The amount of data produced by individuals and corporations has dramatically increased during the last decades. This generalized gathering of data brings opportunities (e.g., building new knowledge using this "Big Data") but also new privacy challenges. The general public express a growing distrust over personal data exploitation, which has been met with successive strengthened regulations (e.g. EU general data protection regulation, GDPR). In the meantime, open data is taking a crucial place within many administrations. The open data policy is a powerful move by public institutions aiming at publishing data collected by public agent. The objective is to manage this data as an asset to make it available, discoverable, and usable by anyone. Both the US and the European Community have foundations to promote this policy. This leads to an important new societal challenge at the crossroads of these social evolutions: how can privacy be preserved while publishing useful data?


Nowadays, data are often organized as graphs with an underlying semantic to allow efficient querying and support inference engines. Such is the case in, for example, linked data and semantic web typically relying on RDF. he SEmantic Networks of Data: Utility and Privacy (SEND UP ANR-18-CE23-0010) project focuses on such databases and will follow two main goals: (1) prevent illegitimate use of private data while querying semantic data graphs and (2) publish useful sensitive semantic data graphs will preserving privacy.