When I started with my digital humanities project of mapping the rowing programs of the United States, I knew it would be a large under-taking. I just had this desire to map the rowing programs of the U.S., and allow it to demonstrate the different types of programs, since that didn’t exist. Continue reading →
My digital humanities project includes mapping the northeastern U.S. boathouses, from as far south as Virginia and as far north as Massachusetts. The goal of this is to show where the clubs are located, what types of clubs they are (high school, juniors, collegiate, masters, etc.), the genders the clubs are open to, and whether or not they have a structure protecting their boats (boathouse, tent, open racks, etc.). Boathouse is a generalized term for the structure that houses the boats of the team. Some teams may not have an actual structure protecting them, they might simply have open racks to the outside world. Other teams may have a tent-like structure protecting their boats from the elements of above. Generally, the older the program, the more likely they are to have an official boathouse, with an actual building and potentially meeting spaces, restrooms, etc. The more prestigious the club, the more likely that boathouse is to be used for social events in addition to rowing. As a rower or coach is traveling throughout the northeast, they would be able to use this map to see where clubs are located and if they would be able to visit and participate.
Crowdsourcing allows a project to get more work done with more people working it. Often, digital humanities projects simply don’t have the funding or the staffing to be able to take on the huge task of digitizing all of the documents in their archives. Often, the documents and artifacts get imaged and placed in an online database. Crowdsourcing becomes a valuable resource at this point.
Voyant, CartoDB, and Palladio are all digital tools to help the public humanists to create visualizations of the data they have collected. Voyant helps users examine the usage of words throughout text-heavy documents. CartoDB helps users map data on a geographic map and share the information presented on those points. Palladio allows users to create network visualizations of data sets, and examine the complex relationships. All three tools are incredibly helpful for the digital public humanists. All three are fairly user-friendly, as well.
Each tool reveals something different about a given data set, depending on what the user wants to examine. Some researchers may want to simply see a geographic map and the data points layered over it, therefore they would use CartoDB. Other researchers may want to see the regularity of word usage, in order to examine trends in an overall document, therefore they would utilize Voyant. Even more researchers may want to examine the networks and relationships between the data points given, not necessarily worrying about the geographic locations given maps, therefore they would use Palladio. It would be possible to combine the different tools to create a hybrid of the data presented, such as a network visualization layered over a geographic map, both to see the locations and relationships given in the data set. Voyant could help the user note the major topics covered, which then could be used as data sets for Polladio, which would help visualize the relationships between those topics and other data points. Polladio could be used to visualize networks that could be also visualized on a geographic map. The different tools can complement each other well, while revealing new points of view to analyze. These three tools are incredibly valuable for a digital public humanist.
Palladio is a digital networking software that enables users to map the connections between different data points. It allows the users to see multi-dimensional data on a networked visualization. It allows the user to think humanistically about the data, and not just as statistical data points. It is fairly user-friendly, allowing for numerous manipulations based on the data given.
This week’s project included using Palladio to map the networks of complex ideas and topics given in the WPA Slave Narratives. We examined the different topics and their relation to multiple data points: age, interviewers, sex, type of slave. It allowed the users to see the complex relationships between interviewers and interviewees, as well as the different topics covered by each. It allowed us to examine the relationships, separate from the locations. We were able to use the locations as we saw fit, but it presented an entirely new level to analyzing the information that a simple geographic map could not provide. The network maps showed that the slave experience was very similar, whether they were house or field slaves, or based on where they lived. It didn’t matter if a person was enslaved in Virginia or Georgia, they had very similar experiences overall.
Palladio helped visualize that information simply for a large data set. Those connections would have been incredibly difficult to make without going through each interview individually to examine the topics, gender, age, locations, etc. Palladio was user-friendly for this project, and made it much simpler to examine and analyze the information presented.
CartoDB is a digital mapping software that enables the user to insert data points onto a map. It can be numerical or categorical data, just so long as it has locational data as well. The mapping software allows users to easily import a database of information, from an online source, Excel, GoogleDoc, etc., in order to plot those data points onto the map. The map that a user could receive might be as simple as a point map that simply shows where the data gets plotted on the map, or it could be as detailed as having a time lapse and density cluster shown at the same time. The type of information shown depends on what exactly the user wants to see.
In our activity, we used data from the WPA’s Slave Narrative Collection. It included data such as location of interview, interviewee, interviewer, gender, location of birth, location of enslavement, type of slave, etc. We were able to import the data spreadsheet very quickly and painlessly, which then quickly created a map that had the data points layered over it. You can choose which data you want represented from that database, and then change how it is represented, based on whether you want a point map, a cluster map, or a categorical map. All of which are manipulatable depending on the information you are seeking to depict. The maps are then easy to export and publish for other people to view. The site is laid out in a straight-forward fashion, and it is mostly user friendly. It is somewhat confusing on the different types of maps, but it then gets more user-friendly as you continue to use it more. CartoDB also offers multiple tutorials and FAQ if you are struggling with it.
Voyant enables users to “see through” their text and recognize patterns and provide a system of analysis for digital texts. It compiles a word cloud and analysis of words in a given text. It also compiles word trend graphs to note which words are used in what frequency. It is a helpful tool to easily grasp the common words and themes in a digital text.
Metadata is a term that includes the data that which makes up the background information of a work. It makes information searchable, it makes information categorizable, and it makes information workable in a digital format.
On the topic of databases, I have reviewed What’s On the Menu, published by NYPL Labs. I am going to continue reviewing its use of metadata.
What’s On the Menu, by NYPL Labs
What’s On the Menu is an online database of historical menus from restaurants. It is part of the collection of menus in the New York Public Library’s rare book collection. It includes about 45,000 menus from the 1840s to the present. NYPL is working to transcribe and digitize all of the menus and geotag them in order to better help researchers.