Methods of Data Research for Law

Abstract

Methods of data research are becoming increasingly important in the legal domain. After explaining the concept of legal big data, to show that law is an area in which a lot of big data is available, this chapter discusses and illustrates several existing and potential applications of data research methods for lawyers and legal researchers. Particular opportunities exist with regard to (1) predictions, (2) searching, structuring and selecting, and (3) decision-making and empirical legal research. These methods constitute an important contribution to legal practice and legal scholarship as they may provide novel unexpected insights and considerably increase efficiency (less resources, more results) and effectiveness (more accurate and reliable results) of legal research, both in legal practice and legal scholarship. This may, among other things, result in improved legal services, new business models, new knowledge and a more solid basis for evidence-based policies and legislation. However, there are also several limits to and drawbacks of the use of these data research methods for law. From a methodological perspective, these include the lack of human intuition, an abundance of results that are not always relevant, limited insights in underlying causality, issues with repurposing, selfconfirmation, self-fulfilling prophecies and reliability issues. It is concluded that, given the opportunities these developments provide for new business models for legal services and for legal research (both in legal practice and in legal scholarship), it is likely that these methods will be used on a larger scale in the near future and that new and additional methods will be developed. This will change to some extent the way legal work looks like and the job market for lawyers.

Application of an Ecosystem Methodology Based on Legal Language Processing for the Transformation of Court Decisions and Legal Opinions into Open Data

“…We show that this approach produces Legal Open Data of satisfying quality while highly reducing the need for manual intervention.Information 2020, 11, 10 2 of 30 manual analysis and processing is prohibitive and automated approaches are needed to undertake such tasks [5]. It is noteworthy that some researchers explicitly classify legal documents as Big Data since they meet at least two of the major aspects of Big Data: volume and variety [6]. While several governments are taking steps to apply semantic web technologies in the legal publishing domain (e.g., the legislation.gov.uk platform where UK legislation is published in XML and RDF) [7], in most countries these documents are usually made available in unstructured or poorly structured formats; for example, as PDF files, HTML documents, or plain text.On the other hand, the current trend of Open Data requires that government data (legal documents being a special category of them) are published without technical and legal impediments, in structured and machine-processable formats, and under an open license.…”

“…Information 2020, 11, 10 2 of 30 manual analysis and processing is prohibitive and automated approaches are needed to undertake such tasks [5]. It is noteworthy that some researchers explicitly classify legal documents as Big Data since they meet at least two of the major aspects of Big Data: volume and variety [6]. While several governments are taking steps to apply semantic web technologies in the legal publishing domain (e.g., the legislation.gov.uk platform where UK legislation is published in XML and RDF) [7], in most countries these documents are usually made available in unstructured or poorly structured formats; for example, as PDF files, HTML documents, or plain text.…”