ABSTRACT
Humanities data are characterized by the complex and messy links between people, places, events, creative works, and artifacts, overlaid by the biases and arbitrary filtration of contemporary observation, recording, and preservation. There has been a slow growth of data management tools for specific use cases, such as Omeka, FAIMS, and Zotero, but these do not solve research data management needs. Thus, it remains common for research projects and academic units to develop their own bespoke data management and publication tools. In this chapter, we introduce the methodology of “databasing as research.” In databasing as research, the scholar is free to adjust their data model interactively and reshape their database as research progresses. A layer of abstraction divides the researcher from the relational database, allowing them to focus on high-level relationships between entities, while the generation of database tables, foreign keys, and validation routines is left to the system. We then describe Heurist, a research data management tool, which enacts the principles of databasing as research, and we present a number of case studies of its use.
