Towards trusted data sharing: guidance and case studies

Data sharing checklist

3. Develop the business model that allows value to be generated and shared

  • How does access to data change an existing business model or create a completely new business model? More broadly, what is the commercial framework?

  • What are the conditions upon which the commercial value generated will be distributed? How are the benefits and costs shared?

  • Will data be monetised and traded, or will value be generated in another way? Will there be an agreement to exchange data between parties, without any money changing hands?

  • Where are costs and benefits incurred? Will the cost of collecting and curating data be incurred by a different part of an organisation or partnership from the part that benefits? Is there a shared understanding of the value of data across an organisation or between stakeholders?

  • Have the costs of data acquisition, cleaning, integration and custodianship been assessed where relevant? Are the costs of technology acquisition and deployment known? Will the technology be developed in-house, through a cloud solution or as a hybrid solution?

  • What business change is required for the organisations involved, including changes to the operating model? Where are existing activities disrupted, or existing revenues redirected?

Learning from the case studies:

Data’s value depends on its use, as well as the cost of collecting, processing or securing it. Where it is challenging to quantify the value of data, narrative approaches can aid organisations in understanding the value of their data.

The ability to use a unique identifier to link datasets creates new value. For example, researchers accessing data via the Grampian Data Safe Haven use a unique identifier to link up. Datasets may be particularly valuable if, subject to appropriate governance, they enable correlation and validation (triangulation) of data.

Organisations need to ensure that the cost of cleaning data, which may require considerable resource, is recoverable. In some cases, a third party may do this, such as in the oneTRANSPORT project.

Where data is monetised, pilots may help to validate approaches to assigning value to data, as have been used by The Weather Company.

Intellectual property issues need to be resolved right from the start.