Misinformation generates misperceptions, which have affected policies in many domains, including economy, health, environment, and foreign policy. Co-Inform is about empowering citizens, journalists, and policymakers with co-created socio-technical solutions, to increase resilience to misinformation, and to generate more informed behaviors and policies. The aim of Co-Inform is to co-create these solutions, with citizens, journalists, and policymakers, for (a) detecting and combating a variety of misinforming posts and articles on social media, (b) supporting, persuading, and nourishing misinformation-resilient behavior, (c) bridging between the public on social media, external fact checking journalists, and policymakers, (d) understanding and predicting which misinforming news and content are likely to spread across which parts of the network and demographic sectors, (e) infiltrating echo-chambers on social media, to expose confirmation-biased networks to different perceptions and corrective information, and (f) providing policymakers with advanced misinformation analysis to support their policy making process and validation. To achieve these goals, Co-Inform will bring together a multidisciplinary team of scientists and practitioners, to foster co-creational methodologies and practices for engaging stakeholders in combating misinformation posts and news articles, combined with advanced intelligent methods for misinformation detection, misinformation flow prediction, and real-time processing and measurement of crowds' acceptance or refusal of misinformation. Co-Inform tools and platform will be made freely available and open sourced to maximize benefit and reuse. Three main stakeholder groups will be directly engaged throughout this process; citizens, journalists, and policymakers.

The proposed solution aims to deliver a descriptive and predictive data analytics platform and related tools using state-of-the-art machine learning and artificial intelligence methods to prevent, detect, analyse, and combat criminal activities. AIDA will focus on cybercrime and terrorism, by addressing specific challenges related to law enforcement investigation and intelligence. While cybercrime and terrorism pose distinct problems and may rely on different input datasets, the analysis of this data can benefit from the application of the same fundamental technology base framework, endowed with Artificial Intelligence and Deep Learning techniques applied to big data analytics, and extended and tailored with crime- and task- specific additional analytic capabilities and tools. The resulting TRL-7 integrated, modular and flexible AIDA framework will include LE-specific effective, efficient and automated data mining and analytics services to deal with intelligence and investigation workflows, extensive content acquisition, information extraction and fusion, knowledge management and enrichment through novel applications of Big Data processing, machine learning, artificial intelligence, predictive and visual analytics. AIDA system and tools will be made available to LEAs through a secure sandbox environment that aims to raise the technological readiness level of the solutions through their application in operational environment with real data.

The underlyingassumption of the project proposal, in line with the UN Security Council recommendations (Resolution n. 2178, September 2014) and the Commission “European Agenda on Security”2015-2020(28.4.2015, COM(2015) 185 final), is that in order to contrast successfully violent extremism,what is neededis a more balanced response to terrorism,combining repressive (protective) measures with preventive measures, in a comprehensive approach in collaboration withactors of civil society and the communitiesof reference, based on a firm commitment to respecting fundamental rights, promoting integration, cultural dialogue and fighting discrimination. To this end, a better understanding of factors constituting violent radicalisation in Europe is needed, which aims,through a multidisciplinary analysis,to a comprehensive view of the phenomenon, investigatingits root causes, in order to develop appropriate countermeasures, ranging from early detection methodologies to strategies, ways and techniques of counter-narrative, involving LEAs together with experts and civil society actors at local, national and European level. In addition, it is necessary to acknowledge that violent radicalization,especially in the case of jihadist extremism,goesmainly through narratives that: have specific characteristics and contents; use specific communication codes;are addressed to specific audiences; and spread in a multitude of ways, over the Internet, as well as by means of in-person communication exchanges that take place in families, schools, places of worship, local communities, etc. These narratives havebeen proven effective towards vulnerable groups such as young people, detainees, and people craving for revenge after having experienced what they perceive as injustices, either at personal or group level. Furthermore, due to this multifarious background, such extremism is characterised by single or group terrorist acts also reflecting a variety of influences and motivational dr

Money underpins all terrorist activities (without money propaganda, training, recruitment, and support are less effective or null). The disruption of terrorist financing activity is a key element in any fight against terrorism. DANTE will deliver effective, efficient and automated data mining, analytics solutions and an integrated system to detect, retrieve, and analyse huge amounts of heterogeneous and complex multimedia and multi-language (in five languages) terrorist-related contents from both the Surface and the Deep Web, including the Dark Nets. The ultimate goal is to discover (by “connecting the dots”), analyse and monitor potential terrorist-related activities and people, with focus on online fund raising activities, but also considering propaganda, training and disinformation. The challenging results of DANTE are achievable by exploiting, improving and integrating several existing data mining and analysis tools (mostly provided and owned by the partners; some already with high TRL). These tools and services will be further evolved and enhanced to be put at the service of the requirements provided by LEA partners (Guardia Civil, Policia Judiciaria, Home Office, Carabinieri). Thus, starting from lab and pre-prototype tools and methods, a market ready product with higher TRL will be the major outcome of DANTE. The presence of end user partners in the consortium will allow the validation/optimisation of the solution and boost of its adoption in their operational circumstances. The DANTE system will be validated and demonstrated in three pilots under the direct responsibility of the involved LEAs in their operational environments with the aim of detecting, analysing and monitoring terrorist-related contents for (i) propaganda (including recruitment, incitement, radicalization and disinformation), (ii) training and (iii) fund raising. DANTE surpasses the needs of the call for ensuring TRL6 of the projects results, by including components that will reach TRL7.

RELIANCE will extend the EOSC service offering with a set of industry-strong, innovative, interconnected services for the open, efficient, and cross-disciplinary management of the research lifecycle. In accordance with FAIR and Open Science principles, it will adopt a holistic approach to address different research activities, spanning: discovery of and access to research data, methods and materials; extraction of valuable information from scientific literature; structuring data-driven scientific investigations as semantically rich research objects; FAIR-ness self-assessment; dynamic collaboration, sharing and dissemination considering the whole lifecycle as a first-class citizen; and supporting reproducibility, validation, versioning and reuse of research results. Core to the service portfolio are Research Objects as the overarching information artefact to manage research, Data Cubes for efficient and scalable structured data access and discovery, and Text Mining for the extraction of information from scientific text as machine-readable metadata. RELIANCE will pilot the services in three different Earth Science communities, fostering the use of Copernicus data and demonstrating their efficacy in real-life vertical and multi-disciplinary scenarios, and will launch an Open Call to engage other communities. The high-TRL research-enabling services portfolio will be onboarded in ESOC following established procedures, ensuring the interplay with cross-cutting and added value services, and following a user-centric approach. RELIANCE will expose its services via APIs and libraries, enabling their use via different frontends and Jupyter notebooks. RELIANCE brings into EOSC more than 3,000 research objects from research communities like Earth Science, represented by three project partners, but also others like Astrophysics and Bioinformatics, which have embraced research objects concept and tools, and will become the best ambassadors to enlarge and engage new communities