Representing the Self Through the Visualization of Personal Data

Introduction

Within this information environment, “numbers are infiltrating the last redoubts of the personal”, activities such as “sleep, exercise, sex, food, mood, location, alertness, productivity, even spiritual well-being” (Wolf, 2010) which can now be tracked by technological devices, capable of recording all kinds of data based on human experience (Lupton, 2020).

Drawing on these possibilities, the concept of data portrait (Xiong & Donath, 1999) emerges in the late 1990s as a means to graphically represent individuals in digital social environments and collaborative systems, based on data related to their interaction history (Dragulescu, 2009). These portraits can be defined as non-mimetic representations of people “made by visualizing data by and about them” (Donath, 2017, p. 187). Given that their purpose is to evoke and express the subject's identity, these visual representation systems are described as portraits, in order to differentiate them from other visualization systems whose main objective is the statistical analysis of personal data. As such, data portraits can be seen as representations of subjectivity, but are also visualizations of a subjective nature regarding design choices they involve on what is to be represented, how it is represented, and to what end or expression. Their primary goal is then “to call into question the claims of transparency, certainty, and objectivity” of data visualization techniques, drawing attention to “the situatedness of the observer and the phenomenon being observed” (Hall, 2011).

The project Data Self-Portrait (Sampaio et al., 2019) therefore involves the design and implementation of a visualization system capable of producing a self-portrait that is generated from personal data related to the subject's daily activities, according to an autoethnographic approach and as a reflection of one’s identity. This kind of self-portrait differs from traditional portraits since its visuality is not the result of a mimetic image record, but rather the product of the collection and representation of data resulting from personal experiences, therefore, functioning as a potential biographical repository.

The project explores different forms of visualizing the same dataset, as complementary expressions of the same self-portrait, which can be presented as an installation, comprising a dynamic visualization that can be interactively explored, a physical object and a printed publication. As the result of an ongoing investigation on data portraits, the project focuses on their ability to represent human experience, as it evolves in time, through one’s digital footprint. In this sense, it is also tied to a reconceptualization of portraiture in the current context of a data driven life (Wolf, 2010), or a daily life immersed in data.

From Portraits To Data Portraits

The portrait is an art form that aims to “index” identity using material objects (Borgatti, 2008). It symbolically represents the individual, not only through his physical characteristics, but also through fragments of his emotions, experiences, behaviors or even knowledge (West, 2004). To this end, portraits traditionally use images of one’s face as a signifier, due to its cognitive richness for conveying not only “who you are” but also our “emotional states” (Donath, 2001), but they also follow cultural conventions through the use of external elements such as objects, inscriptions, poses and spaces, capable of evoking the identity of the person portrayed.