Computational Treatments to Recover Erased Heritage: A Legacy of Slavery Case Study (CT-LoS)
| Autor: | Rajesh Kumar Gnanasekaran, Phillip Nicholas, Richard Marciano, Lori A. Perine, Alexis Hill |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Contextualization
Graph database business.industry Computer science 05 social sciences Big data 050301 education Cultural system computer.software_genre Data science Visualization Metadata Data visualization Cultural diversity 0509 other social sciences 050904 information & library sciences business 0503 education computer |
| Zdroj: | IEEE BigData |
| Popis: | Graduate students at the University of Maryland’s College of Information Studies (UMD iSchool) collaborated in interdisciplinary teams on a case study to explore application of computational methodologies to datafied collections related to slavery in the Maryland State Archives (MSA). Two research questions were examined: (1) What are the opportunities and limitations for using computational methods and open source tools to characterize data encoded within records of enslavement and to discover new patterns and relationships in that data? (2) How does knowledge of social and cultural systems impact those opportunities and limitations? Computational methods and tools were most effectively used when socio-cultural contextualization and technology’s role as a mediator of representation were taken into account. Three additional technical research areas are identified to enhance recovery of heritage hidden in records of enslavement: visualization, graph databases, and ontologies and metadata. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|