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Citizen science is a process by which volunteer members of the public, who commonly lack advanced training in science, engage in scientific activities (e.g., data collection) that might otherwise be beyond the reach of professional researchers or practitioners. The purpose of this paper is to discuss how citizen science projects coordinated by interdisciplinary teams of engineers and social scientists can potentially enhance infrastructure monitoring data and decision-support models for local communities. The paper provides an interdisciplinary definition of infrastructure data quality that extends beyond accuracy to include currency, timeliness, completeness, and equitability. We argue that with this expanded definition of data quality, citizen science can be a viable method for enhancing the quality of infrastructure monitoring data, and ultimately the credibility of risk analysis and decision support models that use these data. The paper concludes with a set of questions to aid in producing high-quality infrastructure monitoring data by volunteer citizen scientists.

The amount of data being maintained by state departments of transportation (DOTs) and local transportation agencies is increasing steadily. Although data provide opportunities to facilitate decision making at transportation agencies, there are challenges involved in managing large and diverse data. This article provides an assessment of the maturity of three data management practice (stewardship, storage and warehousing, and integration) for 16 transportation data groups based on a survey of 43 DOTs in the United States. The assessment results show that data management practices at the monitoring and operations phases of transportation infrastructure life cycle are likely more mature than those at other phases. Inventory data, in particular, has the most mature data management practices. On the other end, real estate data and travel modeling data have the least mature data management practices. A comparison of the practices indicates that data stewardship is more mature than data integration and storage and warehousing practices.