**Content Warning** This post contains subject matter that some may find sensitive or disturbing, be advised. If uncomfortable with this topic, you may support Death By Numbers in other posts. This blog post will be a bit different than a few of our previous posts. Now that we have discussed our project workflow, we are going to begin to discuss the content of the Bills themselves. One thing that we immediately noticed on beginning this project is that suicides are reported on the Bills in a variety of ways that lead to more questions than answers regarding the weekly suicide rate in London. The variety of reports had a lot to do with the religious and legal views on suicide in this era. When looking at suicide rates, Sleepless Souls by Michael MacDonald and Terence R. Murphy state in Table 7.1 Sex Ratio of Selected […]
Category: Workflows
How we get things done: the transcription workflow
Once items are added to DataScribe and the datasets are ready for transcription, the transcription workflow begins. The project owner can assign users one of two roles: reviewer or transcriber. Reviewers can edit all records and items, regardless of the item’s status. For Bills of Mortality, Reviewers include the staff members on the project and our Digital History Research Assistants. Transcribers can only edit records and items which are locked to them. The Bills of Mortality transcription team is made up of undergraduate and graduate students. The Bills of Mortality transcription process starts with a Reviewer assigning items to the transcribers. Each item in DataScribe begins as an unlocked and new item in a dataset. When the Reviewer opens the dataset, they use filters to find these unlocked items and then assign them to individual members of the transcription team. The batch action dropdown menu […]
From Archival Sources to Computational Analysis, Part Two
In our last post, we explained how we used Tropy to organize photographs of bound bills into items, concluding with the export of the item metadata using the Tropy CSV Export plugin. This post covers the other part of the process of going from digital images to items in a datascribe item set. If you look at the workflow image, we’ll be describing work that takes place in the “Image Processing and CSV Creation” and “Omeka S Item Creation” areas. At this point in the process we have a csv and a lot of digital files—possibly organized but maybe not. Each row in the csv file will become an item in our Omeka S installation. Before we can use the csv with the Omeka S CSV Import module, we need to do some further data cleanup. The first thing is to rename the columns in […]
From Archival Sources to Computational Analysis, Part One
Have you ever wondered how a complex project like Death by Numbers comes together? This post is the first in a series about the workflow that takes us from archival sources to transcriptions formatted for computational analysis. Let’s begin with digitization. Digitization of Original Documents There are many ways historic documents become digital objects, and the BoM project is built on documents from a variety of sources. Sometimes we are working with digital images created by commercial publishers from microform reproductions of originals, but in the case of a set of bills in the care of the Wellcome Collection, the project director handled the primary sources directly and took the digital photographs. These bills, which were originally collected by the Medical Society of London, have been bound into volumes. While binding undoubtedly helped preserve the bills, they were not designed to be read in this […]
7 Problems to Expect when You’re Transcribing Historical Data and How to Avoid Them
So you want to start transcribing data from historical documents? The task seems easy! However, there are quite a few issues that can pop up which can create problems for other parts of the project. Below are some of the expected errors our transcribers on Death By Numbers frequently run into and some tips on how to handle them. The job may sound intimidating with all the potential pitfalls, but we have suggested solutions from all the tips and tricks our team has picked up over the past few months. Problem Number 1: Forgetting about the Data Solution: Be Familiar with Your Data Before getting too far ahead of yourself, familiarize yourself with your transcription project. Our project already has several blog posts on the London Bills of Mortality to assist new transcribers like the Bills 101. If you don’t know what you’re transcribing, you […]