Ghost maps and urban networks
Johnson, Steven. (2006) The ghost map: A street, a city, an epidemic and the hidden power of urban networks. London: Penguin.
Steven Johnson describes vividly how Victorian cholera victims fell ill, remaining mentally alert as, in excruciating pain, they witnessed their bodies emptying, fluids gushing out, leaving them shrunken, blue-skinned cadavers within 48 hours. His account is all the more terrifying because I am aware that similar deaths from cholera are still taking place pretty close to home, with cases in KwaZulu Natal recently and in Zimbabwe in 2009 and earlier this year as well. The difference is that Victorian authorities obsessed about the evil ‘miasmas’ or gases associated with the squalid living conditions of the lower classes that they believed caused the disease while we know both the causes and treatment for the disease. The vibrio cholerae pathogen is water-borne, and, ironically, cholera sufferers must be treated by rehydration. Today, cholera deaths are an absolute indictment of public health in a region.
What does this have to do with information visualization? Johnson details how Henry Snow, a physician and amateur scientist collaborated with devoted clergyman Henry Whitehead to solve the riddle of the source of a cholera infection around Broad Street in London (now Broadwick street in Soho). The two used the local knowledge of the infected community to make the maps that helped to counter prevailing orthodoxy, save many lives and introduce the kinds of public health strategems that make today’s mass human settlements viable.
Snow mapped the locations of the sick in relation to water sources, and his map showed how the site of the outbreak corresponded with the actual distances that various residents had to walk to get water in relation to the infected Broad Street pump.
This particular visualization technique is known as a voronoi diagram, and as historians have pointed out, in this case Snow was mapping time (the time it took to walk to a source of water) as well as the spatial layout of the epidemic. With the help of Whitehead’s intimate knowledge of the affected community, Snow was able to prove that the index case of the cholera epidemic, or patient zero, was a young baby whose mother had washed nappies and disposed of water into a cesspool that drained into the pump. This action sealed the fate of the many nearby residents who walked to the Broad Street pump and drank its water over the next two weeks.
Johnson’s account left me with a renewed optimism for the rapidly growing urban networks at home in South Africa, and the probable future megacities which are likely to form if our current rapidly urbanising trend continues. As he points out, the Web links institutional knowledge with local knowledge of amateurs, and (in certain contexts at any rate) it has never been easier for local knowledge to find its way onto a map.
“Where Snow inscribed the location of pumps and cholera fatalities over the street grid, today’s mapmakers record a different kind of data: good public schools, Chinese takeout places, playgrounds, gay-friendly bars, open houses. All the local knowledge that so often remains trapped in the minds of neighbourhood residents can now be translated into map form and shared with the rest of the world.” (2006:219-220)
This is one of the reasons that I am particularly interested in exploring applications of the South African mobile locative social network The Grid. I’ve done some research into local geo-tagged images posted to The Grid from Guguletu which has been fascinating. I should say that my optimism is tempered by awareness of the many barriers and mediators between local knowledge, online publication, and institutional knowledge in the South African context. Johnson discusses how such online networks assisted in the measures taken against avian flu or H5N1. The more recent story of the tweet-fuelled H1N1 panic shows how such systems change the landscapes that they map, and is also a reminder that publics, media and public authorities can be all-too-fallible when they use such systems.
Many thanks to my host, Denisa, for letting me stay in her apartment and giving me access to her wonderful library while I am here.
Lyndon Daniels and I will be collecting examples of open source visualisation tools and track the progress of our project by posting them here over the next two months. I will kick off with Steve Fortune’s voronoi polygon generator, written in python.