Computational Treatments to
re-member
the Legacy of Slavery
(CT-LoS)
— “Reasserting Erased Memory” —

 

Measuring the Impact of Urban Renewal
Richard Marciano, Rosemary Grant, Alexis Hill, Phillip Nicholas, Noah Scheer, Alan Wierdak, Mark Conrad, Kari Fénelon, Arthur “Ray” McCoy, Priscilla Robinson, and Myeong Lee
June 18, 2022

Computational Archival Science (CAS) supports the Racial Reparations Commission work in Asheville, NC.

Exploring AI and ML to Analyze Chattel Slavery Advertisements in the State of Maryland between 1824 and 1864
Rajesh Kumar Gnanasekaran, Christopher Haley, and Richard Marciano
May 31, 2023

A partnership with the Maryland State Archives to computationally explore the nature of the trading of enslaved people. Paper accepted as a book chapter in Artificial Intelligence for Cultural Heritage Organisations.

Building a Digital Asset Management System to Preserve and Better Access the Current and Future Assets of the Mary McLeod Bethune Council House National Historic Site
Richard Marciano, Greg Jansen, Lyneise Williams, and Mark Conrad
March 31, 2022

Researchers partner with the National Park Service. The archival holdings of the site represent the institutional holdings of the National Council for Negro Women and their efforts to create a National Archive for Black Women’s History.

African American Soldiers: Visualizing Their Role During World War I
Alexis Hill and Richard Marciano,
January 28, 2023

Researchers develop an interactive visualization interface to highlight the role African American soldiers played during World War I through photographs.

A Data-Driven Approach to Reparative Description at the University of Chicago
Ashley Gosselar, as part of the 2022 DCIP Certificate with Mark Conrad and Richard Marciano
December 19, 2022

Researchers use computational methodologies and data analytics to automate reparative description of archival finding aids.

Testbed for the Redlining Archives of California’s Exclusionary Spaces (T-RACES)
Richard Marciano, David Goldberg, Rosemarie McKeon, and Chien-Yi Hou
May 14, 2022

T-RACES is a data visualization design that makes the history and effects of redlining in CA and NC newly tangible. Researchers map racial discrimination in housing using collections from the National Archives.

For a link to a national database of over 200 cities see: MappingInequality, co-created by UMD (Richard Marciano), U. Richmond (Robert K. Nelson), Virginia Tech (laDale Winling), and Johns Hopkins (N.D.B. Connolly).

Using Transfer Learning to Improve Text Extraction of Runaway Slave Ads
Aravind Inbasekaran, Rajesh Kumar Gnanasekaran, and Richard Marciano
January 14, 2022
Computational Archival Science (CAS) treats the Maryland State Archives Legacy of Slavery collections

An AI-Assisted Framework for Rapid Conversion of Descriptive Photo Metadata into Linked Data
Jennifer Proctor and Richad Marciano
January 14, 2022
A partnership with the Spelman College Archives Photograph Collection where a Computational Archival Science (CAS) framework is designed and tested to link people, places, and events depicted in historical African American photography collections.

Erasure and Representation in Archives at SAA 2020
Richard Marciano, Lyneise Williams, Marcia Reed, Mark Conrad, Elaine Westbrooks, Adriene Lim
Aug. 7, 2020 at the Annual SAA Meeting. A session advocating for culturally-responsible archival practices that address the significant erasures in visual, material, and historical representation which disproportionately affect communities of color.

Student-Led “Datathon”
Exploring data, investigating methodologies,
Oct 28-29, 2019, at the Maryland State Archives

Working in small interdisciplinary student teams from the University of Maryland iSchool Programs (Undergraduate InfoSciMLIS – Master of Library and Information Science, MIM – Master of Information Management, HCIM – Master of Science in Human-Computer Interaction, and Doctoral program), and from the Drexel LEADS Initiative (Library & Information Science Education and Data Science), the project explored selected datasets from the Maryland State Archives Legacy of Slavery Project under the leadership of domain experts. The “Datathon” was the culmination of 8 weeks of data exploration in the classroom in September and October, with 17 students (undergraduate, master’s, and doctoral).

Partners included the Maryland State Archives (MSA) in the US, together with King’s College London’s Department of Digital Humanities and The National Archives (TNA), in the UK. With Richard Marciano at the U. Maryland, they were awarded a one-year Arts and Humanities Research Council (AHRC) International Research Networking grant for UK-US Collaborations in Digital Scholarship in Cultural Institutions, running from 1 February 2019 to 31 January 2020.