Supplemental data for a research paper on water main failure prediction. The data was authored by Poudel, Alence and hosted on Harvard Dataverse. It was last updated on May 18, 2026.
Use Cases
- Training machine learning models for water main failure prediction based on hydraulic features.
- Testing model robustness under conditions of data incompleteness as described in the associated paper.
- Benchmarking predictive algorithms for infrastructure asset management.
Strengths
- Data is directly linked to a peer-reviewed research publication, providing context.
- Last update timestamp of 2026-05-18 is provided.
Limitations
- Description metadata is limited; actual data quality requires manual inspection after download.
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
Provenance
- Source
- Harvard Dataverse
- Freshness
- Last updated 2026-05-18 20:48:44; freshness should be verified.