Mapping tools allow users to organize, search, and contextualize sources and information using spatial and chronological referents. These tools enable us to create visualizations that represent the different types of information contained in a dataset, the geographical points of reference for sources, and the chronological evolution of sources and their content.

The exercise using Kepler shows that even an entry-level mapping tool can prove very useful to create visualizations that communicate different aspects of the data included in a collection of sources. For instance, the first map we created was a point map. In this type of map, every item of data (in this case every interview) appears as a single dot in a map. The number of dots in the map is equal to the total number of interviews that were conducted in the state of Alabama within the period of time covered by the dataset. This kind of map also allows the user to get some basic information about each interview, such as name, age, gender, and place of birth of the interviewee. When designing the map, it is possible to customize the kind of information available to the viewer. I found this to be a very useful entry point to the data and one that can be customized to facilitate different types of searches.

We also experimented with cluster and heat maps. These maps are meant to represent, respectively, the absolute and relative density of interviews in a particular area. I found the cluster map easier to interpret. If one hovers the cursor over the clusters, one just gets the total number of interviews included in that cluster, but no information about particular interviews. I found the Heat view more difficult to interpret, but I admit that this may have been my fault since I was not entirely sure what this view was meant to represent. Furthermore, the heat map does not offer any additional information about the interviews represented in this type of map.

My favorite map was the timeline map. This is a point map with a timeline attached to the bottom. This map allows the user to locate all the interviews conducted in the state of Alabama during the period of time covered by the data set. It also allows one to see when those interviews took place within the timeline. One can still get information about individual interviews by placing the cursor on a point in the map. In addition, one can use the slider in the timeline to see points appear in the map as time goes by. This map adds a temporal dimension to the spatial one already represented by the map.

We also experimented representing differences between the interviews contained in the data set. In this case, we chose the field “Type of Slave” to be accounted for in the visualization. In this version of the map, one could see points of different colors depending on whether the interviewee was identified as a house or field slave, or both. 

Working with Kepler confirmed my opinion that mapping tools can be useful when presenting, exploring, and analyzing data. Tools like Kepler have something to offer the observer or casual visitor to a site. They enable the creation of powerful visualizations that synthesize a large volume of information in an interface that is familiar to most people. We saw a great example of this in the Histories of the National Mall project. Researchers who are just getting started working with a collection of sources, will also find map visualizations very useful. A good example of this was Photogrammar, which offered a very flexible interface that allowed the user multiple points of entry into the collection. But more experienced researchers can also find use for these kind of tools. Mapping the Gay Guides illustrates how a thoughtful preparation of the data that considers and accounts for changes in the sources themselves, allows researchers to identify and document patterns that would be more difficult to detect if one was just reading the original sources. Overall, these sources facilitate cross-referencing between different possible areas of analysis. Mapping tools are most useful when they can offer a diversity of entry points and the possibility to see how changes in space and time affect the ideas and experiences represented in the data.