Welcome back! We hope you had a productive and/or relaxing summer.
Have you heard of data visualization? Data visualization is a way of using computers to graphically present data in ways which humans can visually interpret. This can be a boon to people who are visual learners. While we all know about pie charts and bar graphs, you may not be familiar with some exciting ways in which legal information providers have applied data visualizations to help the researcher navigate legal information. Here we will be covering examples from several different providers Casetext, Lexis Advance, and Ravel.
Casetext, an innovative legal information startup, has created a heatmap, a type of data visualization in which values in a set of data are represented as colors, for their pro version. Casetext uses the heatmap within a case to show the number of citations to each page of the opinion. The line on the left is the heatmap, the boxes from top to bottom represent page numbers, and the shade of blue indicates how often the corresponding pages have been cited. The darker the shade, the more often the page has been cited. This is useful because it indicates which portions of the opinion citing courts have found to be most important.
The heatmap is not to be confused with Casetext’s “Key Passages” as pictured below. For instance, if we went to the page from the heatmap with the darkest blue, we see a callout with the number 164 just to the right of the passage. The 164 represents the number of times this passage has been quoted in subsequent opinions.
Lexis Advance, a long-time industry leader, has recently added a color coded heatmap to its search results for cases. The example uses the following search limited to U.S. Supreme court decisions since 2007.
As you can see the visualization color codes my search terms and shows where the terms fall within the opinion from Headnotes to dissent. By clicking on the bands of color within the heatmap, Lexis Advance will display the relevant passages within the case. The first example “evolving standards of decency” shows up in Justice Kagan’s opinion, note the relevant pale green bar on the heatmap is highlighted.
Below we can see where the terms “minor” and “murder” show up in Justice Thomas’s dissent. Here, note the purple-orange-purple portion of the heatmap is highlighted.
The heatmaps within the search results represent only the top hits while going into a case gives a much more detailed version of the heatmap as you can see below. What constitutes a ‘top hit’ is determined by an algorithm which looks at inter alia search term location, frequency, and proximity in order to determine the most representative language within the document.
The most obvious use for this sort of data visualization is in finding your search terms within a case, but also by paying attention to the density of search terms and where the colors are together, one can guess where in an opinion the court is discussing the interaction between the different concepts.
Ravel is another innovative legal information startup that has taken a different approach to data visualization. Ravel’s main data visualization presents a search as a series of connections between cases. The two images below represent Ravel’s visualization of a search for the phrase “evolving standards of decency” with the left image sorted by court and the right image sorted by relevance. All of the same information is present. Each circle represents a case. The size of each circle indicates the number of citations within your search results and the color of each circle correlates to the level of the court which wrote each opinion which is more easily discerned in the image sorted by court on the left.
By clicking one one of the case circles, you can obtain a relevance mapping of connections between that case and other cases. The image below reflects the relevance mapping for the case Trop v. Dulles, the case in which the phrase “evolving standards of decency” originated. The pattern in this image shows those cases which both include this phrase and cite to Trop v. Dulles directly. The connection is shown as a blue line with an arrow. The arrow points from the citing case to the cited case and the thickness of the line correlates to the number of times cited. Notice how the image below correlates to the ‘relevance’ view, above right.
The next image shows the visualization for the case Estelle v. Gamble which applies the “evolving standards” from Trop in the context of medical treatment for prisoners. The image below shows the pattern of connections of cases either cited by Estelle or citing to Estelle. Ravel’s data visualization allows researchers to see connections between cases and the development in subsequent cases.
This post included explanations of three fairly new uses of data visualization in legal research. There are many more out there and since Lexis Advance implemented such a tool the other major commercial legal databases are likely to follow suit. If your favorite legal research data visualization tool was not covered please share it in the comment section below.
* Western New England University School of Law students have free access to the pro version of Casetext, contact Artie Berns for full details.
** Ravel provides free access to its data visualization tools for free to law students. You can sign up for a free Ravel educational account here.