We often discuss here on Slaw the future of legal publishers, especially in a digital era. Although some of them have tinkered in-house with their own technological and big data solutions, none have independently brought anything revolutionary to the market to date.
Instead, what we might expect is that these legal powerhouses will either partner up with startups, such as with Thomson Reuters and Blue J Legal last year, or will simply purchase them outright.
In some ways, these patterns are not unique. Quicklaw was first created by the late Hugh Lawford at Queen’s University in 1973. Steven McMurray and Ron Plashkes of Western University created PClaw in 1982. LexisNexis purchased both of them, Quicklaw in 2002, and PCLaw in 2005.
LexisNexis’ newest acquisition this week is RavelLaw, a “new category of intelligent tool that combines legal research and analytics,” founded in 2012 at Stanford University.
LexisNexis already acquired Lex Machina in 2015, which provides analytics for trial strategies based on behaviours by litigants, counsel and the bench, using Natural Language Processing and Machine Learning. Starting 2018, they plan to combine the insights from RavelLaw to also formulate the type of arguments most likely to be persuasive to a judge.
The goal appears to be “to turn lawyers into data analysts.” RavelLaw seems to provide better data visualization techniques than other platforms, but information visualization is not itself anything new in computer sciences.
Technology has long been used to improve user comprehension of data, but also is prone to oversimplification of the data and a propensity for false positives due to artificial artifacts. Some techniques are also more useful than others. For example, Mackinlay illustrated in 1985 that certain types of data visualization techniques are more effective given inherent limitations in human perception and processing.
Data visualization is found extensively in the business world through proprietary tools such as Microsoft’s Excel and Visio, Tableau, Watson Analytics, Data driven documents, Perfuse Toolkit and Gephi. Downsides of these can include cost and ongoing need for technical expertise. The approach that LexisNexis appears to intend to advance with includes integration of the data collection, processing and visualization.
Of course even with the prettiest of graphs, lawyers will not become data analysts overnight. The more serious and dedicated disciples will learn R for coding and use of Weka for data mining.
The one major upside of LexisNexis’ acquisition of RavelLaw is they will be honouring a commitment to complete the digitization of Harvard case law library in a public access database.
While this might be appear to be a strange endeavour for a legal publishing company to engage in, it also signals a truth we’ve seen for some time now – legal publishing of the future has very little to do with unprocessed data, and even less to do with physical books. It will all be in the big data and the analytics.