Kindred Britain: Viewer's Choice
Link to Visualization: http://kindred.stanford.edu/#
What is the purpose of Kindred Britain?
Kindred Britain is a network of nearly 30,000 people - mainly British, mainly dead - connected through family ties. But the site is not merely an extensive archival record. All sites, all datasets, make arguments as well as presenting facts. Kindred Britain is a proposition about the profoundly and unusually familial nature of British society and culture.
Kindred Britain is about relationships and connections - not a biographical site. For the most part, there is relatively little detail on the events and achievements of the people included here. This is not because such things do not matter but because, in the case of well-known figures, these details are widely and easily available elsewhere.
Kindred Britain is a social network, but Kindred Britain differs in being a social network from others of the modern day, like Facebook, because it is largely of the past and, unlike most work on ‘small worlds’, it asks how we can use contemporary theories to understand differently, not the present, but history
Who created Kindred Britain?
The three individuals principally involved in the creation of Kindred Britain are Nicholas Jenkins (Stanford University), Elijah Meeks (Stanford University) and Scott Murray (University of San Francisco).
Nicholas Jenkins originated, researched and oversaw the Kindred Britain project
Elijah Meeks was lead developer on the Kindred Britain site
Scott Murray designed the Kindred Britain site
Who is the intended audience for Kindred Britain?
What Kindred Britain offers is social network of the past, a genealogical history, and it really is intended for those who wish to explore those connections.
It is not for those who are looking for biographical information about a specific person, as this visualization is meant to highlight the networks and connections between individuals in Britain's history and provides only slight information about an individual.
So, someone looking to explore and understand a part of history through the lens of connections between people through time is the one whom this visualization is meant for. This may be a historian, or it may also be someone wishing to explore their own lineage.
What is the data behind Kindred Britain?
Kindred Britain presented a challenge that is growing ever more common in digital humanities scholarship: create a publication that ties together traditionally distinct categories of data in an accessible and scholarly manner.
In this case, it meant bringing together network data, geographic data, biographical data, and chronological data, while presenting that in tandem with traditional linear narratives.
How was the data collected?
Jenkins, the originator of Kindred Britain, had a question of his own about his lineage, and soon after finding more about his family background, he began researching the family history of poets that interested him and found himself researching a large sphere of people. He connected with Anthony Andrews, a retired British army officer who specialized in genealogical research.
Then, in collaboration with Andrews, Jenkins began to notice the existence of a vast network of connections.
And the more people he linked into this genealogical network, the more he saw that many other luminaries and well-known figures in British history could be fused into the structure he was uncovering. The more individuals and families he connected the more seemed to offer themselves for connection. Soon enough, the non-historian undertaking a historical project. A database was accreting, and it would become Kindred Britain.
Some resources used in creating the database that I found include:
PhpGedView, a revolutionary genealogy program:
Great Britain Historical Geographical Information System:
A Vision of Britain:
There was an earlier version of the database compiled by Jenkins at but it's been replaced with a link to Kindred Britain.
This is all the information I was able to find on the sources of data that Kindred Britain was based on. Furthermore, I read that the compiler of Kindred Britain made a conscious decision not to include references like footnotes for the sake of retaining broad accessibility and legibility.
How is the data stored?
The database populated by Jenkins was built using a popular web-based CMS for genealogy known as PHPGedView. PHPGedView provided Jenkins with the capacity to describe family relationships, annotate individuals with events, and place those events in time and space. It also gave indications of how data-driven narratives might take place in allowing users to explore paths between individuals as well as changing the perspective to geographic locations to see individuals associated with those locations.
But to provide better performance and more robust calculations, the database needed to be migrated to PostgreSQL, where sophisticated geospatial, network, and chronological queries could be brought to bear. The PostgreSQL version of the database employed several novel techniques to store and represent the genealogical data, including participation arrays, event periods, and network-based estimation of event dates.
What kind of data is represented and what are the shortcomings?
The data that is represented in Kindred Britain is not solely constituted of data available in primary and secondary sources - there is data represented by estimations and calculations that may be inaccurate or may have different interpretations. For example, as I will explain below, some data used to characterize individuals is a tragedy index, and tragedy can have different interpretations to people.
Calculating Dates and Date Estimates in Kindred Britain
As in most historical work, many dates available in Kindred Britain's primary and secondary sources are vague; just as often they are missing. This means we don’t know the precise start and end of many lives, or of the events within them.
The reconciliation of individuals in Kindred Britain with individuals in the Oxford Dictionary of National Biography required birth and death dates to identify possible matches. Where finer detail is available, it is displayed, but calculations are on a temporal scale of years. Four quality levels of year data are parsed: actual (YR), about (ABT), before or after (BEFAFT), and estimated (EST).The estimated year was computed as follows:
Parse all YR, ABT, and BEFAFT values available in the existing data.
