One Voice for Sewer Condition Assessment and Asset Management

Lewis, Phil; Shan, Yongwei; Khaleghian, Hossein

doi:10.1061/9780784479957.048

Cited by 3 publications

(1 citation statement)

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“…There are nearly 800,000 miles of public sewer pipelines, and many of them are at the end of their service life [1]. As a result, understanding the current condition of the sewer system is a critical step for infrastructure asset management strategies and improving national wastewater systems [2].…”

Section: Introductionmentioning

confidence: 99%

Developing a Data Quality Evaluation Framework for Sewer Inspection Data

Khaleghian¹,

Shan²

2023

Water

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The increasing amount of data and the growing use of them in the information era have raised questions about the quality of data and its impact on the decision-making process. Currently, the importance of high-quality data is widely recognized by researchers and decision-makers. Sewer inspection data have been collected for over three decades, but the reliability of the data was questionable. It was estimated that between 25% and 50% of sewer inspection data is not usable due to data quality problems. In order to address reliability problems, a data quality evaluation framework is developed. Data quality evaluation is a multi-dimensional concept that includes both subjective perceptions and objective measurements. Five data quality metrics were defined to assess different quality dimensions of the sewer inspection data, including Accuracy, Consistency, Completeness, Uniqueness, and Validity. These data quality metrics were calculated for the collected sewer inspection data, and it was found that consistency and uniqueness are the major problems based on the current practices with sewer pipeline inspection. This paper contributes to the overall body of knowledge by providing a robust data quality evaluation framework for sewer system data for the first time, which will result in quality data for sewer asset management.

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Section: Introductionmentioning

confidence: 99%