Rabea Kleymann: Data Diffraction: A Counternarrative to Integration for Digital Humanities Research
Lecture in context of the conference Digital Humanities: Responding to Asian Diversity of the Alliance of Digital Humanities Organizations, 25–29 Jul 2022
Mixed methods are firmly established in Digital Humanities (DH) scholarship. While this approach is understood as a research design adopted from social sciences, mixed methods seem to be an umbrella term for defining DH’s methodological framework in general. The use of computational procedures in DH is often regarded as a combination of quantitative and qualitative methods. So far integration within mixed methods research is often discussed in a realm of technical challenges concerning data settings, standards and ontologies. Although data integration addresses epistemological and social issues of conformity and interoperability of research data for a global DH community.
The presentation argues that integration provides one device to explore questions of difference and diversification within DH scholarship. Therefore, promises, constraints and pitfalls of the “integration”-narrative, which seems to be deeply enfolded in mixed methods research, are described. The focus of attention will be on compatibilities as well as forms of inferences, which gain relevance manufacturing of knowledge within mixed methods research. Discussing mixed methods approaches in computational stylistics and ontologies, this presentation introduces data diffraction—a counternarrative presented by Uprichard and Dawney—as one complementary aim for dealing with different data settings
The literary scholar Rabea Kleymann is research associate with the project Diffractive Epistemics: Cultures of Knowledge in the Digital Humanities.