Palladio is an interesting tool to use and is a bit more complicated than advertised. While other mapping programs were guessable in that the steps used to generate a map could be done by clicking buttons randomly (please take this with a grain of salt – I’m joking for the most part), Palladio would almost certainly require a guide. Additionally, there are glitches in the program when occasionally, the program would freeze. In the tutorial, I tried out both Palladio (the first picture) and Google Fusion Tables (the second picture) for mapping. While Google Fusion Tables also works for a similar result, its functions are nowhere as in depth as Palladio. It is, however, easier to use. As seen in the picture, both have a function that depicts what type of relationship people have to each other. Google Fusion Tables does utilize color and directional arrows, and Palladio does offer a function that allows a person to switch off between two data sets. The advantages of Palladio and Google Fusion Tables are clear. For me, I’d prefer using Google Fusion Tables for the ease of use and when I wanted to make something more visually appealing. However, Palladio would be the main choice if I were to seriously map out relationships for the purpose of studying them.
This time around, I focused mainly on Palladio. The uses of Palladio consist mostly of mapping out relationships between two or more things, represented by nodes and edges, as explained by Scott Weingart in his article, “Demystifying Networks.” It is useful not only for mapping out relationships but also seeing how people connect with each other. As Kieran Healy demonstrates in her article, “Using Metadata to Find Paul Revere,“ she is able to utilize several matrices and mapping tools to not only show who has a relationship with each other but which of their parties connect the most. In the present-day setting, something like this would be extremely useful for ferreting out hostile groups. And even if not for that, it would still prove to be useful in gathering data, allowing a person to more accurately aim their advances towards the right group (i.e. attempting to research a certain topic and going around talking to related individuals.
In the example I used, the data set was of primarily the relationships of Ralph Neumann to others. The relationship network demonstrates who was a giver and who was a recipient of help (if not both) during the time of the Holocaust. Ralph Neumann was hiding underground along with several other people to escape prosecution. Here, as opposed to the first picture of Palladio, I used sized nodes show the people who were connected with each other the most and those who received the most help. As this is a data set on Neumann, naturally, he had the biggest node of all. There was also a timeline function that allowed a person to edit the time of help, which can be seen in the second picture.