Table of Contents
- Religious Ecologies: A large-scale project using early twentieth-century religious census data to create open datasets and visualizations.
- Death by Numbers: A project transcribing the London Bills of Mortality (16th-18th centuries).
- Plague in Iquique, 1903: This case study examines how to transcribe non-tabular or semi-structured data using DataScribe.
- Peste Bubónica en Iquique, 1903: Este caso de estudio examina el proceso de transcripción de datos no tabulares o semi estructurados usando DataScribe.
- 1950 United States Census: This case study explores the process of creating projects and datasets to transcribe returns from the 1950 United States census.
Suggested citation style: Author names, “Title of Case Study,” DataScribe.tech, 2022, < full uri >.
Written by Greta Swain
In the following case study we describe how the American Religious Ecologies project at the Roy Rosenzweig Center for History and New Media utilized DataScribe to transcribe tabular data from early twentieth-century digitized census forms in order to create a new dataset for American religious history. Because DataScribe was still under development when our team started transcription, we first used a basic spreadsheet structure for transcription and transitioned to DataScribe mid-way through the project. In this study, we will provide an overview of the American Religious Ecologies project and the sources we used. We will also detail the process of digitizing and readying our sources for transcription, the transition from using spreadsheets to using DataScribe for transcription, the workflows we developed for transcribing and reviewing, DataScribe as a project management tool, the final format of the data coming out of DataScribe, and the questions and visualizations this new dataset enabled. Finally, we discuss the decisions we made along the way. In total, this study will give you a better sense of how DataScribe was used by a diverse team at a University-based research center, and how it became a critical part of our efforts to transcribe thousands of sources, create new datasets and asynchronously manage a large-scale transcription project.
Death by Numbers
Written by Hernán Adasme, Daniel Howlett, and Emily Meyers
Death By Numbers is a project to transcribe and analyze the London Bills of Mortality, a weekly and annual series of mortality statistics produced from 1603 to 1752. With almost 8,000 bills from the weekly series alone, there is quite a bit of data to sift through and transform into a manageable format for computational analysis. In this case study we will explain how Datascribe was an instrumental part of this process of transcription and transformation.
Plague in Iquique, 1903
Written by Hernán Adasme
This case study examines how to transcribe non-tabular or semi-structured data using DataScribe. The analysis starts with an historical overview of the project Plague in Iquique, 1903, followed by description of the sources used. Then, the case study details the process of organizing and translating the sources into separate Omeka items that can be used to create a DataScribe project Ein the DataScribe module. Next, the case study walks the reader through the process creating a transcription form that captures information that suits the historical questions posed over the sources. Finally, the case study delves into how the data is being recorded in DataScribe, and some possible research paths that a DataScribe dataset allows historians to pursue.
Peste Bubónica en Iquique, 1903
Escrito por Hernán Adasme
Este caso de estudio examina el proceso de transcripción de datos no tabulares o semi estructurados usando DataScribe. El análisis comienza con una descripción general del proyecto Peste Bubónica en Iquique 1903, para luego llevar a cabo una caracterización de las fuentes utilizadas. A continuación, el estudio detalla el proceso de organización de las fuentes en ítems de Omeka S para ser usados para crear un proyecto DataScribe en el módulo DataScribe. Posteriormente, el estudio guía el proceso de creación de un formulario de transcripción destinado a capturar información de interés, a propósito de las preguntas históricas planteadas sobre las fuentes. Finalmente, el estudio profundiza en cómo crear los registros en DataScribe, y en algunos posibles caminos investigativos que DataScribe permite a los investigadores recorrer.
1950 United States Census
Written by Megan R. Brett
This case study explores the process of creating projects and datasets to transcribe returns from the 1950 United States census. The final structure of the DataScribe projects were determined only after a great deal of iteration and experimentation which are detailed in the study. The study includes recommendations and resources for using DataScribe and 1950 United States census returns as a learning tool.