We chose the name Open Data Index for Schools (ODIS) because it provides freely accessible, open-data on the challenge or systemic strain that might be present within school communities. What makes ODIS unique compared to similar tools is that all data are aggregated around public school communities, or the geographic area around specific high schools throughout the country.
The higher the number, the greater the indication that members of the school community are adversely impacted by some challenge or barrier. For example, a school community with a high number on the ODIS domain of “Economics” indicates that the area is under greater economic strain than a school community exhibiting a low number on the same domain.
Note: ODIS metrics should not be interpreted as percentages. The original data metrics are transformed and weighted to be on a scale of 1-100 and should not be interpreted as a straight percentage.
The intent behind ODIS was to develop a tool that could drill down to the high school level nationally, making it as widely usable as possible. The ODIS provides information on over 23,000 high schools nationwide, as listed by the National Center for Educational Statistics (NCES).
We wanted ODIS to focus on individual high school communities so that community impact work could center around specific 9-12th grade institutions and their community needs. Similar to a "county" or "city" level in terms of geographic area, a school attendance boundary (SAB) defines the geographic area by which students are eligible to attend a designated school.
All schools identified by the National Center for Education Statistics (NCES) are public high schools; for the purpose of the ODIS tool this includes magnet schools, charter schools, and traditional public high schools.
No, for schools that have open enrollment without school attendance boundaries (and sometimes charter or magnet high schools), we are not able to provide school attendance boundary data at that level. However, our collaborators at the NYU Marron Institute of Urban Management describe in the technical documentation how calculations were done in the absence of a school attendance boundary.
Data are pulled from multiple sources and are fully documented in ODIS's technical documentation, but sources include the Bureau of Labor and Statics; U.S. Census Bureau; County Health Rankings; City Health Dashboard; and Vera Institute.
All data domains (Economic, Education, Health, Housing, and Crime) are weighted evenly when calculating the ODIS composite using the formula:
ODIS Composite = 1/5 (Economic Stress) + 1/5 (Education Stress) + 1/5 (Health Stress) + 1/5 (Housing Stress) + 1/5 (Crime Stress)
Data from the U.S. Census Bureau is valuable for the purposes of the ODIS tool because we wanted the tool to be able to drill down to individual census tracts and provide the user with information on multiple challenges and barriers in the area immediately surrounding public schools throughout the country. The ODIS is not conveying population-based statistics, but rather hyper-localized, tract-level characteristics of an area around a given school. Put differently, census tracts are small and homogeneous in their data makeup, and their data tend to accurately represent the characteristics of each individual tract.
Since ODIS does not aggregate a large number of tracts together to make assertions about population-based statistics, the systematic bias often accompanying census data is significantly reduced because we are interested in tract-level characteristics around high schools. However, we fully acknowledge that minorities are systematically undercounted in the American Community Survey data collected by the U.S. Census Bureau at a broader, population level.
We envision ODIS being used in multiple ways to help address complex problems facing our country. We built the tool with individuals responsible for resource allocation, education leaders, researchers, policy makers, and philanthropists in mind and with the understanding that information on multiple community challenges and barriers is needed to gauge success with regard to community impact. Below are a few quick use cases that our team was thinking about, as we developed this work:
a. Provide actionable insight for individual leaders to facilitate more holistic community service. b. Allow philanthropic users to align investment priorities with the intended spectrum area of need. c. Facilitate richer impact stories that are based in community data. d. Facilitate the identification of new areas where philanthropic groups and businesses may want to become involved. e. Facilitate the identification of work-based learning initiatives or other targeted programs addressing community need.
Since seven of the variables contributing to ODIS are collected at the county level, we wanted to include a county-level indicator of wealth inequality, which is the Gini Index. The Gini Index is important supplementary information because individual counties throughout the United States can have high levels of income inequality. Therefore, interpretation of ODIS data, which conveys challenges and barriers at the school community level, is enriched by consideration of income inequality at the county level. For example, consider an individual county with high income inequality, meaning the county contains some very affluent communities and some under-resourced communities. By having information on the income inequality on the county as a whole, this will help the user further contextualize the results of the individual school communities returned by ODIS.
All ODIS results can be downloaded and further analyzed offline. Just click the “Complete ODIS Dataset” button in the upper left-hand corner of the tool.
Yes! The ODIS tool was built to serve anyone seeking more information on challenges and barriers present in school communities in order to support mission-driven work. Share the tool any way you like or also send interested users to our ODIS informational page to learn more.
