Investments in transportation infrastructure assets are among the largest investments made by governmental agencies. Besides requiring a large investment for design and construction, transportation infrastructure also requires a significant amount of resources and effort for performing maintenance and/or rehabilitation activities. Along with other considerations, data on asset conditions are used to make decisions regarding the timing of maintenance activities, the type of treatment, and the resources employed. Some parameters under assessment, however, are evaluated through visual — or manual — assessments performed by evaluators on the site due to a lack of reliable, inexpensive automated methods to collect the data. While manual assessments for surface distresses are widely used, they still have the stigma that the results are based on subjective judgments by the individual evaluators. This thesis describes the Data Quality Assessment & Improvement Framework that has been developed to measure, and to improve, the performance of multiple pavement evaluators. This framework is based on a Continuous Quality Improvement cyclic process, where the main components include: a) assessment of the consistency over time — performed using linear regression analysis, b) assessment of the agreement between evaluators — performed using inter-rater agreement analysis, and c) management practices performed to improve the results shown by the assessments. When the Data Quality Assessment & Improvement Framework is applied to actual pavement distress data collected manually by different evaluators, the results show that it is an effective method for quickly identifying and solving data collection issues. The benefit of this framework is that the analyses employed provide performance data during the data collection process, thus minimizing the risk of subjectivity. The Data Quality Assessment & Improvement Framework can be used as part of an asset management program, or in any engineering program where the data collected are subjected to the judgment of the individuals performing the evaluation.
Pavements--Evaluation--Data processing, Pavements--Evaluation--Quality control, Pavements--Maintenance and repair--Quality control.
Level of Degree
First Committee Member (Chair)
Second Committee Member
Third Committee Member
Cordova, Arturo Adrian. "A framework for assessing and improving quality of data from visual evaluation of asset conditions." (2010). https://digitalrepository.unm.edu/ce_etds/31