Data Agents: Promoting Reflection through Meaningful Representations of Personal Data in Everyday Life


Visual and physical representations of historical personal data have been discussed as artifacts that can lead to self-reflection through meaning-making. However, it is yet unclear how those two concepts relate to each other. We focus on meaningfulness, a part of meaning-making that relates to feelings. In this paper, we present three projects where mundane objects, our data agents, are combined in meaningful ways with personal data with the aim to trigger reflection by placing a person's individual experience of data in relation to others'. To identify relationships between self-reflection and meaningfulness we use Fleck and Fitzpatrick's framework to describe the levels of reflection that we found in our projects and Mekler and Hornbæk's meaning framework to define the depth of reflection. We conclude with a discussion on four themes in which we outline how data agents informed the intersections between our central concepts. This paper constitutes a first step towards unpacking those relationships and invites for further explorations by the HCI community.

Maria Karyda
Aalto University, Helsinki, Finland
Elisa D. Mekler
Aalto University, Espoo, Finland
Andrés Lucero
Aalto University, Espoo, Finland




会議: CHI 2021

The ACM CHI Conference on Human Factors in Computing Systems (

セッション: UX and Interaction Design and Research: Techniques, Insights & Prototyping / Reflection, Behavior, Change & Learning

[C] Paper Room 13, 2021-05-14 09:00:00~2021-05-14 11:00:00 / [A] Paper Room 13, 2021-05-13 17:00:00~2021-05-13 19:00:00 / [B] Paper Room 13, 2021-05-14 01:00:00~2021-05-14 03:00:00
Paper Room 13
13 件の発表
2021-05-14 09:00:00
2021-05-14 11:00:00