Determinants of Data Quality Dimensions for Assessing Highway Infrastructure Data Using Semiotic Framework

The rapid accumulation of highway infrastructure data and their widespread reuse in decision-making poses data quality issues. To address the data quality issue, it is necessary to comprehend data quality, followed by approaches for enhancing data quality and decision-making based on data quality information. This research aimed to identify the critical data quality dimensions that affect the decision-making process of highway projects. Firstly, a state-of-the-art review of data quality frameworks applied in various fields was conducted to identify suitable frameworks for highway infrastructure data. Data quality dimensions of the semiotic framework were identified from the literature, and an interview was conducted with the highway infrastructure stakeholders to finalise the data quality dimension. Then, a questionnaire survey identified the critical data quality dimensions for decision-making. Along with the critical dimensions, their level of importance was also identified at each highway infrastructure project’s decision-making levels. The semiotic data quality framework provided a theoretical foundation for developing data quality dimensions to assess subjective data quality. Further research is required to find effective ways to assess current data quality satisfaction at the decision-making levels.

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.