Recent Visualization Projects Involving US Law and The Supreme Court

"Copyright Sign in 3D", Image by Muses Touch

“Copyright Sign in 3D”, Image by Muses Touch

There have been many efforts over the past few decades to use visualization methods and technologies to create graphical representations of the law. These have been undertaken by innovative lawyers in diversity of settings including public and private practice, and in legal academia.

I wrote an article about this topic years ago entitled “Graphics and Visualization: Drawing on All Your Resources”, in the August 25, 1992* edition of the New York Law Journal. (No link is currently available.) Not to paint with too broad a brush here, but things have changed dramatically since then in terms of how and why to create compelling legal visualizations.

Two very interesting projects have recently gotten significant notice online for their ingenuity and the deeper levels of understanding they have facilitated.

First are the legal visualizations of Harry Surden. He is a professor at the University of Colorado School of Law. He teaches, researches and writes about intellectual property law, legal informatics, legal automation and information privacy.

I had the opportunity to hear the professor speak at the Reinvent Law NYC program held in New York in February 2014. This was a memorable one-day event with about 40 speakers who captivated the audience with their presentations about the multitude of ways that technology is dramatically changing the contemporary marketplace for legal services.

On Professor Surden’s blog, he has recently posted the following three data visualization projects he built himself:

  • US Code Explorer 1 consisting of a nested tree structure for Title 35 of the US Code covering patents. Clicking on each levels starting with Part I and continuing through V will, in turn, open up to the Chapters, Sections and Subsections. This is an immediately accessible interactive means to unfold Title 35’s structure.
  • US Code Explorer 2 Force Directed Graph presents a different form of visualization for Title 17 of the US Code covering Trademarks. It operates as a series of clickable hub-and-spoke formations of the Code’s text whereby clicking on any of the hubs will lead you to the many different sections of Title 17.
  • US Constitution Explorer is also presented in a nested tree structure of the Constitution. Clicking on any of the Articles will open the Sections and then the actual text.

Professor Surden’s visualizations are instantly and intuitively navigable as soon as you view them. As a result, you will immediately be drawn into exploring them. For legal professionals and the public alike, he impressively presents these displays in a clear manner that belies the complexities of the underlying laws. I highly recommend clicking through to check out and navigate all of these imaginative visualizations. Furthermore, I hope his work inspires others to experiment with additional forms of visualization of the other federal, state and local codes, laws and regulations.

For a related visualization of the networks of law professors on Twitter, please see the February 5, 2015 Subway Fold post entitled Visualization, Interpretation and Inspiration from Mapping Twitter Networks.

The second new study containing numerous graphics and charts is entitled A Quantitative Analysis of the Writing Style of the U.S. Supreme Court, by Keith Carlson, Michael A. Livermore, and Daniel Rockmore, Dated March 11, 2015. This will be published later in Washington University Law Review 93:6 (2016). The story was reported in the May 4, 2015 edition of The New York Times entitled Justices’ Opinions Grow in Size, Accessibility and Testiness, Study Finds, by Adam Liptak. This article focused upon the three main conclusions stated in the title. I highly recommend click-throughs to read both.

The full-text of the Law Review article contains the very engaging details and methodologies employed. Moreover, it demonstrates the incredible amount of analytical work the authors spent to arrive at their findings. Just as one example, please have a look at the network visualization on Page 29 entitled Figure 5. LANS Graph of Stylistic Similarity Between Justices. It truly brings the author’s efforts to life. I believe this article is a very instructive, well, case where the graphics and text skillfully elevate each other’s effectiveness.


To get online then you needed something called a Lynx browser that only displayed text after you connected with a very zippy 14.4K dial-up modem. What fun it was back then! 

