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Potential of Citizen Science for Enhancing Infrastructure Monitoring Data and Decision‐Support Models for Local Communities
Author(s) -
Gharaibeh Nasir,
Oti Isaac,
Meyer Michelle,
Hendricks Marccus,
Zandt Shan
Publication year - 2021
Publication title -
risk analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.972
H-Index - 130
eISSN - 1539-6924
pISSN - 0272-4332
DOI - 10.1111/risa.13256
Subject(s) - citizen science , credibility , data quality , quality (philosophy) , data collection , process (computing) , data science , computer science , knowledge management , public relations , business , engineering , political science , sociology , social science , metric (unit) , philosophy , botany , epistemology , marketing , law , biology , operating system
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 article 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 article 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 article concludes with a set of questions to aid in producing high‐quality infrastructure monitoring data by volunteer citizen scientists.