Data Structuring for DH Mapping

When working on a digital humanities mapping project, it is easy to get carried away thinking about the possibilities of your work. You could measure the way that characters move in James Joyce’s Ulysses; which rivers are mentioned most often in ancient Greek myth; or the way that urban centers function in Ling Ma’s Severance. All of these are valid topics to explore using digital mapping. But, before you can make a map, you need a dataset.

But what is a dataset in the humanities? Can you make one? If you think about “data” as meaning “information,” yes, you can. Your dataset might include information like: character names, place names, geographic coordinates, time and date information, descriptions, and even images. What is important to remember is that your map will only be able to show the information you have in your dataset. If you want it to show images of mountains when you click on a mountain on the map, you will need to include images in your dataset.

The way that you create your dataset is also important. For example, Google Maps gives you the option to plot out your locations by clicking on their place in the map. Although this is easy, you should avoid doing this in a DH project. If you plot point by point, if you want to transform your map later on, or change to a different mapping tool, or visualize your data in a different way, this will be much more difficult because your data is not structured to accommodate that.

It is best to design your dataset intentionally. Your dataset should preferably come in the form of a spreadsheet (such as .csv or .tsv files) and be designed in such a way that it is easy to add or subtract data as you research. By putting your data into a spreadsheet, as opposed to mapping it out by hand (or cursor), you can ensure that your project will last longer and be easier to migrate to another tool if you ever need to.

• Check out the Humanities Data LibGuide.
• Set up an appointment with a data librarian to talk about digital humanities data.
• Attend our DAVis workshops.
• Visit the dataCAVE.