International audience; Spatial Data Infrastructures (SDIs) are a key asset for Europe. This paper concentrates on unsolved issues in SDIs in Europe related to the management of semantic heterogeneities. It studies contributions and competences from two communities in t...

Gamification is defined as the injection of game elements in applications with non-gaming purposes. This technique has shown outstanding results in promoting the engagement and activity on communities of users, in both business and non-for-profits fields. Often, gamific...

We introduce Clemmys, a security-first serverless platform that ensures confidentiality and integrity of users' functions and data as they are processed on untrusted cloud premises, while keeping the cost of protection low. We provide a design for hardening FaaS platfor...

Raising awareness among young people on the relevance of behaviour change for achieving energy savings is widely considered as a key approach towards long-term and cost-effective energy efficiency policies. The GAIA Project aims to deliver a comprehensive solution for b...

Several challenges are related to metagenomics, one of which is the data management. A related central concept is k-mer which means a possible subsequence of length k from a DNA (sub)sequence. In this work, the focus is on indexing k-mers and supporting box queries wher...

Rendering transport behaviours more sustainable is a pressing issue of our times. In this paper, we rely on the deep penetration of mobile phones in order to influence citizens’ behavior through data-driven mobility and persuasive profiles. Our proposed approach aims to...

Gamification can be used to effect positive behavioral change in various fields, including energy conservation. This paper reports on a survey we conducted to formulate a holistic view of users’ profiles and preferences in an Internet of Things (IoT)-enabled gamified mo...

The development of applications for advanced Intelligent Transportation Systems (ITS), is a growing research area, pushed especially by the need to mitigate problems related to transportation inefficiency, overuse and pollution, mainly caused by the increasing of traffi...

Flood risk prediction has been traditionally based on models that are developed from time-series of data collected over long periods of time from expensive and hard to maintain in-situ sensors available only in specific areas. The climate change has made the monitoring ...

The massive collection of data via emerging technologies like the Internet of Things (IoT) requires finding optimal ways to reduce the observations in the time series analysis domain. The IoT time series require aggregation methods that can preserve and represent the ke...