DD-WARF Accessibility Dataset
Description
This dataset contains web accessibility evaluation results from 320 Latin American university websites based on WCAG guidelines using the WAVE assessment tool. The dataset includes accessibility error metrics, WCAG criteria distributions, clustering profiles, and network-based similarity analyses to support large-scale studies on digital inclusion and accessibility remediation in higher education.
Files
Steps to reproduce
1. Collect the official URLs of Latin American university websites included in the study sample. 2. Evaluate each website using the WAVE Web Accessibility Evaluation Tool based on WCAG accessibility guidelines. 3. Extract accessibility error metrics, including WCAG success criteria violations such as: 1.4.3 Contrast 1.1.1 Non-text Content 2.4.4 Link Purpose 2.3.1 Info and Relationships 2.4.6 Headings and Labels 3.3.2 Labels or Instructions 4. Build a structured dataset containing: University identifier Country Ranking position Total accessibility errors WCAG criteria error frequencies 5. Perform statistical analyses using: Spearman’s Rank Correlation One-Way ANOVA Descriptive statistics 6. Apply DBSCAN clustering to identify accessibility outliers and institutional accessibility profiles. 7. Compute cosine similarity between institutions using WCAG error vectors. 8. Construct similarity networks and perform community detection using the Louvain algorithm. 9. Classify institutions into DD-WARF remediation archetypes using Euclidean distance-based profile assignment. 10. Calculate the Weighted Migration Effort Index (WMEI) to estimate remediation complexity. 11. Conduct sensitivity analysis to estimate the regional impact of targeted accessibility remediation strategies. 12. Generate visualizations including: Scatter plots Box plots Heat maps Radar charts Similarity networks Accessibility profile distributions.