Law Data Science.

Font size: Decrease font Enlarge font
Law Data Science.

A scientific investigator are the term for scientist, while data is nothing but information.Scientific investigation of information that enables an optimum decision making can be the role of the data scientist. Various Decision supports system rely on the volume of data, more the merrier. A lawyer as a data scientist, is more like a liable to work legal data analytics with domain knowledge that goes very deep. Many mistakenly believe a data scientist is just a synonym for a data analyst, but this is wide of the mark. Data science is a somewhat new concept for the legal industry, but it’s an active and, indeed, “hot” field within many other sectors of the economy. Virtually every industry now collects more data about what they do and how they do it than ever before.

"Its better not to leave it on the table, but collect analyse the right data"

A data analysis can differ a bit as compared with data science, while analysis is a deep study of data with hypothetical reasoning based on data examined. on the other hand a data scientist works with the analytics of the data, and with some mathematics, algorithms in conjunction with AI and machine language. A deep domain knowledge is mandatory for a lawyer, this enables them to established the relations between the various key parameters explored and scrapped from the unstructured legal text.

Legal data scientists can be summarised as follows

1. BIG LEGAL DATA : There is no need to justify how big the legal database, quite prolific. The negative side of the legal data available for research and analysis, is that, its completely unstructured. As a legal data scientist, the legal data has to be deeply examined. Structured valuable information to be generated from the volumes of the legal data. This involves deep study of the legal data, lets say case laws. A case law is again a legal data that comprises of the details of a legal case and its conclusion.

2. INFORMATION SCRAPING : For a legal data scientist reading and extracting the valuable information from the legal data or case laws. The extracted information is stored in an structure or in database terms a normalised form of data is generated, source of which is un-normalised. This data is the basic data that is used by law data scientist and is processed and worked with various algorithms. As already mentioned a deep domain knowledge is mandatory for extracting valuable information from the case laws, a compressed normalised data.

3. LEGAL NETWORK ANALYTICS : Establishing various relations with the extracted data is more of legal network analysis. The data can be weighted with a numeric value that relates to its importance in the complete context of the legal data"case law". Not just the weightage but these numeric weights added to the various extracted date also helps in the graphical representation of the data. The domain knowledge is very important in conjunction with the practical experience. An absurd analytics can ruin the outcome.

4. LEGAL TEXT COMPARISON : Comparison of various legal text is another important aspect in legal data science. Comparison is mainly conducted to find the similarities or the differences amongst the compared legal text. Comparison again exemplifies the process of data science. Considering a case law, a lawyer always refers a similar cases while arguing for a specific cases.This has an strong influence in the final conclusion of the case law.

5. PREDICTIVE ANALYSIS : This is nothing but, working with the analytics of the extracted valuable information of the legal documents. The predictive analysis is mainly done based on various algorithms that are deployed in AI or the machine language that leverages to anticipate the final conclusion. The algorithms work on the analytics of the data.

6. CASE FORECASTING: The legal data science that mainly works with the important data points in the legal document are generated to predict the outcome of the judgements. This is why at each of the above mentioned stage the legal knowledge is very important.

What does a lawyer need to be a data scientist.

A data analysis can differ a bit with data science, while analysis is a deep study of data with hypothetical reasoning based on data.While, a data scientist works with the analytics and with some mathematical code or algorithms

KEYWORD : law data science,legal data scientist, data science, lawyer data scientist