Replication Data for: Visual Attention and Harmony Assessment in Horse–Rider Combinations

<p>This repository contains the datasets used in a study investigating how participants visually assess harmony in horse–rider combinations using eye-tracking and verbal evaluation.<br>
Participants viewed five video stimuli across equestrian disciplines and rated harmony on a 0–10 scale while their eye movements were recorded.<br>
The dataset integrates:<br>
<ul>eye-tracking metrics</ul>
<ul>harmony scores</ul>
<ul>participant characteristics</ul>
<ul>qualitative theme coding</ul></p>

<p>Dataset structure<br>
1. harmony_clean_long_dataset.csv<br>
Long-format dataset at the level of participant × video × AOI.<br>
Includes:
<ul>Participant ID (anonymised)</ul>
<ul>Video_label (discipline)</ul>
<ul>AOI_label (11 anatomical regions)</ul>
<ul>Fixation metrics:<br>
NOF (number of fixations)<br>
DOF (duration of fixation)<br>
TFF (total fixation time)<br>
OOF (order of fixation)</ul>
<ul>HarmonyScore (0–10 rating)</ul>
<ul>Participant characteristics (Category, Level)</ul>
<ul>Qualitative coding variables (horse, rider, connection themes)</ul><br>
This dataset contains 1,650 observations (30 participants × 5 videos × 11 AOIs).</p>

<p>2. harmony_fixation_analysis_dataset.csv<br>
Aggregated dataset at the level of participant × video.<br>
Includes:
<ul>Fixation proportions per AOI</ul>
<ul>Principal Component Analysis (PCA) scores:<br>
FRC1–FRC5 (fixation-based gaze strategies)</ul>
<ul>HarmonyScore</ul>
<ul>Video_label and Level_label </ul>
<ul>Qualitative theme proportions (Horse, Rider, Connection)</ul></p>

<p>3. harmony_duration_analysis_dataset.csv<br>
Same structure as fixation dataset, but based on fixation duration.<br>
Includes:
<ul>Duration proportions per AOI</ul>
<ul>PCA scores:<br>
DRC1–DRC5 (duration-based gaze strategies)</ul></p>

<p>Data processing<br>
Eye-tracking data were processed in Python. Fixation counts and durations were converted into proportional measures per participant and video to control for variation in recording length.<br>
Principal Component Analysis (PCA) with Varimax rotation was applied to identify broader gaze strategies, using standardized AOI variables and an eigenvalue > 1 criterion.</p>

<p>Ethical considerations<br>
All data were anonymised prior to analysis. No personally identifiable information is included.</p>