TrustNShare

TrustNShare aims to design and establish a data trust model that uses quasi-continuous gradations of trust and incentives to balance the best possible data usage scenarios. Motivation is the finding that there are unavoidable re-identification risks, especially in the area of mobile-collected rich data sets. In response, Distributed Privacy Preserving Computing approaches will be used to implement a flexible choice of the degree of data sharing. TrustNShare will support transparent fine-tuning of trustworthiness, risk tolerance, and data sharing. To test the model, the project is implementing Trust Navigator, an app that implements the specific trust processes for flexible consent through smart contracts in a tamper-proof manner. To ensure the acceptance and effectiveness of the data trust model developed in the project by data givers and takers, they will be actively involved in the investigation of relevant influencing variables of data sharing. The development and design of incentives for data sharing will be carried out in a participatory research process.