By Greta Swain
Originally posted on the Digital History Fellowship Blog at the Roy Rosenzweig Center for History and New Media (RRCHNM). Click here to see the original post.
The Public Projects Division creates tools, projects and collections that encourage greater interaction with history among a popular audience. Some of the division’s projects are geared directly for public engagement while other tools help public history professionals more easily create collections, exhibits and projects of their own. During our four-week rotation in this division, we worked primarily on two projects, Omeka S and Mapping Early American Elections.
One of the most well-known and in-demand tools that RRCHNM has created, Omeka, comes out of the Public Projects Division. Omeka was released in 2008 as a web content publishing platform that would allow for the assembly, management, and exhibition of digital collections. Omeka S, the Public Project’s newest addition, builds on the popularity of Omeka Classic. Omeka S allows users to create and manage multiple Omeka sites on a single install. It also boasts new modules (plugins) for mapping and importing collections from other systems. Additionally, it allows users to share resources and collections among their multiple sites, and assign distinct privileges to different levels of users.
When we began our work with Omeka S, it was in its final phase of testing, but as of yesterday, Omeka S: 1.0 has officially been released. To start out, we worked with Megan Brett, the Omeka End User Outreach and Testing Coordinator. She taught us how to work with with GitHub and secure shell (SSH) via the command line to install themes and plugins on an Omeka install. Then we worked to simultaneously review the existing Omeka S documentation while testing the instructions on the dev site. We were asked to proofread, not only for spelling and grammar errors, but more importantly, for readability and usability. Did the directions make sense? Were there enough screenshots to help the user follow along with the text? Were the screenshots current? Did they display what a user would really see on his or her screen? Did the dev site respond in the ways that the documentation suggested that it should?
This process of reading and testing gave me firsthand experience with using Omeka S and provided me a more profound sense of the tool’s capabilities. It has enabled me to confidently describe Omeka S to others and explain how it differs from Omeka Classic. Finally, it has encouraged me to explore how I can use the new features of Omeka S in my own work.
During the second half of our rotation, we worked on the Mapping Early American Elections projects. As an Early Americanist, I was excited to work on a project in my favorite era. Although I normally focus on women, gender and social history in this period, looking at the early elections was really fascinating. At the time we (briefly) joined the project, the project team had already created a data set based on the information collected in A New Nation Votes (NNV). They were in the process of creating maps from that data set to represent each Congress in each state in order to help visualize the votes based on political parties.
In addition, they were adding brief interpretive text to each map to explain how each state’s election system worked and to call attention to any interesting aspects of the elections or trends from the previous election. To get a taste of this work, we were asked to write the interpretive text for all the states during the first three Congressional elections. Writing this text required us to look at each visualization (map), compare it to the chart devised from the data set, compare it to the data tables, footnotes and research notes provided by NNV, and then complete additional research for some of the more complicated elections. After we finished writing our interpretive text, Dr. Lincoln Mullen taught us how to use markdown and GitHub to add some of our text to the dev site for the project.
As a student of history, I really enjoyed the historical inquiry and analysis associated with this assignment, as well as the larger questions that the work forced us to discuss and try to answer. First of all, it reminded me how much I like the investigative and interpretive work of history–trying to sort through many different pieces of evidence in order to form one’s best (informed) guess or interpretation of what happened in the past. The more I found out about each election, the more digging I wanted to do.
Secondly, the work forced me to ask bigger questions like, what does it mean to be elected? In our original instructions, we were asked to mention in the text how many candidates from each political party were elected. While this at first sounded straightforward, we soon found out that it proved more difficult. For example, what about elections where one candidate received the most votes, but then the election was contested, votes were later ruled invalid, and the results were officially modified? What if a candidate received the most votes but died before he could take office or he declined to serve? Is there a difference between who was elected and who served in Congress? These and similar questions were discussed during the project meetings before settling on a more precise definition for the project.
Most of all, this project showed how me how digital history projects can make an argument and contribute to the historiographical conversation. Dr. Rosemarie Zagarri, the Lead Historian on the project, writes in the project’s blog in a post called “What Did Democracy Look Like? Voting in Early America” that “Early American elections subvert conventional notions that portray the development of early American democracy as an orderly or systematic affair.” Doing the research required to write the interpretive text really drove home this argument. Early American elections were, in fact, really messy. After the Constitution was ratified, elections didn’t just automatically happen in an organized and efficient manner that was consistent from state to state. As Zagarri asserts, it was an era of experimentation.
By looking at the voting practices and results for several different states during the same election, it was easy to see how the election systems varied state by state. For example in the First Congress, Delaware’s election law required voters in each of the state’s three counties to submit names of two persons they wished to elect. Of these two persons, one was required to be an inhabitant of the voter’s own county and the other needed to be from a different country. The person who received the most votes overall (at-large) would win the election. In the First Congressional election in New York, on the other hand, the state was divided into six districts and voters in each district elected one candidate to represent their own district.
The experimentation of the era, even within an individual state, was also evident by looking at change over time in a single state during the first three Congresses. A great example of this is Pennsylvania. For the First Congress, Pennsylvania held an at-large election where voters were allowed to vote for eight different candidates who could reside anywhere in the state. For the Second Congress, Pennsylvania created eight districts, and only allowed voters to elect one candidate who had to reside within their own district. For the Third Congress, Pennsylvania’s number of congressional seats increased from eight to thirteen (following the results of the 1790 Census) and consequently, the state discontinued its use of the district system, and instead switched back to an at-large system like they had used for the first congressional election. Examples like these provide strong evidence that supports the project’s historiographical argument.
Overall, I enjoyed the mix of technical and more traditional (research and analysis) aspects of working in the Public Projects Division. Even though I am leaving this division, it will be interesting to track both of these projects as they progress; I will be curious to see how users respond to Omeka S in its first few weeks post-launch, and to discover what findings come out of the Mapping Early American Elections project.