Thomas Davidson

Spotify Warped

We conducted a crowd-sourced survey to understand the kinds of insights users wanted to learn about their music listening history. Through this lens we examined and contrasted the information desires of Casual Users and Self-Tracking users, as well as the impact of passively collected data and how these elements could change conceptual models of Personal Informatics. We explored barriers that exist for users accessing and engaging with their data and established an information space to describe the abstract insights users wanted to learn before outlining how well existing summaries satisfy these information needs. We highlighted distinct differences between casual users and those who commit significant time to tracking and establish how well existing frameworks can explain these users needs.
This work is currently under submission and is available on request.

The Impact of Data Facts on Confirmation Bias

I was the second author on a project led by Shiyao Li which examined how Data Facts (generated data summaries) attached to ambiguous visualisations can influence confirmation bias in viewers.
This work is currently under submission and is available on request.

Distributed Tracing Visualisation

I conducted a qualitative interview study with collaborators from industry which characterised the problem space of distributed tracing visualisation formally for the first time. Across two rounds of 1-on-1 interviews with 6 practitioners we used grounded theory coding to establish users, use cases, and identify shortcomings of existing distributed tracing tools. We derive guidelines for the development of future distributed tracing tools and expose several open research problems that have wide reaching implications for visualisation research and other domains. This work was published in TVCG and presented at IEEE VIS 2023 in Melbourne.

The State of Visualisation in Systems Research

When assessing the existing state of visualisation in distributed tracing it became clear that little to no work has been done which focuses on the human aspect of distributed tracing. I undertook a survey study which examined the presentation of user facing aspects in the more general field of systems research focussing on human-in-the-loop tools. The findings from this work suggested that despite the implemented tools often being a fundamental contribution of the work, they were frequently under presented, designed, and explained. This work was published at the Symposium on Cloud Computing in 2022 and presented in San Francisco.

TraVista

I helped to develop and design the visualisations used in a piece of work that investigated augmenting individual trace visualisations with aggregate data for performance debugging.

Artistic Music Listening History

This project represents a creative explorative visualisation of my own personal music listening history. Implemented using d3 I present visual representations of my listening history ranging from one day of data, to visualising all 12 years of my listening on Spotify. The visualisation design is intended to be abstract and leans on the metaphors of soundwaves (for the day visualisation) and a wending path through my discovery of new artists (for the year visualisation).

Digital Relationships

Digital Relationships is a data visualisation project that allows users to generate explorative and informative visualisations based on their own Facebook messaging data. The website lets you explore your messages over time and produce customisable infographics directly linked to your digital relationships with others. The work was selected and presented at the 2021 Science Gallery Youth Symposium.

An Exploratory Analysis Visualisation Tool for Classic English Literature

During my masters I worked on developing a tool which facilitated exploratory analysis of literature through visualisation and interaction techniques. The approaches I implemented built on previous approaches to abstract text visualisation and augmented them to enable users to gain insight into sentence structure, character and location references, as well as the age of language used throughout the text. I was supervised by Tim Regan from Microsoft Research and Alan Blackwell from the University of Cambridge.

Direct Solo Piano Sonography

As part of the L312 Digital Signal Processing with Computer Music course I implemented and presented my work on visualising piano performances in real time.

Using Machine Learning to Solve a Rubik's Cube

For my undergraduate dissertation I analysed the performance of a machine learning approach to solving a semi-scrambled rubik's cube when compared to human participants with varying levels of experience.

Email - Thomas.James.Davidson@emory.edu

Address

Office W302, Maths and Science Center
Emory University, 400 Dowman Drive
Atlanta, GA, USA
30322

Twitter - @td_viz