Making sense of such “big data of the past” requires new approaches to data management, mining, visualization, and interpretation – an endeavour that poses multiple challenges to the disciplines of both history and data science.
This problem will be addressed with a new Doctoral Training Unit (DTU): “Deep Data Science of Digital History”, an interdisciplinary DTU unit between C2DH, FSTM, FHSE, LIST and LISER. The FNR recently granted 18 PhD positions and will allow the DTU to train students and engage with them in a critical study of historical data by bringing together intellectual and technical resources generated across disciplines, particularly from digital history, social sciences and data science.
To achieve this objective, the DTU will deepen the interdisciplinary collaboration between digital history and computer science by exploring the concepts of deep history and deep data science.
Based on the theoretical framework of “digital hermeneutics”, this DTU will tackle critical in historical data science.