Startup is Visualizing and Interpreting Massive Quantities of Daily Online News Content

"News", Image by Mars Hill Church Seattle

“News”, Image by Mars Hill Church Seattle

Just scratching the surface, some recent Subway Fold posts have focused upon sophisticated efforts, scaling from startups to established companies, that analyze and then try to capitalize upon big data trends in finance¹, sports² , cities³, health care* and law**. Now comes a new report on the work of another interesting startup in this sector called Quid. As reported in a most engaging story posted on VentureBeat.com on November 27, 2014 entitled Quid’s Article-analyzing App Can Tell You Many Things — Like Why You Lost the Senate Race in Iowa by Jordan Novet, they are gathering up, indexing and generating interpretive and insightful visualizations for their clients using data drawn from more than a million online articles each day from more than 50,000 sources.

I highly recommend a full read of this story for all of the fascinating details and accompanying screen captures from these apps. As well, I suggest visiting and exploring Quid’s site for a fuller sense of their products, capabilities and clients. I will briefly recap some of the key points from this story. Furthermore, this article provides a timely opportunity to more closely tie together seven related Subway Fold posts.

The first example provided in the story concerns the firm’s production of a rather striking graphic charting the turn in polling numbers for a Democratic candidate running for an open Senate seat in Iowa following a campaign visit from Hillary Clinton. When Senator Clinton spoke in the state in support of the Democratic candidate, she address women’s issue. Based upon Quid’s analysis of the media coverage of this, the visit seemed to have helped the Republican candidate, a woman, more then the Democratic candidate, a man.

Politics aside, Quid’s main objective is to become a leading software firm in supporting corporate strategy for its clients in markets sectors including, among others, technology, finance and government.

Quid’s systems works by scooping up its source materials online and then distilling out specific “people, places, industries and keywords”. In turn, all of the articles are compared and processed against a specific query. In turn, the software creates visualizations where “clusters” and “anomalies” can be further examined. The analytics also assess relative word counts, magnitudes of links shared on social media, and mentions in blog posts and tweets. (X-ref again to this November 22, 2014 post entitled Minting New Big Data Types and Analytics for Investors that covers, among other startups, one called Dataminr that also extensively analyzes trends in Twitter usage and content data.)

The sample screens here demonstrate the app’s deep levels of detail in analytics and visualization. As part of the company’s demo for the author, he provided a query about companies involved in “deep learning”.  (X-ref to this August 14, 2014 Subway Fold post entitled Spotify Enhances Playlist Recommendations Processing with “Deep Learning” Technology concerning how deep learning is being used to, well, tune up Spotify’s music recommendation system.) As this is an area the writer is familiar with, while he did not find any unexpected names in companies provided in the result, he still found this reassuring insofar as this confirmed that he was aware of all of the key participants in this field.

My follow up questions include:

  • Would it be to Quid’s and/or Dataminr’s advantage(s) to cross-license some of their technology and provide supporting expertise for applying and deploying it and, if so, how?
  • Would Quid’s visualizations benefit if they were ported to 3-D virtual environments such as Hyve-3d where users might be able to “walk” through the data? (X-ref to this August 28,2014 Subway Fold post entitled Hyve-3D: A New 3D Immersive and Collaborative Design System.) That is, does elevating these visualizations from 2-D to 3-D add to the accessibility, accuracy and analytics of the results being sought? Would this be a function or multiple functions of the industry, corporate strategy and granularity of the data sets?
  • What other marketplaces, sciences, professions and products might benefit from Quid’s, Dataminr’s and Hyve-3D’s approaches that have not even been considered yet?

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1.  See this November 22, 2014 post entitled Minting New Big Data Types and Analytics for Investors.

2.  See this October 31, 2014 post entitled New Data Analytics and Video Tools Affecting Defensive Strategies in the NFL and NBA.

3.  See this October 24, 2014 post entitled “I Quant NY” Blog Analyzes Public Data Sets Released by New York City.

*  See this October 3, 2014 post entitled New Startups, Hacks and Conferences Focused Upon Health Data and Analytics .

**  See this August 8, 2014 post entitled New Visualization Service for US Patent and Trademark Data .