Towards Data-Informed Communities

Behavioral data, which informs us of the quantitative ‘what’s’ and ‘how’s’ of a concern, lack the support of the ‘why’s’ that can help better understand the context. More so, when different data sets are held together to better understand their combined effect, these very same ‘whys’ are currently only understood as trends (Kim et al, 2018). In the field of HCI and personal informatics (PI), behavioral data plays a role in levels of self-reflection that is still centered around the individual. More quantitative data than qualitative data is generated and critical reflection (which is characterized by linking individuals to a global community) is lacking (Cho et al, 2022). Introducing communities (or a group of people with shared concerns) can be a means of generating qualitative data while generating reflection amongst its members.

The focus of this project will be to understand what role behavioral data can play in shaping communities. Different data sets will be used in the context of women’s health and their interaction and effect on a relevant community will be observed. The results will be an improved understanding of the role behavioral data can play in such a community to generate insights into the context and aid in group reflection processes.