Missing birth (or death) years are calculated for the individual. The intuition guiding the algorithm presumes that the relative ages of kin at various events (age at birth of children; age of spouse; age of parents at birth) will be comparable between individuals.
For families with complete data, compute an average age difference between individuals and other family members of different type, as a training set. In other words, assume there is an average age difference between spouses, between parents and children, and between siblings. The missing birth and death years are estimated to be the average of average distances for their kin with known values.
Individuals without birth information and with no relatives with birth information are not accommodated by this algorithm, but by running the algorithm recursively, estimated dates can be used to estimate dates, with predictably degenerate returns.
Shortcomings of this approach:
The birth dates and death dates that are calculated or estimated may not be entirely factual, and though Kindred Britain reports that for the most part their algorithms have produced a near accurate date for these events, it still is not always accurate.
Pros of this approach:
Because of the structure of Kindred Britain, it makes sense to want to have some estimated birth and death date so there aren't any awkward gaps in the information. For example, in constructing timelines, without being able to have a good estimate on a birth date or death date, it would be difficult to display that timeline, but it would be preferable to include that information about a link that could be important than to not.
Calculating Tragedy in Kindred Britain
Kindred Britain makes an attempt to summarize the level of tragedy in their lives using a computational approach.
In the case of our Tragedy Index, points are assigned for tragic events that can be gleaned from the events and attributes of individuals and their families. The use of points and scores implies a game perspective on the life of individuals and allows us to see the highest scoring in tragedy individuals in Kindred Britain. This took a dialectic approach, with the first tragedy index based solely on the lifespan of the individual and their parents and children. The individual scored a point if:
One died before the age of 45.
One’s parents died before one was the age of 13.
One’s children died before the child was the age of 13.
An individual would get a point for “dying young or of violence”. There is an attempt to determine if someone died of violence by reading descriptions of his or her death and searching for the following keywords: “battle”, “wounds”, “killed in action”, “hanged”, “shot”, “executed”, “beheaded”, “tower hill”, “Tyburn”, “murdered”, “stabbed”, “suicide”, “killed himself”, “killed herself” or “cwgc.org” in the description of their death event.
A point was also awarded for mental illness based on the presence of keywords “insane”, “breakdown”, or “lunatic” in any events associated with the individual.
Finally, a point was awarded for the death of every sibling before that sibling reaches the age of 13.
Shortcomings of this approach:
Tragedy may have different interpretations. Because there are very specific requirements for what tragedy entails in this visualization, it may not correctly represent tragedy in some individuals who have or have not experienced much of it. One view of tragedy may value the loss of life in battle as greater than the loss of life to disease.
An example of questionable interpretations of tragedy occur in the following example: Erasmus Darwin, who had 15 children by 4 partners and lived to the age of 71, had a life that was “four times” as tragic as Jack Kipling, who “only” died in battle at Soos at the age of 18.
Furthermore, there is a problem with any approach to compressing humanistic data into numerical data. This system of computing tragedy gives rise to the ever-present issue of sparseness in the database. If a family is not fully described in Kindred Britain then it can lead to an individual having a lower than actual tragedy score, just as an unknown death date may end up too early and give the family members a point for a falsely young death.
Pros of this approach:
This was, to me, one of the very interesting features of Kindred Britain. It was an interesting take on trying to quantify tragedies and compare the level of tragedy amongst other related individuals, to see if there are any other patterns.
At least, even if people may have different interpretations of tragedy, the meanings of tragedy within the context of Kindred Britain are consistent.
Calculating Inbreeding in Kindred Britain
Directionality coupled with pathfinding and specificity in the kind of relation determined ‘Inbreeding’, which attempts to find an ancestral path between an individual’s parents. So, for instance, if a direct lineal path could be found between two parents that terminated two generations prior indicating the parents were first cousins and so had one or more common grandparents then this value would be 5.
Shortcomings of this approach:
Inbreeding has specific societal connotations, so the points given to inbreeding may not be entirely representative of the lineage in a fair manner that won't be misconstrued.
Pros of this approach:
The determination of a common ancestor relays information that can be important in determining another way two individuals are connected.
Networks and Connections in Kindred Britain
Kindred Britain differs from these popular social networks is that the extraordinarily vague and malleable ways of connecting people in most social networks, as ‘acquaintances’ or ‘friends’, are rejected here in favor of something more clearly defined and restricted: family ties of blood or marriage. The iron law for inclusion in Kindred Britain is that an individual must have familial or marriage ties to someone already included.
Kindred Britain is constituted out of a network with a high degree of clustering and a relatively short average path length, given the spans or geography and chronology traversed.
