Networking in Maps, and a little confusion.

Previously, I made a blog post about Palladio and creating “special” maps. This week in class, we went a little further and used Palladio to make a map of networks. In the article “Demystifying Networks”, Scott Weingart explains network in the simple terms of “stuff” and their relations.

We were given a data set to use by Marten Durer h people in the time of World War II that showed such things as t heir gender, who gave/received help, and who may have given help or received it. It was a lot of information to take in since it was all on a spreadsheet, but once I put it into Palladio and generated a network map, there were different options that I could choose so I could see the information in different ways.

giver and reciever new

The first attempt of the networking maps that I made is of the one above. I screenshotted this from the Palladio website and whenever I do that it does come out blurry so the names are probably hard to read on this. For this map, I selected it to show the network between the gives and receivers.  Essentially, this map shows who gave help to who and who received it and the string of networks that these people were in. It’s hard to see, but there are darker circles in this map that represent people who both gave help and received it as well.


The second map I attempted to do was “race”. This map essentially made separate networks of people based on their race and it was actually kind of interesting. Part of the map cut off in the screenshot, but there were more networks down below that were very minimal. The biggest network in the middle was all German names and had multiple repeats. The people with the same last name were networked together. Below the large network were two smaller network of people also grouped together by their race. What I found interesting was that “AushweisNazi” was on the edge of the large network alone connected down to a smaller network. I am not quite sure what that means and couldn’t really figure it out.

I think I had a harder time deciphering what these maps. With the Spacial Maps, everything is clearly labeled and obvious to explain. With networks, there are so many names that are connected that for me, it is hard to tell what they represent. Overall, it is interesting to see how many data points connect though.


Spacial Maps

In class, we have been talking about the difference between maps and “Spacial Maps”. Essentially, Spacial maps are not your ordinary 2D map but instead have many different layers to it. Spacial Maps can be interactive and show such things as, how many people migrated to an area at a certain time, the distance that a herd of animals traveled, or even where a photograph was taken. In an article by  Jenna Hammerich that we read in class, she talks about how this technology can answer historical questions  such as  “Why did African American families settle almost exclusively on the near north side of St. Louis in the 1940s?”. Below is a link to an example of a Spacial Map made by the Humanities Team at Standford:

I used the website to create my own spacial maps using the Cushman Collection data set.

paladio map 1

This is one map that I created. The “dots” are all based off of a data set and represent where each photograph was taken.  To make this map, I simply uploaded the data set and added the layers of geocoordinates and land.

palladio 2

In the map above (I know it is a little blurry that’s how my screenshots kept coming out whenever I saved them) I used the “size point” future on the dots instead. With the size point feature, the dots appear larger where more photographs are documented. I also changed the view of the map to ‘streets’ so that I could see actual state / city names instead of just land. Large dots appear frequently in California so I can learn that a majority of the photos in the Cushman Collection were taken on the West coast of the United States.

cali map

Taking it a step further, I focused in on the map in California so I could see which cities actually had the most documented photos. From this, I was able to see that there were a lot of photos scattered along the Bay such as San Francisco and Oakland. However, Salinas, Fresno, and Los Angeles had the largest dot sizes telling me that those cities individually had a lot of photographs taken there.

This map, that I found on is a economic activity map. This map is very similar to the Spacial maps that we have gone over. It has a legend in accordance with colors that shows where in the south there were farmers, forests, manufacturing and trade, livestock, fishing, mining, and places of no activity.

Screen shot 2010-10-22 at 2.27.28 PM