Local Project Descriptions for Connecting People and Place

A one-page description of the cross-site IDS project can be found here.

Integrated data systems (IDS) contain data from various government agencies that are merged at the individual level. An IDS can be used by service providers to improve case management for individuals or by analysts to inform policymaking, targeting, and program evaluation. The types of data vary across systems, but might include records from social safety net programs, child welfare cases, juvenile justice records, public school systems, Medicaid claims, and homeless systems. An IDS enables a more holistic understanding of public programs, well beyond the perspective of an individual’s contact with only one agency.

With support from the Annie E. Casey Foundation, the National Neighborhood Indicators Partnership (NNIP) launched a cross-site project to advance the state of practice by linking IDS data to information about neighborhoods. Its overarching goal is to enhance local organizations’ access to information from IDS data so that they can be applied to problems at the neighborhood level. A lot of work in the IDS field examines how these systems can be used for policy research and for program improvement but little considers the neighborhood context in which the clients are living or the relationship of place to child or family outcomes. This project focuses on making this connection between IDS data and neighborhood indicators. It demonstrates to IDS administrators, funders, and agencies contributing data how working with local data intermediaries can result in new insights related to their own program interests.

Six NNIP partners were selected through a competitive process to participate in this project. Each partner proposed a program to inform local or neighborhood action and help foster the relationship between the NNIP partner and local or state IDS. The project began in June 2013 and concluded in April 2016. For more information, please visit the project's website.

Learn more about the partner projects below:



The Baltimore Neighborhood Indicators Alliance-Jacob France Institute (BNIA-JFI) at the University of Baltimore proposed a project to better understand the equity of access to programs that provide households with energy assistance to make weatherization improvements and reduce energy consumption. Studies have shown that households in homes that have been weatherized experience greater residential stability and increased financial security due to improvements in housing quality and decreases in energy expenditures. BNIA-JFI partnered with BNIA-JFI the Maryland Departments of Housing and Human Resources as well as various city and community-based partners in the planning and implementation phase of the project.

BNIA-JFI’s study examined households who applied for weatherization in the city of Baltimore in 2012.They showed that weatherization benefits were largely being extended to income-qualified residents living in middle-market neighborhoods. Homes in more distressed communities were in too poor condition to qualify weatherization benefits and their applications were denied at much higher rates. As a result of this project, the Baltimore Energy Initiative and staff from city agencies are determining how they can better direct resources to households who have been denied weatherization benefits


The Center on Urban Poverty and Community Development based at the Jack, Joseph and Morton Mandel School of Applied Social Sciences at Case Western Reserve University (CWRU), worked with the Ohio Longitudinal Data Archive at Ohio State University’s Ohio Education Research Center to understand how involvement in the foster care and juvenile justice systems affects high school graduation and early adult outcomes. Youth involved in these two systems are more likely to fail to graduate from high school on time or enter post-secondary educational programs, experience high unemployment rates, and experience homeless and future involvement with the criminal justice system. The study targeted a cohort of ninth graders in the Cleveland Metropolitan School District who had reached ages 18 to 21.

CWRU’s study identified characteristics of both at-risk youth, demonstrated the differences in educational attainment and future success between system-involved youth and youth who are not system-involved, and examined system involvement at the neighborhood level in order to develop suggestions for neighborhood-based policies to improve outcomes for the affected youth. Analysis revealed that youth involved in foster care and juvenile justice systems during high school are about two to four times more likely to access homeless services and send more days in jail. Results were shared with local agencies, the Jim Casey Youth Opportunities Initiative, and the YWCA’s “A Place 4 Me” program and marked the first time these groups had real metrics on what has happening to youth. Using the results, these groups are currently working to design more effective interventions for ninth graders. 

New York City

New York University’s Furman Center for Real Estate and Urban Policy worked with the New York City Center for Innovation through Data Intelligence to study the factors that best predict entry into New York City homeless shelters. While city governments face high costs for sheltering individuals and families, they also face indirect costs such as family instability, reduced educational attainment, disruption to the labor supply, and increased consumption of other social services. Providing effective interventions before a family loses their home could reduce these costs and help avoid shelter entry. To improve the targeting of interventions, the project identified specific individual, housing, and neighborhood situations, such as receipt of public assistance and other city services, housing code violations, property turnover, incidence of foreclosures, and neighborhood crime rates, individuals and families face before they enter the shelter system.

