How we do

Data for Good breaks down the silos between traditional behavioural and register-related areas, so prevention, business development and growth can be implemented with a more holistic approach and on a broader foundation. All this is done through the combination of anonymised/pseudonymised register and behavioural data in a secure environment.

Through the use of a number of advanced calculation methods, including big data, algorithms and cognition methods the relationship between human behaviour and register-related areas is analysed, thus making it possible to create a solid basis for new insights.

Companies and institutions will only have access to uninterpreted anonymous data and insights across areas.

Projects

DATA for GOOD summit

In September 2020 we had a conference with Danish Industry (DI) discussing how we jointly ensure privacy and data security for the citizen while also ensuring databased value creation for companies and society.

Following the conference we held a series of 5 webinars (in danish). You can see the webinars here:

https://www.danskindustri.dk/tech-der-taller/var-med/afholdte-webinarer2/webinarer-fra-data-for-good/

BLOCKDAP

A project funded by the Danish Industrial Foundation.

Project aim is to test a new IT infrastructure that adds privacy
through the use of Secure Multiparty Computation technology,
SMC, to blockchain technology.

https://www.industriensfond.dk/blockchain-data-and-privacy

https://www.datafair.org/blockdap-

HEDAX

A project funded by the Danish Innovationfund. HedaX, abbreviation
of ‘Health Data Exchange’.

With the use of a new IT infrastructure it is possible to exchange personal health and behavioural data through individual consent,
thus giving the user the right to control their own personal data.
The DfG governance model ensures the citizen rights and the
project aims to contribute to developing personalized medicine.

https://innovationsfonden.dk/da/investeringer/investeringshistorier/danmark-i-forertrojen-i-indsamling-af-sundhedsdata

https://www.datafair.org/hedax