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Per-and polyfluoroalkyl substances (PFAS), a group of environmentally-persistent compounds, are environmentally ubiquitous and challenging to remediate. Several studies show that PFAS are detected in drinking water systems when sampling is conducted, making human exposure via drinking water an important health consideration. This research: 1) develops a mapping tool for prioritizing sampling locations; 2) establishes a method for making GIS data and meta (data) in the mapping tool accessible; 3) fosters decision making by integrating knowledge brokering and the alignment interest and influence matrix (AIIM). The tool developed is this research is a geospatial and statistical PFAS hot-spot screening model that assists decision makers in prioritizing and identifying drinking water systems that may be prone to PFAS contamination. There is a need for this type of model because current PFAS exposures are most often identified only when sampling occurs; however, it is too timely and expensive to sample everywhere immediately and there is a lack of tools to assist decision-makers with prioritizing where is a sample. This research also ensures accessibility for the geographic information system (GIS) data and (meta) data by developing a data deposition method that aligns with findable, accessible, interoperable, and reusable (FAIR) principles. Lastly, this research emphasizes the importance of stakeholder engagement to foster informed decisions when science is emerging and uncertain.