Summary of the project: The overall goal of the JuDDGES project is to harness state-of-the-art Natural Language Processing & Human-In-The-Loop technologies to provide legal researchers with new Open software and tools that enable extensive, flexible and on-going meta-annotation capability (both automated and employing domain experts in-the-loop). This capability is applied to legal records/judgments from criminal courts across jurisdictions with varied legal constitutions (Poland, England & Wales). We hence seek to dissolve barriers of resources, language, data & format inhomogeneity that currently impede research on judicial decision making. In making this new software, tools and data resource open on a public repository, researchers will be empowered to develop and empirically test theories of judicial decision making and address judicial policy and practice-relevant questions. Researchers from public (legal) institutions can also reuse the data for their purposes. The application of Open Science hence also rectifies a substantial gap in the empirical legal research domain that has been slow in adopting Open Science principles. The resulting annotated pan-national dataset & toolset will constitute the largest and most comprehensive open and reusable legal research repository in Europe for research on judicial decision-making. Relevance to the topic addressed in the call: This project will develop an AI-based solution (tool) that can be used by researchers to examine unstructured textual data in court records and/or written legal judgments. In doing so, we will create the largest extant pan-national legal dataset in Europe. The tool would allow researchers to access and progressively enrich large, detailed, and representative legal samples of data (starting from what we have made available) in a resource- and cost-effective as well as time-efficient way. The datasets so produced and adjusted to Open Science principles and openly available from a trusted data repository, will also be accessible to others for re-use both within and across legal jurisdictions, including the unexpected researcher/user (e.g., from legal institutions). Indeed, the open software & Human-In-The-Loop (HITL) tools that the project will provide will enable non-AI-specialist ECR researchers to interrogate judicial decision data and identify novel lines of research interrogation. The tool and resultant data will thus expand methodological horizons. In the long-term, our project will contribute to a scientific, evidence-based approach to judicial policy and practice in the courts. The project embodies and exemplifies the principles enshrined within Horizon Europe initiatives on open research data, applying Open Science principles and the utilisation of Open Infrastructures.

The IoT has a great potential to provide novel services to humans in critical areas for society. This innovation however requires updating our understanding of the risks associated with the new technology so that we can deploy it with confidence and society can trust it. Amongst the biggest problems for this vision to become a reality are security flaws due to technical restrictions, immaturity of software applications, intrusion threats through new challenges in complex usage scenarios, and mainly a lack of transparency. The IoT could become human centric computing that serves our society, but simultaneously amongst the main triggers for security problems is human behaviour, either unintentionally or maliciously. The core idea of SUCCESS is to use methods and tools with a proven track record to provide more transparency of security risks for people in given IoT scenarios. Our core scientific innovation will consist on the extension of well-known industry-strength methods in our priority areas. Our technological innovation will provide adequate tools to address risk assessment and adaptavity within IoT in healthcare environments and an open source repository to foster future reuse, extension and progress in this area. Our project will validate the scientific and technological innovation through pilots, one of which will be in collaboration with a hospital and will allow all stakeholders (e.g. physicians, hospital technicians, patients and relatives) to enjoy a safer system capable to appropriately handle highly sensitive information on vulnerable people while making security and privacy risks understandable and secure solutions accessible. This innovation will be achieved by a multi-disciplinary team of recognized experts in their fields which has significant experience in knowledge transfer to and from society. SUCCESS will have significant impact, strengthening the interdisciplinary approach to this important challenge at the crossroads between society and technology, creating new methods for increased security in healthcare, supporting the use of these robust methods by adequate open-source tools, and educating on the use of our products through real-life working prototypes.