The Data-Expectation Gap: A Vocabulary Describing Experiential Qualities of Data Inaccuracies in Smartwatches

Fuente: arXiv
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Main Authors: Dritsa, Dimitra, Houben, Steven
Format: Preprint
Published: 2025
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author Dritsa, Dimitra
Houben, Steven
author_facet Dritsa, Dimitra
Houben, Steven
contents Many users of wrist-worn wearable fitness trackers encounter the data-expectation gap - mismatches between data and expectations. While we know such discrepancies exist, we are no closer to designing technologies that can address their negative effects. This is largely because encounters with mismatches are typically treated unidimensionally, while they may differ in context and implications. This treatment does not allow the design of human-data interaction (HDI) mechanisms accounting for temporal, social, emotional, and other factors potentially influencing the perception of mismatches. To address this problem, we present a vocabulary that describes the breadth and context-bound character of encounters with the data-expectation gap, drawing from findings from two studies. Our work contributes to Personal Informatics research providing knowledge on how encounters with the data-expectation gap are embedded in people's daily lives, and a vocabulary encapsulating this knowledge, which can be used when designing HDI experiences in wearable fitness trackers.
format Preprint
id arxiv_https___arxiv_org_abs_2501_11556
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle The Data-Expectation Gap: A Vocabulary Describing Experiential Qualities of Data Inaccuracies in Smartwatches
Dritsa, Dimitra
Houben, Steven
Human-Computer Interaction
Many users of wrist-worn wearable fitness trackers encounter the data-expectation gap - mismatches between data and expectations. While we know such discrepancies exist, we are no closer to designing technologies that can address their negative effects. This is largely because encounters with mismatches are typically treated unidimensionally, while they may differ in context and implications. This treatment does not allow the design of human-data interaction (HDI) mechanisms accounting for temporal, social, emotional, and other factors potentially influencing the perception of mismatches. To address this problem, we present a vocabulary that describes the breadth and context-bound character of encounters with the data-expectation gap, drawing from findings from two studies. Our work contributes to Personal Informatics research providing knowledge on how encounters with the data-expectation gap are embedded in people's daily lives, and a vocabulary encapsulating this knowledge, which can be used when designing HDI experiences in wearable fitness trackers.
title The Data-Expectation Gap: A Vocabulary Describing Experiential Qualities of Data Inaccuracies in Smartwatches
topic Human-Computer Interaction
url https://arxiv.org/abs/2501.11556