Edits, Additions, Swirl Integration by: Amanda Lim and Bhavya Gupta
Original Author: Wolfgang Alschner
Hi there! Welcome to the Data Science For Lawyers Course. A team of dedicated students at the UCL Data Science Society have been working hard to provide accessible resources to learn data science specifically in the law field. LegalTech, or legal data science, has gained popularity over the years, and thus we wanted to provide a way for people with zero background in coding to learn some cool data science techniques applicable to law.
Legal data science refers to harnessing the power of computer science and artificial intelligence to scale legal research by analyzing legal documents more efficiently and effectively. Data science can be used to handle and explore large amount of legal texts, finding information in unstructured text, automate legal document analysis through artificial intelligence, predict the outcome of court decisions, and much more!
This course teaches you how to utilise R, a programming language for data science, from scratch through an interactive learning environment called Swirl. Swirl allows you to learn R in a question-and-response style, like a chatbot who is your personal tutor! The Data Science For Lawyers Course will teach you how to approach and solve big legal questions using R.
These lessons are based on workshops original created by Wolfgang Alschner, a Professor at the University of Ottawa, and the University of Ottawa Legal Text Mining Lab. "The uOttawa Legal Text Mining Lab brings together expertise in law and computer science to rethink legal analysis in the age of big (legal) data. Millions of legal texts exist and each harbours useful insights that can make the law more effective, just and accessible. Yet, legal scholars typically lack the tools to tap into this resource. Conversely, computer scientists have the skills to mine data, but not the subject matter expertise to know what questions to asks and what problems to solve. The Lab integrates expertise from both fields to produce insights that neither discipline could generate on its own".
Wolfgang Alschner, Assistant Professor at the uOttawa Common Law Section with Cross-Appointment to the Faculty of Engineering and Computer Science.
Virginie Jetté, PhD Student
Peter C. Zachar, JD Student
Sarah Crothers, JD Student
Samantha Lo, JD Student
Tasfia Ruba, JD Student
Visit http://www.datascienceforlawyers.org/learning-resources/ to view the original workshops and more learning resources.
Here is a list of sources referenced on the original Data Science For Lawyers website.
– Ashley, Kevin D. Artificial Intelligence and Legal Analytics. Cambridge University Press, 2017. Link.
– Livermore, Michael, and Daniel Rockmore, eds. Law as Data: Computation, Text, and the Future of Legal Analysis. SFI Press, 2019. Link.
– Alschner, Wolfgang. “The Computational Analysis of International Law”, in: Rossana Deplano and Nicholas Tsagourias (eds.), Research Methods in International Law: A Handbook, 2019 [SSRN Version]
UCL Data Science Society does not take any credit for the creation of this material, except where additions/edits were made. Swirl integration and additional material and questions were created by Amanda Lim and Bhavya Gupta as part of a project initiated by the UCL Data Science Society.
Last updated June 24th, 2020