bdva general data value chain

The DataVaults Data Value Definition

DataVaults aims at Individuals taking control of their personal data, deciding which kind of data can be shared, when and also obtaining a compensation for sharing it. The first step of DataVaults as a platform focused on personal data is to collect and store data coming from different personal contexts, such as sports, mobility, healthcare, energy, preferences, etc. and to provide the Individual a tool to share such data with Data Seekers (economic operators and public administration), while keeping control over it and gaining an economic value.

In turn, data seekers are able to work on shared personal data and combine it with other types of data they have, to create new datasets or relevant derivatives (insights, reports, etc).

In D1.1 – DataVaults Data Value Chain Definition, the project Consortium presents an overview of what a data value chain is, with a stronger focus on personal data, and how the different stakeholders can benefit from it. One of the objectives of the document is to present the state of the play of personal data platforms, by diving into existing tools and methodologies for personal data management. Then it focuses on the various approaches taken by different stakeholders towards a personal data economy, looking at different angles and potential revenue streams behind data platforms.

Zooming in the DataVaults ecosystem and the five demonstrator partners, an initial set of possible usage scenarios is recorded, alongside the data sources they would like to use in the context of DataVaults, in order to elicit stakeholders’ needs and expectations from the DataVaults personal data framework.

datavaults demonstrators data sources
Figure 1: DataVaults demonstrators data sources

Key Takeaways from the DataVaults Data Value Chain Definition

One of the most important ideas drawn from reading the state of the art of the data value chain, and more specifically of the value of personal data, is that there is no common defined methodology for calculating the value of personal data, although individuals are interested in knowing how much this could be, since  a lot of companies are currently gaining high economic profit from personal data without any remuneration to individuals sharing it. 

The concept of privacy is also perceived in the document as one of the most relevant ideas. The users are open to paying more for better data privacy and security. The legal issues around the personal data will be one of the challenges of the project and some ideas have been reflected in the document.

Another aspect of key importance for a data management framework, is the actual availability of data. This is not a static parameter, on the contrary, it may change from time to time, as it depends on the updates of devices APIs, the introduction of new APIs and data sources, the terms of use of the various services, as well as legislation.

The outcomes of D1.1 set the scene for the development of the DataVaults personal data platform, and the identified challenges will be further studied and discussed in the future.