Research has recently started to examine the temporal organization of work in the gig economy, as one manifestation of a broader and longer-term trend towards the destandardization of working time (Burchell et al., 2024). Existing studies have shown that algorithmic management tends to favour a fragmentation of working time that coexists with its extensification and an increase in the share of time that is unpaid (Mangan et al., 2023; Piasna, 2024; Pulignano et al., 2024). However, existing research has so far drawn mostly on classic qualitative methods, or survey data which provides very aggregate information on average number of hours work, without providing information on their distribution. The latter would allow to more accurately examine the fragmentation/extensification thesis. Our study makes an original contribution to the literature by providing a novel perspective into the destandardization of working time drawing on unique analysis of Uber driver's personal data generated and collected by the platform. Drawing on the participatory methodology “digipower” (Pidoux et al., 2022), workers accessed their personal via a Subject Access Request (SAR) mobilizing individual rights guaranteed by EU's General Data Protection Regulation. The data was collected in the context of worker mobilization around the process of reclassification Uber drivers' employment relation in the Geneva Canton that took place in 2022, with the support of the association PersonalData.IO. The paper examines the working patterns of 24 drivers working actively in the 4-year period from January 2019 to December 2022 who gave their consent for their data to be reused in this study. The data analysed provides rich information over an extended time period offering detailed insights on the temporal organization of work by Uber. The fine-grained portrait of worker's working time patterns over four years provides robust evidence supporting the claims that gig work favours an extensification and fragmentation of working time. We present new in-depth analyses that reveal individual variation within workers' trajectories across different time periods, suggesting that the destandarisation of manifests at the within-individual level. Across workers, the heterogeneity observed is likely reflecting the differential uses that different profiles of workers make of platforms. Besides producing statistical insights into Uber drivers' work organisation, this paper offers a further theoretical contribution about the fragmentation of working time in the gig economy from a sociology of work perspective. This approach deepens our understanding of such fragmentation by linking it to platform functionality.