Talking datasets – Understanding data sensemaking behaviours

Highlights

• We use a mixed-methods study to examine data-centric sensemaking activities.

• We identify three distinct clusters of activity patterns and their related data attributes.

• We discuss user needs important when understanding and reusing data created by others.

• We propose design recommendations for tools supporting data sensemaking and reuse.

Abstract

The sharing and reuse of data are seen as critical to solving the most complex problems of today. Despite this potential, relatively little attention has been paid to a key step in data reuse: the behaviours involved in data-centric sensemaking. We aim to address this gap by presenting a mixed-methods study combining in-depth interviews, a think-aloud task and a screen recording analysis with 31 researchers from different disciplines as they summarised and interacted with both familiar and unfamiliar data. We use our findings to identify and detail common patterns of data-centric sensemaking across three clusters of activities that we present as a framework: inspecting data, engaging with content, and placing data within broader contexts. Additionally, we propose design recommendations for tools and documentation practices, which can be used to facilitate sensemaking and subsequent data reuse.