---
layout: publication

title: An interview method for engaging personal data

key: 2021_imwut_interview

type: paper

order: 2021-11

shortname: interview

image: 2021_imwut_interview.png

image_large: 2021_imwut_interview_teaser.png

authors:
	- moore
	- pgoffin
	- Jason Wiese
	- meyer

# A link to an internal blog post (use only the relative URL)
blog-post: 

# Include a shortened name for the journal or conference/proceedings
journal-short: IMWUT
year: 2021

# Create BibTeX info, using one of the entry choices
# Articles have a "journal", and inproceedings have a "booktitle"
# Preprints are articles with the location of preprint mentioned in "journal"
# You can remove fields you don't need, or else leave them blank
# Try to include a DOI, or use the publisher URL below
# Specify new BibTeX fields by adding a new key and value inside "bib:"
bibentry: article 
bib:
  journal: The Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT)
  booktitle: 
  editor: 
  publisher: ACM
  address: 
  doi: 10.1145/3494964
  url: 
  volume: 5
  number: 4
  pages: 1-28
  month: dec
  pmcid: 

# Add things like "Best Paper Award at InfoVis 2099, selected out of 4000 submissions"
award: 

# Provide a link to the publisher's webpage if no DOI is available
publisherURL: 

# Link to an official preprint server
preprint_server: 

# Links to a project hosted on VDL, or else externally on your own site
project: https://vdl.sci.utah.edu/EngagementInterviews/
external-project: 

# Video entries, a preview , talk, and intro video. Vimeo IDs or youtube IDs are supported
# you need to pick either a vimeo or youtube ID. We definitely want a downloadable video too.

# Provide a preprint and supplement pdf
pdf: 2021_imwut_interview.pdf


# Extra supplements, such as talk slides, data sets, etc.

# Supplemental, cc-by images. Make caption brief (at most 60 chars).

# Link to the repository where the code is hosted
code: 
abstract: "<p>
Whether investigating research questions or designing systems, many researchers and designers need to engage users with their personal data. However, it is difficult to successfully design user-facing tools for interacting with personal data without first understanding what users want to do with their data. Techniques for raw data exploration, sketching, or physicalization can avoid the perils of tool development, but prevent direct analytical access to users' rich personal data. We present a new method that directly tackles this challenge: the data engagement interview. This interview method incorporates an analyst to provide real-time personal data analysis, granting interview participants the opportunity to directly engage with their data, and interviewers to observe and ask questions throughout this engagement. We describe the method's development through a case study with asthmatic participants, share insights and guidance from our experience, and report a broad set of insights from these interviews.
</p>"

# After the ---, you can put information that you want to appear on the website using markdown formatting or HTML. A good example are acknowledgements, extra references, an erratum, etc.
# The --- is REQUIRED! 
---

# Acknowledgements

The authors thank Greg Furlich for his indispensable data analysis skills, our study participants for sticking with us throughout this longitudinal study, and our anonymous reviewers for their thorough and supportive comments. This research was supported by the National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health under award number U54EB021973; the National Science Foundation under award number 1936071; and by the Wallenberg AI, Autonomous Systems and Software Program (WASP) and the Knut and Alice Wallenberg Foundation. The content is solely the responsibility of the authors and does not necessarily represent the official views of these funding agencies.