DATALAB has participated in several research programs funded by national and European Commission research funds. DATALAB has participated in more than 25 research and development projects from which it has scientifically leaded more than 15 projects in the area of advanced data management and analytics, social networks, Web content mining and cloud computing. The most recent research activity involves relevant projects funded by the EU H2020 framework.
PTwist aims to design, deploy, and validate an open platform which will twist plastic reuse practices, by boosting citizens awareness, circular economy practices, and sustainable
ENCASE will leverage the latest advances in usable security and privacy to design and implement a browser-based architecture for the protection of minors from malicious
The Big Data era poses a critically difficult challenge and striking development opportunities in High-Performance Computing (HPC): how to efficiently turn massively large data into
There is no escape from the expansion of information, so that structuring and locating meaningful knowledge becomes ever more difficult. This project will tackle this
The aim of EICOS is to provide the methodology, the theoretical and modeling foundations as well as the algorithmic techniques and the necessary software architecture
Legacy systems are likely to contain software vulnerabilities that can lead to various security breaches. On the other hand, these systems contain valuable information about
Cloud4Trends: Leveraging the cloud infrastructure for localized real-time trend detection in social media
Cloud-based framework for social networks trends detection and analysis via real-time large-scale data clustering techniques, evolving social graph mining with tailored data preprocessing and cleaning.
The purpose of this project concerns the investigation, determination and implementation of a common Enterprise Architecture, which can cover the particular needs of the most
COST Action IC0804 proposed realistic energy-efficient alternate solutions to share IT distributed resources. As large scale distributed systems gather and share more and more computing
Cloud9 is structured around three pillars, reflecting also on the research-related workpackages and final deliverables: (i) the Cloud Computer abstraction, building a novel highly scalable