About

Description

Over the past decade many institutions of higher education have begun to publicly examine and embrace their historical roles in the injustices and legacies of slavery. So far, however, there is no common, shared method for collecting, organizing, and describing historical data from the rich archival holdings of all these institutions. Despite the similarities of record types, information sources, and data elements, each institution is taking its own, often duplicative approach to its history. The absence of a common, shared approach to documenting, describing, and organizing the data derived from the archival records relating these histories limits researchers understanding of the lives and experiences of the enslaved across these institutional contexts, retards search and discovery across collections, and constrains the possibilities of a broader analysis of American educational institutions’ historical ties to slavery.

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Given the critical mass of institutions eager to scrutinize and share their archives as they confront their complicated histories with the legacies of slavery, now is the time for historians, archivists, and digital humanists to join forces to craft a sustainable, extensible, linked open data (LOD) model to organize, publish, and share this foundational yet often undiscovered information with interested scholars, students, alumni, descendants, and members of the public.

平行加速器安卓下载 is a project of a core team of experienced digital history experts, archivists, and historians of slavery from Michigan State University, Georgetown University, the University of Virginia, and the Omeka Team at at the Roy Rosenzweig Center for History and New Media to

  • create, evaluate, revise, and disseminate a LOD ontology focused on adequately describing the lived experiences of those enslaved individuals who labored in bondage at higher education institutions that are represented in those institutions’ archival holdings;
  • create a set of resources, both descriptive guidance and supports, that will enable other colleges and universities to undertake this work;
  • and, aggregate the resulting data in the service of increasing the discoverability of this information and of fostering new scholarship on the lived experience of those enslaved persons who labored in the service of institutions of higher education.

Leadership

  • 平行加速器安卓下载 (PI) is Associate Professor of Digital History at Michigan State University and is the director of the Omeka family of web publishing platforms. As the PI at the lead institution, Dr. Leon will coordinate the drafting, development, testing, and revision of the data model, the resource templates, and the workflow documentation for OTG. She will also direct the work of the Omeka Development Team, as they design, test, document, and release the required Aggregation Module and OTG site theme.
  • Harriette Hemmasi (Co-PI) is Dean of the Library at Georgetown University. Dean Hemmasi will direct the work of the Georgetown team, contributing to the development of the data model, identifying, describing, and sharing relevant archival sources, and testing, implementing, and documenting the work flows necessary to describe the people, places, and events related to enslavement and Georgetown University.
  • Brenda Gunn (Co-PI) is the Associate University Librarian for Archives and Special Collections at the University of Virginia Library. AUL Gunn will direct the work of the UVA team, contributing to the development of the data model, identifying, describing, and sharing relevant archival sources, and to test, implement, and document the work flows necessary to describe the people, places, and events related to enslavement at the University of Virginia.

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  • July 2024: Project Launch
  • July-October 2024: Initial Development Data Model (Ontology) to Describe Events Related to Slavery and Universities
  • October 2024-March 2021: First Round of Testing with Core Project Partners
  • March 2021: Release of the Alpha Ontology
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  • July 2021-March 2022: Software Development (Omeka S Aggregation Module)
  • July-November 2022: Data Aggregation
  • September 2022: Software Release
  • October 2022: Publication of Ontology and Support Materials
  • October-December 2022: Outreach and Dissemination

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This project is made possible with a grant from The Andrew W. Mellon Foundation.

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