Making sense of data interrelations in qualitative longitudinal and multi-perspective analysis

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