From Data to the Creation of Meaning Part 1: Unit of Analysis as Epistemological Problem

IASSIST Quarterly 2013 7 Abstract Aligning data and research infrastructure is, as our daily work often reminds us, a difficult process. While data professionals often focus on research lifecycles, incentives, storage and transmission technologies, metadata and data sharing we tend to overlook the epistemological incongruences of diverse research and data practices. All data creation processes, even if unknowingly, make assumptions about the world and what exists as a unique unit that can be analyzed. In attempting to make data meaningful to different audiences, especially across disciplines, we must pay attention to these epistemological assumptions. Failure to do so will inevitably frustrate our attempts to develop meaningful infrastructure for research data and even potentially undermine effective research through misunderstandings of data. Looking at census and zip code data as examples, this paper explores the issue of unit of analysis as an example of such disciplinary epistemological assumptions. The complexities that arise even in these simple examples suggest the importance of addressing the theoretical complexities of dealing with data collections, management and interpretation.