Présentation de l'éditeur

Legal Data and Information in Practice provides readers with an understanding of how to facilitate the acquisition, management, and use of legal data in organizations such as libraries, courts, governments, universities, and start-ups.

Presenting a synthesis of information about legal data that will furnish readers with a thorough understanding of the topic, the book also explains why it is becoming crucial that data analysis be integrated into decision-making in the legal space. Legal organizations are looking at how to develop data-driven insights for a variety of purposes and it is, as Sutherland shows, vital that they have the necessary skills to facilitate this work. This book will assist in this endeavour by providing an international perspective on the issues affecting access to legal data and clearly describing methods of obtaining and evaluating it. Sutherland also incorporates advice about how to critically approach data analysis.

Legal Data and Information in Practice will be essential reading for those in the law library community who are based in English-speaking countries with a common law tradition. The book will also be useful to those with a general interest in legal data, including students, academics engaged in the study of information science and law.

Sarah A. Sutherland is President and CEO at the Canadian Legal Information Institute (CanLII) where she works on advancing CanLII’s strategic priorities of providing access to law. She writes and presents regularly on legal data internationally and has a bi-monthly column on Slaw.ca.

 

Sommaire

Introduction

1 Legal Data Overview

1.1 Introduction

1.2 Why Look at Data?

1.3 Applications

Business Improvement

Legal Research

Academic Research

Court Processes

Customer Focused Applications

1.4 Sources

Courts and Tribunals

Dockets

Court Business Data

Legislative Bodies

Government Departments

Law Firms and Lawyers

Academic Research

Legal Technology Companies

1.5 Global Context

United States

Canada

United Kingdom

European Union

Africa

India

Singapore

Australia

1.6 Conclusion

1.7 Works cited

2 Sources of Data

2.1 Introduction

2.2 Sources

Governments

Open Datasets

Parliamentary Bodies

Courts

Case Law

Court Pleadings

Business processes

Billing

Web Logs

Legal Publishers and Data Providers

2.3 Developing Data

Experimental Methodology

Proxy Data

2.4 Strategy

2.5 Conclusion

2.6 Works Cited

3 Data Formats

3.1 Introduction

3.2 Categories

3.3 Issues Particular to Law

Case Citations

Depth of Data

Machine Readable Law

3.4 Types

Numerical

Categorical

Free Text

3.5 Delivery Formats

Spreadsheets

Tagged Formats

Databases

APIs

3.6 Considerations

Data Standards

Passively and Actively Collected Data

Supervised and Unsupervised Machine Learning

Law as Code and Law as Data

3.7 Planning

3.8 Conclusion

3.9 Works cited

4 Data Analysis Techniques

4.1 Introduction

4.2 Close Reading

4.3 Statistical Analysis

Normal Distribution

Random Distribution

Linear Distribution

Multiple Points of Comparison

Techniques

T-Tests

Regression

Compared to Machine Learning

4.4 Machine Learning

Supervised Learning

Unsupervised Learning

Reinforcement Learning

4.5 Natural Language Processing

Bag-of-Words

Vector Analysis

4.6 Other Tools

Knowledge Bases

Decision Trees

Network analysis

4.7 Conclusion

4.8 Works Cited

5 Interpreting Legal Data

5.1 Introduction

5.2 Approaching Data Analysis

5.3 Methodology

Statistics

Hypothesis Testing

Regression

Machine Learning

Natural Language

5.4 Considerations

Correlation and Causation

Proxy Data

Sensitivity

Suitability

Complexity

Extrapolation

5.5 Concerns

Overfitting

Bias

5.6 Conclusion

5.7 Works Cited

6 Issues with Using Legal Data

6.1 Introduction

6.2 Availability

6.3 What Is Missing

6.4 Ambiguity

6.5 Limitations on Language Processing

6.6 Sampling

Analytics and Sample Size

6.7 Cost

6.8 Jurisdiction

6.9 Structure

Case Law

Legislation

Law Firms’ Data

6.10 Risks

6.11 Conclusion

6.12 Works cited

7 Artificial Intelligence

7.1 Introduction

7.2 Definition

7.3 Promise and Limits

7.4 Types of Artificial Intelligence

Statistical Analysis

Machine Learning

Vapor Ware

7.5 Process

7.6 Likely Impacts

7.7 Limitations

7.8 Concerns

Fairness

Error and Bias

Ethics

7.9 Thinking Critically

7.10 Conclusion

7.11 Works cited

8 The Law and Politics of Legal Data

8.1 Introduction

8.2 The Nature of Data Based Applications

8.3 Access to Data

8.4 Privacy

8.5 Jurisdiction

Infrastructure

Legacy Systems

Government Controls

8.6 Primary Law

8.7 Practice Data

8.8 The Research Landscape

8.9 Working Toward Change

8.10 Conclusion

8.11 Works cited

9 Vision for the Future

9.1 Introduction

9.2 Thinking About the Future

9.3 Forecasting

9.4 Technology Adoption Dynamics

9.5 Issues

Data Availability

Privacy laws

Available investment

Cultural acceptance

Competing priorities

Regulation of Technology

Social Concerns

9.6 Divergence

Jurisdiction

Population Segments

Legal System

Culture

9.7 Predictions

Near term

Changing Productivity Paired with Changing Market Size

Medium Term

Born Digital Legal Data

Long Term

The Next Generation of Artificial Intelligence

9.8 Conclusion

9.9 Works Cited