Online Safety and Security for Protection of Public-Facing Professionals and Democratic Resilience Politician, Reporters, Teachers, Emergency services staff and Police officers are public-facing professionals (PFPs). This means they operate in the public eye with at times dramatic repercussions for their private lives (e.g., ‘trial by social media’, unwanted identification, online harassment and threats to themselves or their families). Online attacks are often framed as a way to ‘redress injustices’ or holding public professionals to account. They, however, can have dramatic negative consequences. Therefore, it is important to better understand the challenges faced by PFPs for their participation in online spaces and provide mechanisms to them and their organisations to effectively safeguard, manage and mitigate against these risks. OSPREY will build a knowledge base for PFP-specific risks, harms, protection needs and harm impacts, focusing on mapping shared and profession-specific risk profiles and safeguarding requirements; create a comprehensive knowledge-base on attack vectors and motivations of perpetrators across to understand disparate types/motivations (e.g., personal grievances, ideological driven campaigns, foreign political campaigns) to guide improved protection approaches; co-create advanced AI tools, mechanisms and solutions shaped for PFP-specific challenges empowering secure participation in online spaces; toolkits and trainings to improve knowledge of PFPs, their employing organisations, LEAs and law/policy makers how to prevent, manage and mitigate online harms as well as legislate for better safety of PFPs; improve public awareness on online harm impacts, including practical approaches to allyship and bystander activation.

Across Europe society is changing due to demographic, technological and economic developments. Communities are getting more diverse, both in real life and online. This challenges Law Enforcement Agencies (LEAs) to engage with, and to reassure, communities about safety and security matters in a trustful way. The changing status quo is significantly shaping perceptions of policing, requiring adaptive strategies. To address these challenges, the KOBAN project will create an innovative, research and practice-based Community Policing (CP) initiative, adopting an evidenced based approach.It will focus on co-creation and collaborative security between LEA and non-LEA community members, leading to mutual trust and respecting each other’s contributions. This results in a greater sense of security, whilst contributing to an overall increase in the efficiency and effectiveness of securing all communities including those who are often considered hard to reach and engage. KOBAN’S Capability Model will identify proven methodologies, models, technologies, tools and best practices, and use them as a foundation for future proactive, co-active and reactive CP capabilities. This knowledge will help to build the AI Assistant as well as the App Factory for the development of further CP tools, methods and solutions tailored to the needs of stakeholders and adhering to social, legal, cultural, ethical and gender equality standards. These will be tested and validated in six pilot projects throughout Europe. KOBAN will support capacity building, embedding knowledge, skills and capabilities within organisations and communities leading to bespoke training for both police personnel, municipalities and citizens. In short, KOBAN will lead a cultural and organisational transformation that address current fundamental barriers to effective community policing. With its Capability Driven Approach, KOBAN is setting the stage for future-proof community policing, both online and in the real world.

KINETIKA embraces Industry 4.0 concepts to create a groundbreaking 4D digital twin framework for cultural heritage (CH) objects with mechanical parts, focusing on movable structures of industrial heritage and cultural heritage masonry. By integrating advanced imaging - photogrammetry, laser scanning and muography - KINETIKA captures both the physical form and internal complexity of objects, reflecting their dynamic nature. Through IoT-based sensor networks, the project continuously monitors structural integrity, environmental conditions, and mechanical performance, feeding data into AI-driven analytics for anomaly detection, predictive maintenance, and conservation strategies. The core principles of the 4D Digital Twin include accurate 3D representation, displacement or strain estimation, functional simulation, predictive failure analysis and time-based evolution modelling. These capabilities are enhanced by advanced computer vision and AI algorithms, enabling new levels of study and engagement with CH assets. KINETIKA also emphasises interactive and cross-media engagement, combining 3D models, images, sensor data and simulations to create immersive experiences for researchers, educators and the public. Collaboration between the cultural and industrial sectors is central, with KINETIKA's platform being seamlessly aligned with the ECCCH framework to ensure data interoperability. Third-party CH service providers will offer and consume specialised services through a secure interface, enhancing the ECCCH data while tailoring solutions for different heritage professionals. The project will validate its innovations through representative case studies, including clock towers, looms and drawbridges, demonstrating the platform's adaptability and guiding further applications across a wide range of cultural artefacts.