The following methods are used for the production and visualization of shareable, interactive feature layers containing ToxPi profiles using ArcGIS Pro. To learn more about ToxPi, see ToxPi Description below.
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For users looking to generate a predesigned layer file of ToxPi profiles with Python, or users who are unsure, see Method 1.
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For users looking to use an ArcGIS Toolbox(e.g., for integration into existing ArcGIS workflows), see Method 2.
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For users looking to see example walkthroughs, see the vignettes in Examples.
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For users looking to visualize existing maps, see Visualizations.
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For users requiring help with data manipulation and formatting requirements, see Utilities.
Definition
The ToxPi framework provides a method for transparently integrating and visualizing data across disparate information domains and is often used to determine risk values for the data being analyzed.
Description
Data that are not normally compared are combined into a data matrix comprising various data domains, or slice categories, with varying weights that represent the different data categories. Each slice category, represented by a color scheme, can then be separated into subdomains. The data matrix is then analyzed to produce a risk score ranging from 0 to 1 for each slice category, as well as a corresponding overall score that represents the record’s total risk from all categories. These scores are determined via a rank system for easy comparison between different data points and are displayed in a ToxPi profile for each record. If the data record's are locations, the figures can be mapped geographically. The calculation process, as well as ToxPi profile interpretation for Covid-19 data, are depicted below. For a more in depth look at the ToxPi framework, visit www.toxpi.org
Use the script ToxPi_creation.py to automatically produce predesigned feature layers containing interactive ToxPi profiles using the output of the ToxPi GUI as input. This is the suggested method, unless you are skilled with ArcGIS Pro and have a specific need for a Toolbox. An example walkthrough is shown in Vignette 1.
ToxPi_creation_customized.py can be used with county or census tract data for a more data rich map and acts as an example of how ToxPi_creation.py can be customized with further geoprocessing steps to create more advanced maps for specific data. An example walkthrough is shown in Vignette 3.
Steps:
1A. Load raw data into the ToxPi GUI
1B. Analyze data and output results file to a CSV, and make sure file meets data requirements
1C. Run python script from windows command prompt using the required parameters
1D. Open output layer file in ArcGIS Pro
1E. Share resulting map to ArcGIS Online
The ToxPiToolbox.tbx file is an ArcToolbox that contains a custom tool called ToxPi Construction for drawing the polygons that make up ToxPi profiles. It requires more manual steps than the script; however, a model can be created for the automation of map creation, and the toolbox allows for more customization than the script, including drawing a subset of slices for ToxPi profiles. This, along with a walkthrough example, are described under Vignette 2.
Steps:
2A. Load raw data into the ToxPi GUI
2B. Analyze data and output results file to a CSV, and split the coordinates into two separate columns
2C. Add results file to ArcGIS Pro
2D. Add ToxPiToolbox.tbx to ArcGIS Pro
2E. Run required analysis steps including the ToxPi tool and share resulting map to ArcGIS Online
We thank the PVI project team for data provision and the Baker Lab at NCSU for software testing. We also thank Dan Schmitt and Logan Wenzel for their expertise in implementation. This research was supported by the National Institutes of Health (NIH) grant awards ES030007 and ES025128, and by intramural funds from the National Institute of Environmental Health Sciences and the National Institute for Allergy and Infectious Diseases. Portions of the code for drawing slices were adapted from the Coxcomb tool for ArcGIS Pro.
Fleming J, Marvel SW, Supak S, Motsinger-Reif AA, Reif DM. ToxPi*GIS Toolkit: creating, viewing, and sharing integrative visualizations for geospatial data using ArcGIS. J Expo Sci Environ Epidemiol. 2022 Apr 26. doi: 10.1038/s41370-022-00433-w. PMID: 35474345.
Open-access link to full-text article: https://www.nature.com/articles/s41370-022-00433-w