The study focused on families who entered New York City homeless shelters for at least one night between 2005 and 2013. Using machine learning techniques, researchers found that adding building and neighborhood characteristics increased the explanatory power of the prediction model. The results offer city or nonprofit homeless providers an opportunity to use such indicators to better target outreach services that might prevent homelessness. 

Pinellas County

In partnership with the Policy and Services Research and Data Center at the University of South Florida, the Juvenile Welfare Board of Pinellas County (JWB) researched the individual, home, family, school, and community-level factors that most impact chronic absenteeism in Pinellas County, Florida. In Pinellas, chronic absenteeism, defined as when a student misses 10 percent or more days of school per year, impacts an estimated 14,000 students in grades K through 12. Individual, family, and home factors, such as medical illness, behavioral health problems, poverty, parental abuse or neglect, and poor property conditions can interact with more environmental factors, such as a community’s physical conditions or an unsupportive school setting, to adversely affect a child’s ability to attend school. Compared to those who attend school regularly, children who frequently miss school have more difficulty with school performance and academic achievement.

JWB’s study followed a cohort of students in Pinellas County from elementary school through middle school.  The team’s results showed that both people and place influence chronic absenteeism and that attendance habits developed early in a child’s school career will have a long-term effect. As a result of the study, JWB, which also funds programs for children and families, are directing new resources towards the higher-risk neighborhoods they identified. Parent and child outreach efforts have also been affected as the results of the study encouraged JWB to focus outreach efforts early in a child’s school career.  


The University Center for Social and Urban Research at the University of Pittsburgh (UCSUR) worked with the Allegheny County Department of Human Services to study how neighborhood characteristics and human services involvement affects chronic absenteeism in three Allegheny County school districts. Chronic absenteeism is not only a strong predictor of lower educational achievement, but has also been linked to health, housing, and neighborhood condition issues such as asthma, poor property conditions, financial instability, and high crime rates. Understanding the factors that contribute to chronic absenteeism and determining which neighborhoods are most affected, allows for the development of more targeted strategies to improve school attendance and future educational outcomes.

The study targeted students who were enrolled in Pittsburgh Public Schools, the Clairton School District, and the Woodland Hills School District during the 2013-14 school year. Researchers found that certain neighborhood characteristics (e.g., high rates of violent crime and low median home prices) and property characteristics (e.g., age of a student’s home and tax delinquency) were linked to higher levels of chronic absenteeism. UCSUR also found that students who switched schools mid-year, possibly because of a move, were more likely to struggle with chronic absenteeism. As a result of the study, education stakeholders in Pittsburgh became more aware of the role stabilizing housing and improving housing conditions can play in reducing chronic absenteeism. While the school district is already working on policies to better aid students who switch schools mid-year, UCSUR is also working with community development corporations to further spread the idea that housing instability can affect a child’s  education. 


Data Spark, a Providence Plan initiative, studied civic engagement levels among youth in Rhode Island. The project examined trends in youth volunteerism by partnering with Serve Rhode Island, the state’s AmeriCorps administrator. There is a strong desire for community service agencies and youth development organizations to better understand how programs that encourage civic engagement and leadership development may influence the state’s leadership pipeline. DataSpark focused on understanding the demographic, socioeconomic, academic, and neighborhood characteristics of youth who participated in AmeriCorps as well as understanding how participation affects future levels of engagement, educational attainment, health, and workforce participation.

To learn more about AmeriCorps volunteers in Rhode Island, DataSpark’s study linked volunteer data to data on K-12 education, college attendance, employment, and voting habits. DataSpark found that many AmeriCorps volunteers came from low-income neighborhoods and served in the same communities. Additionally, more than half of these volunteers came from Rhode Island’s four urban core cities of Providence, Pawtucket, Central Falls, and Woonsocket. These findings will influence Serve Rhode Island’s future recruitment efforts and help them better target individuals from these neighborhoods. Serve Rhode Island also plans to use the results to improve their outreach efforts to the K-12 community.