About

Producer

Sharon M. Leon is an Associate Professor of History at Michigan State University, where she is developing projects on digital public history and digital networking projects related to enslaved communities in Maryland. She is a principle participant in MSU’s Consortium on Critical Diversity in a Digital Age Research initiative. Leon received her bachelors of arts degree in American Studies from Georgetown University in 1997 and her doctorate in American Studies from the University of Minnesota in 2004. Her first book, An Image of God: the Catholic Struggle with Eugenics, was published by University of Chicago Press (May 2013). Prior to joining the History Department at MSU, Leon spent over thirteen years in George Mason University’s History Department at the Roy Rosenzweig Center for History and New Media as Director of Public Projects, were she oversaw collaborations with library, museum, and archive partners from around the country, and served as a Director of the Omeka web publishing platform.

Collections Consulted

Research was conducted in the following collections, housed at the Booth Family Center for Special Collections at Georgetown University Library:

Research Goals

In contrast to the approach that an individual genealogist or descendant might take to the materials, I am working to understand the community as a whole across all the Jesuit-owned farms during the period before the major sale in 1838. In addition to the traditional historical methods of archival research, I am using linked data, digital visualizations, and perhaps social network analysis to provide both a micro and macro view of the community and its experiences. Thus, I am experimenting with visualization techniques to offer a macro-level entry point to these individuals and their relationships that will allow both scholars and members of the interested public to get a sense of the whole community over time. I am approaching this work with several key questions:

Audience

I have been conducting this work with a number of key audiences in mind. First, there is a clear public audience who has a deep interest in the specific stories of the enslaved community owned by the Maryland Province Jesuits: the descendants of that enslaved community. As the process moves forward to identify and connect with the descendants, I want this material to be clearly accessible to them so they have, as much as possible, an understanding of their ancestors time in Maryland. The larger community of Georgetown University alumni and students form a related public audience for the work. Second, I view the project as making a major contribution to the larger effort of universities studying their history with slavery. In addition to the specific data and history of this community, the work offers a sample data model for describing and publishing data about enslaved individuals and their activities that any university could use with their own archival materials. Finally, given the depth of documentary evidence available about this community, I envision this work being useful to scholars of slavery in the Chesapeake and scholars of U.S. Catholicism.

Data Processing

I am in the process of creating a derived (meso-level) data set that will hopefully yield significant findings about the lives of this particular community of enslaved people. In reviewing the records, I have been in search of evidence of family status and formation, life cycle events such as birth, marriage, and death, shifts in freedom status and ownership, travel, health events, daily conditions, and labor and economic transactions. The individual farm and Georgetown College account ledgers have been particularly fruitful because they list individual day-to-day transactions about supplies, clothing, hiring, and healthcare in minute detail. They also occasionally include inventory lists of the people present at the various sites. The ledgers are necessarily uneven in their coverage and detail because they were created by many, many hands as the Jesuit personnel who managed the farms changed over time. Additionally, there a good number of contractual documents to support major transactions, such as sales and inheritances. The proceedings of the Corporation of Roman Catholic Clergyman include any resolutions approved by the directors, which include planned sales, dispute resolutions, and other kinds of major transactions. These proceedings are sometimes confirmed and expanded through individual correspondence among individual Jesuits. Finally, the archival collections contain extremely important sacramental records, which provide the bulk of the data for reconstructing family and kinship networks.

Having combed through these materials, I have extracted every instance of an event involving an enslaved person and I am in the process of building a linked open data repository that includes those events and the people involved in them. This network of communities includes enslaved people owned by the Jesuits, enslaved people owned by non-Jesuits, free people of color, and a cast of white people, Jesuit and non-Jesuit, who are party to these events (1730-1840). Together these individuals are participants in over 1,700 events, including life cycle events, religious events, material provisions, health incidents, travel, labor and economic transactions, and inheritance, sales, or manumission transactions.

The assembly of this data set has involved the hand processing of information out of document transcriptions into rectangular data. For each individual enslaved person in the records, I created a row with a unique identifier. I then worked to establish kinship relationships. Finally, though many of these individuals have the same first name and no last name, I undertook a painstaking process of deduplicating and disambiguating the individuals by triangulating among pieces of documentary evidence that included key indicators about location, year of birth, and family connections. I am also in the process of working through a set of event types that represent each appearance of an enslaved person in the records. These types include: birth, baptism, marriage, death, inventory, health, sale, legal, labor, commerce, conditions, travel, punishment, run away. For each event, I have extracted key details of the event, the date, event participants, and a link to the digitized copy of the document itself when it is available.

Site Infrastructure

The assembly of this data set has involved the hand processing of information out of document transcriptions into rectangular data. For each individual enslaved person in the records, I created a row with a unique identifier. I then worked to establish kinship relationships. Finally, though many of these individuals have the same first name and no last name, I undertook a painstaking process of deduplicating and disambiguating the individuals by triangulating among pieces of documentary evidence that included key indicators about location, year of birth, and family connections.

The ultimate goal for all of that rectangular data was for it to be imported into Omeka S.

Omeka S offers the ability to use the URIs for other Omeka S Resources as descriptive values within metadata fields, in essence linking one Omeka S Resource to another (i.e. using a Person type Resource for Martha Washington as the value for the Creator field in description of a Text type Resource). Alternatively, a user could input a URI for an external resource (i.e. Martha Washington's DBPedia page). Omeka also makes it possible for users to attach media to Resources in three ways: through a simple file upload, through the use of an embed code from an outside resource, or use of a URI for an existing resource. Users creating many Items using the same LOD vocabulary properties can create a Resource Description Template to make the description process more efficient.

Thus, in preparation for that import, I created three resource templates that represented the data model for my content types (people, events, and locations). Resource template can be formed by selecting properties from any existing linked data schema. My templates combine properties from DCMI Terms and Type, FOAF, and from Bio, Relationship, and Schema, which I imported for this project.

Having created the templates, I was able to import the entire universe of people using the CSV Import plugin to map their details to the appropriate LOD property in the template. Then, I used their unique IDs and Omeka S IDs to build the relationship links networking them to family members, Jesuits, and external related individuals.

In addition to establishing the kinship networks, I am in the process of working through a set of event types that represent each appearance of an enslaved person in the records. These types include: birth, baptism, marriage, death, inventory, health, sale, legal, labor, commerce, conditions, travel, punishment, run away. For each event, I have extracted key details of the event, the date, event participants, and a link to the digitized copy of the document itself when it is available. Again, I have formed this information as rectangular data for CSV Import structured through the Event Resource Template.

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