Working with Arlington County's chief digital officer, students in SDAL's Data Science for the Public Good program have established a comprehensive set of criteria that can be used to develop and improve any open data portal.
In collaboration with Arlington County, our laboratory conducted a pilot study to identify messaging patterns that keep users engaged with their regional emergency alert systems, allowing officials to focus outreach efforts toward populations with the lowest levels of enrollment.
Among regional governments, funding for services such as public transportation often relies on accurate estimates of local employment.To capture a clearer picture of its working population, Arlington County commissioned our researchers to develop new methods for filling in the gaps left by federal employment data.
Using data from Arlington County's Operation Firesafe program, SDAL's data scientists have developed a model to predict which homes are least likely to contain a functioning smoke alarm—insights that can be used to target public safety initiatives toward the regions where they're most needed.
By integrating diverse data streams, our research team is able to provide policymakers with a detailed view of how emergency services resources can be deployed to maximize safety and efficiency.
Using 911 data from Arlington County Fire Department, SDAL's data scientists have identified factors that affect response time to structure fires—insights that can be used to improve the general safety of Arlington County residents and make the allocation of emergency resources more efficient.
Using data from the Washington Metropolitan Area Transit Authority, students in SDAL’s Data Science for the Public Good Program diagnosed some of the determinants that contribute to bus fare evasion, an issue that represents up to $20 million in lost revenue each year.
Our researchers are developing new methods to capture the diversity of local communities in precise geographical detail through the use of local real estate assessment data.
Working with the Department of Housing and Urban Development, our research team conducted a series of experiments to assess whether current reporting practices pose a significant risk to respondent confidentiality in the American Housing Survey.
Our researchers are testing the use of local property data to develop more robust, up-to-date measures of housing value by employing information sources outside of the traditional federal survey system.
School assignment policies can play a critical role in making our schools more diverse. Our researchers performed a close examination of district data to assess their unique strengths and limitations.
SDAL consulted with the Kentucky Center for Education and Workforce Statistics to identify trends among graduating high school students. The results reveal new insights about state policies used to promote college readiness.
A new framework encompassing the methods needed to capture, repurpose, and integrate external data sources will help the Federal Census Bureau meet the challenges of declining response rates and increasing costs.
Our educational program trains aspiring scholars how to sift through vast amounts of information related to public safety, employment, and the provision of services to discover how communities can become more efficient and sustainable.
SDAL researchers are developing new tools to model the dynamics of belief on a massive network scale—resources that could help policymakers predict how the spread of information through digital media will affect public health behaviors.
A collaborative effort between physicians, researchers, and government representatives is establishing a new set of guidelines to assist organizations in sharing health information responsibly and effectively.
By linking a population’s activity patterns to time- and location-specific air quality data, our research team is able to develop computational models which can be used to study differing rates of ozone exposure.