Week 5- Locating London’s Past

For this blog post, I chose the map “Locating London’s Past.” This map uses a GIS interface in order to enable researchers to visualize and map data about London from the seventeenth and eighteenth centuries. This is done against a 1746 map of London created by John Rocque and the first accurate OS map. The project was carried out by several English Universities and institutions with the help of grant funding. They created their own online geocoding tool in order to carry out automated matching of location data as well as manual checking of that data.

The map allows you to choose between 5 layers which are 1746, 1869-1880, blank, map, and satellite. Then you can choose what data you want mapped by selecting one or more datasets such as Old Bailey Proceedings, Coroner’s Records, Criminal Justice, Four Shillings in the Pound Tax, Fire Insurance, Plague Deaths, Glass, and Population and Area Data. From there you can narrow down the data to specific parameters such as gender, keywords, and dates. The data that matches these parameters will then be mapped based on the geolocation of the records.

Turnbull states “a map is always selective. In other words, the mapmaker determines what is, and equally importantly, what is not included in the representation.” This definitely applies to Locating London’s Past. The mapmakers have decided to focus on mapping data from legal documents such as death records, insurance records, hospital records, and criminal records. It comes from the point of view of the government, given that these are documents that governing bodies collected. Furthermore, it reflects the viewpoint of the Universities that created the map because they are the ones who decided to use these specific datasets.

The map reveals how different points of data are geographically situated in regards to each other. For example, when looking at data from the plague datasets, you see that the deaths are all located very close to one another. However this map obscures the historical contexts in relation to these data points. That being said, you can research the datasets on the website and find out what mapping these points can show, but it isn’t readily available. For example, the authors state that by mapping the four shillings in the pound tax data set, you get an idea of the wealth distribution about London during that time. However, by having to toggle back and forth between that information and the visualization, the website does not provide a cohesive experience. I would suggest redesigning the map so that the historical relevance about the datasets were present when you mapped the information so that users get a better understanding of what the data actually shows about London’s past.