by Pierangela Samarati, (Università degli Studi di Milano)

MOSAICrOWN - Multi-Owner data Sharing for Analytics and Integration respecting Confidentiality and OWNer control  - is a Horizon 2020 project that aims at enabling data sharing and collaborative analytics in multi-owner scenarios in a privacy-preserving way, ensuring proper protection of private, sensitive, and confidential information. MOSAICrOWN will provide effective and deployable solutions allowing data owners to maintain control on the data sharing process, enabling selective and sanitized disclosure providing for efficient and scalable privacy-aware collaborative computations.

by Sabrina Kirrane, and adapted for ERCIM News by Jessica Michel

The SPECIAL project (Scalable Policy-aware Linked Data Architecture For Privacy, Transparency and Compliance) addresses the contradiction between Big Data innovation and data protection compliance requirements by proposing a technical solution that makes the achievement of both of these goals realistic. SPECIAL allows citizens and organisations to share more data, while guaranteeing compliance with the General Data Protection Regulation (GDPR), thus enabling both trust and the creation of valuable new insights from shared data.

by George Hatzivasilis (FORTH), Kostas Fysarakis (Sphynx) and Sotiris Ioannidis (FORTH)

Modern educational tools and computer technologies are now getting adapted in the cyber-ranges field. Simulation, emulation, as well as serious gaming, provide an enhanced training experience under realistic conditions and accurate operational environments. The THREAT-ARREST Horizon-2020 project is developing a model-driven platform for professional cyber-security training and the raising of awareness for individuals and organizations.

by Christos Anagnostopoulos, Aris Lalos, George Pavlidis, Christos Koulamas, Athanasios Kalogeras (ISI, Athena R.C), Ana Garcia Lopez (University of Granada) and Giacomo Di Benedetto (Enginelife-Engineering Solutions)

The WARMEST project is developing an intelligent decision support system that will result in a low impact tool to suggest improvements in maintenance and risk management procedures in cultural and heritage sites (CHSs).

by Sándor Baran and Annette Möller (Faculty of Informatics, University of Debrecen and Institute of Mathematics, Technical University of Clausthal)

Statistical calibration of ensemble weather forecasts is a rapidly developing research area of statistics as well as atmospheric and water sciences. We are developing and implementing multivariate approaches explicitly accounting for dependencies between weather observation locations and/or between weather variables, including temperature, precipitation and pressure.

by Dumitru Roman and Ahmet Soylu (SINTEF)

Corporate information, ranging from basic company information such as company name(s) and incorporation date to complex balance sheets and personal data about directors and shareholders, are the foundation that many data value chains depend upon in various sectors. However, collecting and aggregating information about a business entity from relevant public and private sources and especially across borders and languages is a tedious and very expensive task rendering many potential business models non-feasible.

by Patrick Jost (NTNU), Gisela Böhm (University of Bergen), Monica Divitini (NTNU) and Ingvar Tjostheim (Norwegian Computing Center)

Data is being collected everywhere, and people are often unaware of what information they share, with whom and what it is used for. Games have the potential to increase people’s awareness about privacy and, at the same time, help researchers to better understand decision-making processes around data sharing. This is the challenge addressed by ALerT, a multi-disciplinary project aiming at developing serious games and research tools for privacy awareness.

by Francesco Flammini (Mälardalen University and Linnaeus University, Sweden), Valeria Vittorini (CINI and University of Naples Federico II, Italy) and Zhiyuan Lin (University of Leeds, UK)

The European RAILS research project is investigating the potential applications of artificial intelligence (AI) within the rail sector, and helping define roadmaps for future research in next generation signalling systems, operational intelligence, and network management.

by Franco Mazzanti and Davide Basile (ISTI-CNR)

The 4SECURail project – funded by the European Union Horizon 2020 Shift2Rail Joint Undertaking – has two overall objectives: to design a Computer Security Incident Response Team (CSIRT) for joint EU-Rail cybersecurity, and the setup of a Formal Methods Demonstrator for the evaluation, in terms of cost, benefits and required learning curve, of the impact of the use of Formal Methods for the rigorous specification of the components of a railway signalling infrastructure.