Shortcomings of this approach:
A lot of important connections can be left out because of the lack of ties that go unacknowledged as those ties are not ties of family. So, relations between important figures in history may go undetected in the network when these indeed did influence the history and circumstance of an individual. So, by only focusing on familial ties, the lens in which Kindred Britain tries to understand the past is incomplete.
Another important shortcoming of Kindred Britain is the nameless throng of the unintegrated millions as well, which means that a lot of connections go unnamed, even some familial ones.
Finally, because it shows only shortest path connections between individuals, other networks that may connect individuals may be missed and, therefore, leave out important information. Many historically significant individuals are not part of this network. Amongst those individuals not (or not yet) included are: the poets Elizabeth Barrett Browning and Robert Browning, the philosopher Thomas Hobbes, the computer scientist Alan Turing, the playwright Ben Jonson, the scientist Michael Faraday and the fantasy novelist J. R. R. Tolkien.
Pros of this approach:
This is the heart of what Kindred Britain is about. Even though ties about non-familial relationships between people are not included, it creates a sense of focus for Kindred Britain so that it focuses on family trees, lineage, and ancestry. So, someone seeking answers in regards to genealogy and familial connections of an individual will know those connections will be made visible without clutter. It also makes visible the ‘small world’ nature of the Kindred Britain network, which was a goal of the project.
When considering these familial networks, I really like Kindred Britain designates as ‘married’ some famous same-sex couples such as those of Natalie Barney and Romaine Brooks, W. H. Auden and Chester Kallman along with Oscar Wilde and Lord Alfred Douglas. This decision has important consequences not only for the local texture of descriptions of an individual and his or her family, and thus, I personally feel is important to denote and acknowledge when it was not an act fulfillable in Britain at the time.
Why are the interface and visualization good?
Some features that really work well in Kindred Britain include the amount of features that can be the amount of resources that allow you to both explore the networks and learn about the connections between individuals.
Most visualizations are designed to serve one, but not both, of these goals. Typically, exploratory tools enable users to make some sense of data, to identify trends and relationships. These tools are used before it’s known what and if there is anything of value in the data set. Explanatory visualizations are designed to tell you a story of what is already known about the data. For example, most images created by newspaper or magazine graphics desks fall into this category, because they are trying to explain to readers what their reporting has discovered.
Some useful tools include:
The Networking Panel
It’s easy to pull up a network visualization on Kindred Britain. And, with a little practice, reading that visualization is not hard either. Here are the ways that people can be connected to each other in Kindred Britain’s visualizations:
A yellow line denotes lineage.
A magenta line denotes marriages, domestic partnerships and affairs. If two nodes are connected to each other by a magenta line, then the individuals are related through marriage (most commonly), a partnership of some kind or by an affair.
An orange line denotes siblings.
The visualization also gives a lot of different options for visualizations, to display different information about a network of individuals.
Transformations in Layout:
The TREE layout creates a family tree for a family or a dynasty, and a grid for a connection between two individuals.
The PLOT layout plots the nodes on the canvas by Year of Birth and Year of Death.
The FORCE layout arranges the nodes according to a traditional force-directed algorithm. This means that nodes are attracted to the other nodes that they are connected to, and pushed away from nodes they are not connected to.
The PROFESSIONS layout turns on polygons around nodes based on their occupations. This gives different approximations of social connectivity, to contrast with lineal connectivity.
This is a great way to show the same visualization in different ways, such as the tree highlighting generations in the visualization or displaying networks of people in terms of their professional circles. This can be useful in learning about a person's network.
An example below shows how you can change the layout to show professions, which is a great way to display information about a network of individuals:
Transformations in Color:
The CENTRALITY function colors the nodes according to their centrality values, which is based on their level of connectedness in the network.
The ODNB function colors the nodes by their ‘ODNBscore’, which is the distance a particular node has from a relative mentioned in the Oxford Dictionary of National Biography.
The BIRTHDATE function colors the nodes by year of birth.
The TRAGEDY function colors the nodes by their tragedy score. See the conceptual story on Tragedyfor more information.
The INBREEDING function colors the nodes by their relatedness score.
The DEPTH function colors the nodes based on the number of ancestors mentioned in Kindred Britain.
The GENDER function colors the nodes by gender. Male nodes are blue and female nodes are purple.
This gives a cool way to explore how people scale against each other in different aspects, such as tragedy, inbreeding, gender, etc., and to get more information about people in a network.
Color Differences below for Tragedy Coloration vs. Gender Coloration:
By dragging one node next to or on top of another, you can also explore Kindred Britain in two other ways:
When the node’s blue penumbra turns orange, a comparison box will appear relating the two individuals in terms of historical time and differing lifespans. If there are any professional similarities, the box will also show these.
When the node’s penumbra turns green, you can release and doing so will prompt Kindred Britain to update the screen to show the familial path between the two individuals.
