Efficient Editing

Digital Critical Editions are onerous. The labor of transcription, translation, and annotation that a highly qualified workforce must carry out represents thousands of hours of work and requires substantial funding, in addition to long-term institutional support.

In a sense, that high-visibility projects in the Digital Humanities can obtain the vast amounts of funding necessary to run is a blessing.

Yet heavy reliance on the largesse of wealthy foundations, universities, and government agencies, the prolonged need for important human resources, does not constitute a viable economic model for the future. If more and more scholars can afford to produce ambitious digital editions of primary source documents, this practice remains the privilege of a few wealthy countries, reinforcing thus their cultural hegemony.

To make historical documents from all over the world accessible to a broader public, the cost of Digital Critical Editions should decrease by orders of magnitude.

In this series of blog posts, I evaluate the different approaches and technological bricks that scholars from all over the world can use to publish primary source documents more rapidly and at minimal expenses.

I will evaluate, in particular, technologies such as machine learning, blockchain, and decentralized storage.