{"accessLevel": "public", "bureauCode": ["020:00"], "contactPoint": {"fn": "Terranna Haxton", "hasEmail": "mailto:haxton.terra@epa.gov"}, "description": "The dataset was created from simulating contamination incidents in a water distribution system and selecting optimal sampling locations to identify the contamination incident. This data includes the number of contamination scenarios still credible after each sampling cycle; the number of nodes correctly identified as being contaminated after each sampling cycle; and the number of nodes identify as likely contaminated, likely not contaminated, and uncertain after each sampling cycle. \n\nThis dataset is associated with the following publication:\nRodriguez, S., M. Bynum, C. Laird, D. Hart, K. Klise, J. Burkhardt, and T. Haxton. Optimal sampling locations to reduce uncertainty in contamination extent in water distribution systems.   Journal of Infrastructure Systems. American Society of Civil Engineers  (ASCE), Reston, VA, USA, 27(3): 1-31, (2021).", "distribution": [{"downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1502586/Opt_Sampling_Paper_Figure_Data.xlsx", "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet", "title": "Opt_Sampling_Paper_Figure_Data.xlsx"}], "identifier": "https://doi.org/10.23719/1502586", "keyword": ["Drinking water distribution system", "Source identification", "drinking water distribution system modeling", "grab samples", "model uncertainty", "modeling and optimization"], "license": "https://pasteur.epa.gov/license/sciencehub-license.html", "modified": "2018-08-24", "programCode": ["020:060"], "publisher": {"name": "U.S. EPA Office of Research and Development (ORD)", "subOrganizationOf": {"name": "U.S. Environmental Protection Agency", "subOrganizationOf": {"name": "U.S. Government"}}}, "references": ["https://doi.org/10.1061/(asce)is.1943-555x.0000628"], "rights": null, "title": "Optimal sampling locations contamination extent WDS figure dataset 08242018"}