Different protection needs depending on the data source?

How can we help people better protect their data in times of digitization? This is the question we are addressing in a current research project on the topic of data protection and privacy on the Internet. Our focus is on the aspects “transparency” and “possible countervalues” if we deliberately publish our own data.

We asked the participants to rank different data according to their need for protection. This shows that people assign different types of protection to different types of data, with a total of five types of data being given priority in terms of protection.

Five types of data

We specified the following data types for selection

  • Communication content (chats, mails,…)
  • Mobility behaviour (car, bus, etc.)
  • Financial data (account movements)
  • Personal data (personal information such as name, address,…)
  • Health-related data (blood values,…)

The question was: “”The following is a list of various data areas. How important is the protection of this data to you? put the data area whose protection is most important to you in the first place; the data area whose protection is second most important to you in the second place, etc. ”

Different need for protection

The result is astonishing: there are clear differences in the need for protection depending on the data source. First and foremost are financial data with a clear gap to all other data types. More than half of the participants (58%) rank this data area as the most sensitive data. This is followed by personal data. One in four places these in first place. This is followed by health-related data with 10%, i.e. one in ten places them in first place. The last two places have similar levels of communication content (4%) and mobility behaviour (2.5%) with the lowest need for protection.

This ranking is particularly relevant for innovations and new business models in the digital field. For example, eHealth offers, i.e. digital solutions for all aspects of health, are likely to encounter a significantly greater willingness to share data. Financial services, on the other hand, which often require a great deal of explanation for the consumer, have to meet much greater requirements if data is to be shared. We can confirm this from innovation projects in the area of financial services, for example in the area of business models for future credit processes.

Health data only medium need for protection

We were surprised by the position of the health-related data, which ended up in the lower field in the ranking for need of protection. This indicates that people are willing to disclose their health data if they can expect it to lead to better treatment, for example.


The project myneDATA is a research project funded by the BMBF with 2.25 million euros and coordinated by Dialego AG. Duration June 2016 – May 2019. http://mynedata.de
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