  Data preprocessing is a crucial stage in the data analysis pipeline, with
both technical and social aspects to consider. Yet, the attention it receives
is often lacking in research practice and dissemination. We present the
Smallset Timeline, a visualisation to help reflect on and communicate data
preprocessing decisions. A "Smallset" is a small selection of rows from the
original dataset containing instances of dataset alterations. The Timeline is
comprised of Smallset snapshots representing different points in the
preprocessing stage and captions to describe the alterations visualised at each
point. Edits, additions, and deletions to the dataset are highlighted with
colour. We develop the R software package, smallsets, that can create Smallset
Timelines from R and Python data preprocessing scripts. Constructing the figure
asks practitioners to reflect on and revise decisions as necessary, while
sharing it aims to make the process accessible to a diverse range of audiences.
We present two case studies to illustrate use of the Smallset Timeline for
visualising preprocessing decisions. Case studies include software defect data
and income survey benchmark data, in which preprocessing affects levels of data
loss and group fairness in prediction tasks, respectively. We envision Smallset
Timelines as a go-to data provenance tool, enabling better documentation and
communication of preprocessing tasks at large.
