Title Pending

In this paper, I reflect on the growing cross-disciplinary convergence around the use of bibliographic metadata as empirical material in digital/computational history and quantitative economic history. I outline the main challenges in preprocessing library catalog metadata, drawing on examples from both fields. A pilot case on the academic collection of the Old University of Louvain demonstrates key steps in data transformation and preparation, with the aim of aligning common routines and creating reusable resources across disciplines. I then examine how metadata can be applied in historical network analysis, discussing underlying premises, potential caveats, and key modeling decisions. Based on this examination, I propose a multilayer network representation as a structurally faithful base to represent bibliographic metadata. Finally, by drawing a comparison to practices in quantitative economic history, I show how adopting hypothesis-driven modeling and statistical inference can address skepticism toward digital approaches and thereby advance the computational development of digital history.