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Databases

This section gathers databases and tools used in Computational and
Empirical Legal Studies. It highlights key resources that support data-driven research on laws, courts, regulations, and legal systems worldwide.
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Computational & Machine Learning Resources

Title
Link
About
TradeLab

Real-world legal research projects often using empirical evidence and practitioner engagement.

OECD Investment Treaty Tools

Treaty data, metadata, and policy summaries- 

underused resource for treaty practice analysis.

HUDOC – ECtHR Database

Full archive of ECHR decisions with structured filters-

useful for doctrinal-empirical hybrid work.

ICSID Caseload Statistics

Downloadable case-level arbitration statistics for trend analysis.

UNCTAD Investment Dispute Navigator

Case-level ISDS database with filters by issue, industry, outcome

very useful for empirical ISDS research.

Mapping Investment Treaties

Empirical visualization of BIT relationships and content. 

Excellent for treaty network and structure research.

UNCTAD IIA Mapping Project

Structured content analysis of 2,500+ IIAs across 100+ legal issues. 

Ideal for treaty-level empirical comparison.

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Legal Databases & Mapping Projects

Title
Link
About
Data Science For Lawyers

A practical guide to Python, data science, and machine learning for lawyers. 

ICSID Caseload Statistics

Downloadable data on international arbitration trends.

AI Law Tübingen

Empirical legal tech research with NLP + structured data.

Computational Law Lab

Research at the intersection of law, data, and computational design.

LLCA – Hamburg

Legal linguistics + NLP-focused law & language lab.

Machine Learning for Science

ML applied across disciplines — including law-related case studies.

CLDS – Center for Legal Data Science (UZH)

Research hub producing empirical legal data analysis.

Harvard Caselaw Access Project

Full-text U.S. case law from 1658–2018 — useful for historical and longitudinal studies in legal doctrine.

Court Listener

U.S. federal and state court opinions with API-suitable for large-scale legal prediction and citation network research.

LexNLP

NLP toolkit tailored to legal documents. Ideal for extracting structure from contracts, pleadings, and decisions.

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