LCAM – Legal Case Law Analytics & Modeling
Exploring Big Data Insights through AI-Driven Statistical Modeling Project
Exploring Big Data Insights through AI-Driven Statistical Modeling Project
Strengthened democratic institutions and public administration (rule of law).
The activities contribute to accountable, independent and more efficient public administration at national and local levels, aim to reinforce Ukraine’s justice system and support investigations of war crimes and other crimes committed in connection with Russia’s aggression. A consistent priority is to create conditions for increased transparency and a reduced risk of corruption while strengthening civil society’s role in reconstruction and reform. The project also supports digital transformation in Ukraine, which reinforces the rule of law in times of war.
In post-war Ukraine, rapid implementation of sustainable development ideas is vital to construct a peaceful, inclusive society and ensure universal access to justice, along with establishing effective, accountable and participatory institutions at all levels. Ukrainian courts handle over 4 million cases yearly, significantly impacting citizens’ trust in both the judiciary and state authorities. Surveys reveal widespread distrust. Ukraine ranks third in complaints lodged with the European Court of Human Rights; about one-third cite violations regarding the duration of proceedings or enforcement of decisions. The Unified State Register of Court Decisions publishes more than 100 million court decisions in open access, yet the register lacks effective search tools and structured information access. Human resources alone cannot efficiently process this data. LCAM addresses these shortcomings by investigating innovative tools for analysing big data from publicly available court decisions, providing unique opportunities to collect, analyse and summarise empirical data on judicial proceedings and to inform future transformations of the national justice model.
Analyse Ukrainian case-law datasets using advanced statistical methods and artificial intelligence, predict case outcomes, evaluate factors affecting judicial procedures, promote justice and strengthen democracy.
The project gathers and analyses big data from more than 100 million Ukrainian court decisions through innovative statistical analysis methods and AI algorithms. Its results provide objective evidence for assessing judicial reform effectiveness and for aligning Ukrainian practice with EU law and values. Transparent and effective monitoring of national judicial practice, as well as uniform application of EU law by Ukrainian courts, are essential for Ukraine’s accession path. LCAM supports these goals by supplying empirical evidence, open datasets and reproducible analytical tools for EU institutions that monitor compliance, for anti-corruption bodies, and for investors seeking a predictable legal environment.
Primary beneficiaries are policymakers, civil-society organisations, government institutions, human-rights groups and justice-reform advocates who rely on empirical data to shape legislation, policies and public initiatives.
Secondary beneficiaries include legal practitioners, small and medium-sized enterprises and citizens who benefit from faster, more predictable dispute resolution and a higher level of trust in the judiciary.
EU institutions responsible for monitoring membership requirements, judicial reform and anti-corruption efforts will also benefit indirectly. Bilingual outputs broaden access for scientists, practitioners, ordinary citizens and businesses.
LCAM combines the advanced machine-learning and complex-systems expertise of Linnæus University (Sweden) with the deep mathematical and legal knowledge of Taras Shevchenko National University of Kyiv (Ukraine). External stakeholders—Vilnius University, Jagiellonian University, Örebro University and the University for Continuing Education Krems—contribute specialised expertise, feedback and dissemination capacity.
Project management is led by Sweden; Ukrainian partners develop software for automated data collection and labelling, create categorisation methodologies and adapt neural networks. The consortium applies innovative statistical analysis methods and AI algorithms to large-scale court-decision data, delivering open, structured datasets and analytical models.
Project outputs—prototype software, structured databases and natural-language-processing algorithms—will enable continued collaboration on EU-funded initiatives that extend LCAM’s methods to user-facing e-justice tools. Existing networks in the EUniWell alliance, Erasmus+ proposals and planned Horizon Europe actions provide pathways for further joint work after the project ends.