Towards trusted data sharing: guidance and case studies

Data sharing checklist

2: Identify the scope of data to be shared and how it will be used

  • What data needs to be shared to solve the problem? Who is sharing data and why?

  • Where does data exist and where are there gaps? Are there many places from which to source this type of data or only one? How might this change over time?

  • How will data be used, and what analytics will be applied?

  • Will raw data, augmented data, derived data or a solution based on data be shared? The higher up in that pyramid, the greater the value, effort and risk.

  • What metadata specifications and standards are needed?

Learning from the case studies:

Many organisations do not know what data they hold and how to use it, so would benefit from carrying out audits that look at data quality, provenance and timeliness. Good quality metadata and effective curation are vital.

It is possible that, in defining the opportunity to create value from data, suitable data does not exist and ways of generating it must be found. For example, in the oneTRANSPORT project, early analytics work indicated that additional sensors were needed to supplement data already being collected.

Alternatively, data may exist but be inaccessible – for example, if data is personal, commercially sensitive or if it is otherwise siloed – in which case the development of trusted and appropriate ways to access it will be needed. Grampian Data Safe Haven enables access to highly sensitive data, while the Data and Analytics Facility for National Infrastructure (DAFNI) enables access to data that would otherwise be highly siloed.