  Designing future IoT ecosystems requires new approaches and perspectives to
understand everyday practices. While researchers recognize the importance of
understanding social aspects of everyday objects, limited studies have explored
the possibilities of combining data-driven patterns with human interpretations
to investigate emergent relationships among objects. This work presents Thing
Constellation Visualizer (thingCV), a novel interactive tool for visualizing
the social network of objects based on their co-occurrence as computed from a
large collection of photos. ThingCV enables perspective-changing design
explorations over the network of objects with scalable links. Two exploratory
workshops were conducted to investigate how designers navigate and make sense
of a network of objects through thingCV. The results of eight participants
showed that designers were actively engaged in identifying interesting objects
and their associated clusters of related objects. The designers projected
social qualities onto the identified objects and their communities.
Furthermore, the designers changed their perspectives to revisit familiar
contexts and to generate new insights through the exploration process. This
work contributes a novel approach to combining data-driven models with
designerly interpretations of thing constellation towards More-Than
Human-Centred Design of IoT ecosystems.