This gives a really cool and intuitive way to connect people and view relationships between them, rather than searching them in the connection tab.
The Timeline Panel
This is a useful way to visualize individuals in terms of their lineage, events in their life, and events in that year generally in Britain.
Blue circles, located throughout an individual’s lifespan bar, represent births and deaths.
Purple circles represent other types of events that took place during the individual’s life.
Green-gray bars represent a birth, and connect the blue circles of individuals involved with that birth.
Purple bars represent marriages or domestic partnerships between two individuals, and connect their corresponding event circles.
Divorces, which are also represented with a purple bar, are distinguished by connecting gray circles from two people.
In browsing the Timeline, historical events will appear at the bottom of the panel to provide some context to the lifespan bars, and this is nice to have some perspective of the time.
The Geographic Panel
Another interesting visualization is the Geography Panel, which provides you with a map of the world, with highlighted regions to denote the different places that the people of the current visualization are from.
It's visualized just as a world map that shows where a network of individuals are from. If you hover over an area, you can see the list of people from that area.
Another nice feature is that you can also get rid of the city names if you prefer.
The main menu is a wonderful way to get started in the environment when you don't have an exact start in mind how to start searching and gives some curated, interesting connections for you to view for yourself. In a way, it's a great way to get familiar with the visualization, how it operates, and what to expect when performing searches.
The three main menu features are:
They align with the goals of the Kindred Britain project, which was for it to be both explanatory and exploratory, and this fulfills both of these goals.
There are four different ways you can perform searches in Kindred Britain:
To narrow your search, each of these search functions, except for Recent Views, uses a feature called a Birthdate Bar. By default, the Birthdate Bar is set to ‘Born anytime’. By dragging the left and right handles on the blue bar, you limit your search to individuals born within a particular time period, which is an intuitive way to use it and useful when you are hoping to search within a certain time period.
The Recent Views tab in the Search dropdown keeps track of the last five visualizations that you have viewed, which is useful if you want to backtrack.
Finally, another aspect I really liked about Kindred Britain was the Biography Boxes, which included information about an individual by clicking their name.
This makes it easy to know who the person is and a few details about them—for example, some events in their life, why they score higher on tragedy, if they were married, who they’re connected to, when they died, etc.
What doesn't work about the interface and visualization?
There are a few things that I did not feel worked in the visualization.
Firstly, and most of all, was that it wasn't immediately intuitive. For a project of this scale, that's a bit understandable, but as a creature of the modern day, I want something I can understand without reading any directions. Below is an example of the opening screen, which gives you a bit of a tutorial on how to use it, which I wish wasn't necessary in the first place.
Furthermore, looking to the example picture above, it can be a bit difficult getting a sense of direction just by looking at a network of nameless icons that are only identified by colors that show gender, profession, etc. Of course, it is a tradeoff between clutter and not including the names, but it seems like it would be useful to have a list of names on a page for a network of individuals.
One thing that was particularly annoying about using the Network Panel was being unable zoom in and out, which is especially useful for a visualization of a network, where it's natural to want to hone in on details of a network or see a big picture. This was a huge annoyance in interacting with the visualization for me. The only way to move around the panel is to drag, which should be available but shouldn't be the only way to move around the panel.
Another problem with the visualization that I had was how the Timeline and Geography Panels would take up space on the page even when they weren't being used. At the picture above, you can see that timeline and geography, though minimized, are still taking up a decent amount of space on the bottom of the page when they could have been elsewhere when not being used.
Therefore, as can be seen above, the gear box interface would get cut off for the network tab and just cannot be seen. I didn't know for the longest time that Siblings were represented by an orange line.
Finally, some color scales, which are meant to differentiate different portions of information, have the same color scheme, which doesn't make it intuitive to know what you're looking at if you forget.
The Network Panel
The Geographic Panel
For the geography panel, it wasn't originally intuitive that it represented where a person came from. If I hadn't read it in the documentation, then I would have never known what it represents - where they're from, where they died, where they spent the most time in their life?
The thing that I did not like about the search bar is that, while I like the Recently Viewed option, I did not like that it only goes back by five searches. Also, in the beginning, it is not intuitive where you can find this Recently Viewed button, as it does not really match the whole idea of search, which is an exploratory, open-ended sort of a feature, unlike Recently Viewed.
The Meanings and Scales of Certain Features
It is not clear what certain abbreviations mean or what is denoted at first glance. For example, a scale of Tragedy points is not an intuitive thing to understand, as human beings interpret tragedy in many different way, and it's generally not numerical. Human beings also do not interpret Inbreeding, for example, numerically.
Also, scales given by centrality, depth, or ODNB aren't easily understood without looking at some documentation for what each scale means and is attempting to portray.