The Digital Pasts Lab (DigPasts-Lab) is geared towards performing innovative, quality research in digital humanities, with an emphasis on historical research. We aim to create an interdisciplinary workspace among different humanities researchers and between humanities researchers and data scientists, which develops and enriches both worlds.
Although data science is a new field, in the humanities, working with data is anything but a new phenomenon. Scholars have been studying and analyzing their data - texts, paintings, artifacts - for hundreds of years, in “analog” methods, which have produced ripe and extensive research into human thought and history. But now, humanities researchers are gradually moving from the dusty libraries and stacked books, to the dusty desktops and stacked hard-drives.
This move is not only the result of modern conveniences, but the result of opportunity. New technologies, such as natural language processing (NLP), optical character recognition (OCR), computer vision applications, and other machine learning (ML) models, offer innovative research avenues. They provide new methods for scholars to analyze their data from different perspectives. Feedback from humanities researchers is also imperative for improving and developing further these new technologies, giving them practical applications and advancing their capabilities, particularly by using human-in-the-loop and human-machine interfaces.
Furthermore, digitization offers not only a better preservation method, but also the opportunity for a wider audience to access the data, scholars and laypeople alike. Information and knowledge are no longer the sole propriety of the academic few. It is fast becoming widely accessible, granting new pedagogic and interdisciplinary cooperation opportunities that enrich our cultural knowledge.
We can summarize our vision in the following four main goals:
For more information on our projects, each of which touches on at least one or more of these goals, see the Projects page. For existing tools for assyriologists, see the Babylonian Engine (version 1.0) demo or the beta version.
Scholars, companies, or other parties interested in cooperating with the lab may contact us through the lab email: firstname.lastname@example.org.