Making Sense of Data Interrelations in Qualitative Longitudinal and Multi-Perspective Analysis

Abstract

In this article, we address data interrelations that social researchers face when working with qualitative data collected through in-depth interviews with longitudinal (QLR) and multi-perspective (MPR) research designs. Revisiting data from four different research projects and building on the proposal by VOGL, ZARTLER, SCHMIDT and RIEDER (2018), we present the 4C model of complexities within data interrelations. Specifically, the broader pool of data allowed us to cross-investigate how interview data may contradict, correct, complement, or be confluent with what the researcher has gathered from another interview conducted at a different point in time (longitudinally) or with another study participant (multi-perspective approach). Using different forms of transitions (e.g., transitions to adulthood, migratory transitions, transitions to parenthood) as a common analytical thread, we argue that revealing inherent inconsistencies in the data reflects the complex and ever-changing nature of reality and that making sense of these inconsistencies often enriches interpretations.

Keywords

• qualitative data analysis
• multi-perspective research (MPR)
• qualitative longitudinal research (QLR)
• aging transitions
• motherhood
• migration