Data 2020: Value estimation, prioritisation and distribution

Fri Feb 21, 2020
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Many people now recognise how important data is to our societies and economies, but how to value data is still an area of active research. Being able to put a value to data should help governments and organisations know where to invest

Data 2020: Value estimation, prioritisation and distribution

Value estimation, prioritisation and distribution is one of the key areas we’ve identified in our Data 2020 landscape review to help organisations understand hot topics in the world of data in 2020 – from digital competition to data rights

Many people now recognise how important data is to our societies and economies, but how to value data is still an area of active research. Being able to put a value to data should help governments and organisations know where to invest.

Traditional ways of valuing data – based on how much it costs to create or what it can be sold for – don’t reflect the full value of data to society. Approaches like Deloitte’s ‘Assessing the value of TfL’s open data and digital partnerships’ report for Transport for London show how much more value comes from the actions and decisions data supports, and the innovation and economic growth of data reusers. This means it’s contextual: data is more valuable to a community when it is used to help meet their goals.

Much of the value of data arises from combining it with other data, whether that’s analysing billions of web searches each day, the medical histories of millions of diabetes patients, or combining land use and weather patterns to identify where to site new wind turbines.

Being able to value data helps governments work out how to prioritise increasing access to data. The European Commission will this year identify high value datasets that should be made open across six categories – geospatial, earth observation and environment, meteorological, statistics, companies, and transport.

For organisations sharing data, being able to estimate value helps to justify investment in improving data quality or interoperability. It can also help to work out how to fairly share value between those who collect or maintain data and those who use it.

  • Working out the current and potential value of a dataset
  • Prioritising datasets for investment in particular geographies or sectors
  • Classifying data to understand different types of value
  • Incentivising investment in creating, using and sharing data
  • Fairly distributing the value that arises from the use of data

This is not an exhaustive list of resources. If you provide tools or resources in this topic, please let us know by emailing [email protected]org

  • Anmut
  • Bennett Institute for Public Policy
  • Open Data Institute
  • The Lisbon Council

This is not an exhaustive list of all organisations working in this area. If your organisation is working on this topic and you’d like to be included in this list, please let us know via [email protected]

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