Functional Anomaly Monitoring in Cyclical Water Treatment

This dataset supports the replication of results for a study on monitoring functional anomalies in cyclical water treatment processes. It contains data and code authored by Hunter J. Privett and collaborators from the Mo(Wa)²TER Datasets organization. The dataset was last updated in February 2026.

Use Cases

• Reproduce anomaly detection results from the associated study using the provided data and code.
• Analyze cyclical process data to identify functional anomalies in water treatment operations.
• Validate statistical monitoring methods for cyclical industrial processes as described in the source publication.

Strengths

• Dataset is associated with a peer-reviewed publication, providing methodological context.
• Includes both data and code, facilitating full reproducibility of the study's results.
• Last updated in February 2026, indicating recent maintenance.

Limitations

• Specific data structure, column names, and row counts are unknown, limiting immediate analytical utility.
• The scope and completeness of the data for independent modeling beyond replication are unclear.

Provenance

Source

Mo(Wa)²TER Datasets, authored by Hunter J. Privett.

Collection Method

Data and code compiled to reproduce the results of the associated research publication.

Freshness

Last updated 2026-02-18.