Last week, we have learned a bit more about Palladio through how it graphs its given data. It became an interesting experience as it presents itself as another way to help people understand information through visualizations. This is similar to mapping data from analyzing what we visually see and then be able to relate to it. According to the Demystifying Networks reading, it explained how representing the information through networks implies in comprehending whatever is going on. I was able to see how networks analyze data from the dataset during the tutorial in class.
First, I loaded in the dataset that provided the people and relations that they had. The data that I used was about the people who offered to help others who were facing some trouble during WWII. Then, I set up the settings that provided an outline between the givers and receivers. Finally, I narrowed down both the facet and timespan filters, which quickly reduced the number of people and relations. In comparing these two visualizations, I noticed some differences when playing around with the timespan. The timespan in the second picture expands “between 0011-12-22 and 0013-12-29” in which it shows the each of the relations between the contributors and receivers. The larger relation from both of these pictures show that they kept the same relationship as time passed by. However, there were some differences between the smaller relationships as they expanded a bit throughout time.
In conclusion, analyzing data through networks is useful in providing an understanding of the information and offering an explanation to what it represents.
Sometimes it is difficult in analyzing a map, but for this assignment it seemed like it was easy to understand through a few simple processes in Palladio and Google Fusion. For these visualizations, I wanted to see specifically where most of the photographs from the Cushman Collections were taken in California. The red dots are the geocoordinates of where the pictures were taken. In comparing the two maps from these different programs, they have some interesting qualities that makes them unique.
When I developed these visualizations, I simply loaded the Cushman edited spreadsheet into the sites, applied the geocoordinates and made them visible to view, and outlined the California borders in order for the viewer to see the coordinates within the state. The Palladio map shows the same geocoordinates as the Google Fusion map, but they are different from the layers that I offered for Palladio. However, Google Fusion map does not offer a lot of choices in changing the map’s background, unlike what Palladio did.
From looking over at these maps, they helped me understand how these pictures correlate with each other. In the spatial history reading from Zephyr Frank, he explains that spatial history teaches us the importance of space in offering us a historical outlook through visual analysis. Both visualizations show the spaces in between of where the photographs took place in; when analyzing them, they were mostly taken around the coastal, central, and southern areas of California.
Overall, they were quick and easy maps to create and they provided interesting information to me visually about the Cushman photographs in California.
We have learned how to use Palladio today and it was interesting in making the maps. This map is based off of the Cushman Collections on where the photographs were taking place. Most of them seem to be around the United States, mainly in places like San Francisco and Chicago.
Last week, my Digital Humanities class has been busy with creating a public website about martyrdom through Omeka. We worked on this website in order to help us analyze martyrdom and develop some connections with other historical artifacts or pictures that relate to it. Apparently the whole process in developing a resourceful website for others to see and use seems a bit more difficult than it looks, but I guess it takes some time to get used to it and learn more about what it can do.
Omeka has enabled me to consider a little bit more about the items that we set up online and add them to the collections. In comparing Omeka with WordPress, the site was careful in asking many questions about what the item was, where it originated from, and if we had the right to use it. This relates to Leopold’s, Articulating Culturally Sensitive Knowledge Online: A Cherokee Case Study in that it talked about how sensitive some items of a culture can be when it becomes public. When searching for items to include in the collections, it seemed a bit difficult to understand what the site was asking for from the various questions it provided to us, but it became a simple process in the end. Establishing the exhibits became interesting in thinking deeply about exhibit’s topic and utilizing different items for supporting our theme on martyrdom. These exhibits required a lot of research on the items chosen since they had to relate to martyrdom in any way from the time it took place to how it was portrayed in other works. Metadata takes uploading items seriously as it required information that not a lot of people would look at for any website.
Overall, the site has been useful in setting up a site that would be helpful for others in understanding history and culture.
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