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Elijah Meeks's blog

Kindred Britain Techniques 1: Permalinks on a Graph

Kindred Britain has a handful of patterns and functions that are rather novel in their creation or deployment. In this series, I'll be exploring the methodology and motivation for them, as well as go into some technical detail as to how they work. The first feature I'd like to focus on is the use of rich permalinks for sharing Kindred Britain. These direct links to particular states of Kindred Britain mean that when you share a link like this: doesn't just open up Kindred Britain, but rather it opens up a very particular view of Kindred Britain, in this case the genealogical path from General Robert E. Lee to President Zachary Taylor.

Genealogical path from Robert E Lee to Zachary Taylor

Kindred Britain: A sign of our times

Today marks the public release of Kindred Britain, a new interactive scholarly work that explores the role of family in British culture. Integrating geospatial, temporal, and network information visualization, this project attempts to demonstrate the genealogical interconnectedness of the British elite. In doing so it expands the notion of Britishness, and the notion of society and culture in general, such that through family ties we can see George Washington, Napoleon Bonaparte, Sigmund Freud, and Kevin Bacon all included among these kindred British. To achieve this took significant effort not only in writing code, but in envisioning how to present so much information of so many different kinds in a way that did not overwhelm a reader. I want to stress the concept of the reader here, rather than a "user" since to create a site like this one has to move away from the stereotype of the user with their short attention span and incapacity to grasp complexity. It doesn't pay to create works for users, and buy into the myth that no one reads anything on the Internet and that a website has to be designed for someone with a ten-second attention span. Works like Kindred Britain and ORBIS not only include much flashy and interactive content, but vast quantities of text.

Discovering Regions with ORBIS v2

Animated difference in clusters in ORBIS v2

A simple demonstration of the kind of higher-level analysis possible with the new cartograms and clustering in the v2 version of ORBIS. This is accomplished entirely within the browser (except for turning it into a gif) first by running cartograms for selected sites (in this case the 9 sites that are labeled by default) according to each priority, then clustering them and then drawing borders around the clusters. Notice the borders are drawn using convex hulls, and so you have overlap on border regions. It may be better (or perhaps provide an interesting alternative) to derive borders using Voronoi diagrams.


A screenshot of ORBIS v2

Over the coming months, I'll be spending some time integrating new features, data, and base layers to ORBIS: The Stanford Geospatial Transportation Network of the Roman Empire. While ORBIS was tremendously successful both in its public appeal and its use in scholarship, there has been a growing list of small and not-so-small features that could improve the model or the user experience of it. Some of these have already been implemented in a prototype version seen in the screenshot above. Rather than wait for the new version to be finished, though, ORBIS v2 will be developed publicly, with the code available on Github. This way, ORBIS will benefit from the user feedback and feature requests of the larger digital humanities and software development community. There are still a few systems administration and database steps that need to occur before this can happen, but when the code and new site are available, the link will be posted here and on @ORBIS_Stanford on Twitter.


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