The UI for the portal is straightforward and easy to use and also doubles as a GIS. Through the advanced search function users can use either the criteria or filter tabs to narrow their searches to specific sites. For example when you narrow down the search to RMP facilities only you can quickly pinpoint all of these facilities on a map of an area to show how burdened an area may be with these types of facilities.
Creators of the Student Health Index recommend using the tool in combination with qualitative data collection and stakeholder/community engagement (e.g. working with school leaders, local community leaders, and healthcare providers).
A full guide to using the dashboard is available here.
Users must select the ranking variable for either the overall vulnerability index score or for one of the four sub themes: Socioeconomic Status, Household Composition & Disability, Minority Status & Language, or Housing Type & Transportation.
A dictionary of terms used in this data resource are available at the bottom of this webpage: https://www.atsdr.cdc.gov/placeandhealth/svi/documentation/SVI_documentation_2018.html.
These datasets all involve a strong spatial component. The presentation of such data could best be done via GIS Software, with their integration within a story map to demonstrate the importance of environmental stewardship to natural environments as well as the people who depend on such resources for their livelihoods. For example, EPI data can be incorporated with EM-DAT’s disaster data to better understand the relationship between a country’s EPI performance and the amount of technological disasters it observes. A country’s EPI score on Fish Stock Status can be compared with how much the nation’s GDP relies on fisheries to draw attention to discrepancies between stewardship and a country’s reliance on this resource. This process will require a user to be familiar with GIS Software and spatial plotting of data points (as the datasets themselves have not been integrated into ArcGIS), and using this software to integrate information together into meaningful maps.
Creating maps by different combinations of indicators or geographic aggregations could be tinkered with to produce provocative data visualizations. Ranking scores can be used to draw distinction between different census tracts. However, clear inequities are evident even without these adjustments, with the HPI index score clearly demonstrating noticeable differences across geographies.
