About JuDDGES

Wrocław University of Science and Technology (Polish: Politechnika Wrocławska) is a leading technological university in Wrocław, Poland. Founded in 1945, the university has evolved into a world-class institution recognized for its excellence in research and innovation. Named by Huffington Post UK in the top 15 of the World's Most Beautiful Universities Rankings, its main campus is located near Plac Grunwaldzki alongside the Oder river.

The university ranks among the best in the world according to the Shanghai Ranking (ARWU 2021: 901-1000 band) and holds 3rd place among Polish technical universities. With over 26,000 students and more than 4,000 academic staff, it operates 14 faculties across engineering, sciences, medicine, and social sciences. This platform is developed by the Department of Artificial Intelligence at WUST, which is renowned for its cutting-edge research in AI, machine learning, natural language processing, and legal informatics, contributing significantly to both academic advancement and real-world applications.

The JuDDGES project harnesses state-of-the-art technologies in Natural Language Processing (NLP) and Human-In-The-Loop (HITL) to revolutionize how legal researchers access, annotate, and analyze judicial decisions across various jurisdictions. Our team is committed to dissolving barriers in legal research, fostering open science, and enhancing the empirical study of judicial decision-making.

JuDDGES aims to develop open software and tools for the extensive and flexible meta-annotation of legal records from criminal courts in jurisdictions with diverse legal systems, starting with Poland and England & Wales. This initiative is designed to support the development and empirical testing of theories in judicial decision-making, facilitating a deeper understanding of judicial policies and practices.

This platform is one of several independently maintained projects that together form the JuDDGES research pipeline. The parent research project hosts datasets, NLP pipelines, and HITL experiments. A dedicated annotation workbench, maintained by partner contributors, produces the verified ground-truth annotations that downstream tools — including this platform — consume.

Keeping the projects separate but linked through shared open data formats lets each team iterate on their own cadence while still contributing to a coherent whole.