with or using data from

  • Legal standing and compliance – reflects the need for organisations to abide by relevant laws, regulations and social norms to avoid harmful impacts from collection, use and sharing of data.

The model uses the same maturity levels as the Open Data Maturity Model:

  1. Initial — the desirable processes are non-existent or ad hoc, with no organisational oversight

  2. Repeatable — processes are becoming refined and repeatable, but only within the scope of individual teams or projects. There are no organisational standards

  3. Defined — processes are standardised within the organisation based on best practices identified internally or from external sources. Knowledge and best practices start to be shared internally. However the processes may still not be widely adopted

  4. Managed — the organisation has widely adopted the standard processes and begins monitoring them using defined metrics

  5. Optimising — the organisation is attempting to optimise and refine its process to increase efficiency within the organisation and, more widely, within its business sector

You can find the full Data Ethics Maturity Model here.

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