As a leading laboratory in the Biocomplexity Institute of Virginia Tech, the Social and Decision Analytics Laboratory is modeling the social condition of metropolitan areas, integrating novel sources of data to examine health and wellness, and uncovering key factors that drive industrial innovation.
Social and decision analytics have the power to fundamentally change our understanding of the world around us. Our research informs effective policy-making under uncertainty, combining expertise in statistics and the social sciences to transform all data into actionable knowledge.
Leveraging analytics to solve real-world problems requires a broad range of expertise. The SDAL team includes thought leaders in a wide variety of fields: statistics, social, behavioral and economic sciences, political science, psychology, simulation, computer science, data analytics, information technology policy, and infrastructural resilience.
SDAL is driven to make data analytics an accessible and effective part of the policy-making process. SDAL’s newest partnerships and recent discoveries are regularly profiled on our news page, while public lectures are available in our presentations archive. Our location at the Virginia Tech Research Center in Arlington, Virginia allows us to partner with local, state, and federal governments, non-profit organizations, and industry throughout the D.C. metro area and beyond.
Every global challenge we face today is rooted in information. Advances in big data analysis have the potential to revolutionize the ways we address long-standing social problems such as unequal access to services and affordable housing.
To address these and other pressing issues, the Social and Decision Analytics Laboratory is pioneering three major domains of research.
The Science of “All" Data aims to integrate disparate sources of data—surveys and experiments; local, state, and federal administrative government records; social media; mobile technology, and geographic information—to deliver a comprehensive understanding of social problems. We are experts in drawing actionable information out of messy data sets of all sizes.
Information Diffusion Analytics charts how knowledge and social attitudes spread through information networks using a combination of network science, cognitive modeling, crowd-sourcing, and machine learning. Our research predicts how information reaches people and affects their outlook.
Community Learning Data-Driven Discovery (CLD3) allows organizations to identify individually maintained data resources that serve their mutual needs. Information that would have been siloed within a single department is “liberated,” freed for use throughout the community. Our research focuses on how to discovery, liberate, and repurpose these data flows to achieve data-informed policy development.
Our unique CLD3 approach is supported by expertise in five sub-domains of analytics research:
- Metropolitan Analytics applies data on infrastructure, environment, and people to understand how urban areas can support the well-being of their expanding populations. Our research guides the growth of resilient cities.
- Education and Labor Force Analytics seeks to provide a clearer picture of the factors that help students and employees thrive by understanding learning processes, social interactions, and learning environments. Our work examines the impact of education on labor force outcomes.
- Health and Well Being Analytics leverages public and private sector medical data to help communities deliver healthcare services where they are most needed. SDAL studies help healthcare resources do more good.
- Emergency Management Analytics creates deep characterizations of situational awareness at all levels through accessing and integrating comprehensive information of conditions that increase risks and stress to the emergency responders and the citizens they serve. Our research guides the development of equitable policies and practices to improve the safety and security of our communities.
- Industrial Innovation Analytics utilizes data from partners in the private sector to identify factors that reduce costs and improve efficiency. We enable the private sector to move beyond business analytics to develop information integration technologies.
Since its founding in 2013, SDAL has developed its world-class statistical and data science capabilities in support of the Biocomplexity Institute’s overarching mission to predict, explain, and visualize the behavior of massively interacting systems.
Backed by the Biocomplexity Institute’s diverse research programs and unique, high-performance computing infrastructure, SDAL has established long-term partnerships with a variety of organizations including Arlington County, Procter & Gamble, the Robert Wood Johnson Foundation, the United States Census Bureau, and the Department of Housing and Urban Development.
The Social and Decision Analytics Laboratory welcomes new collaboration opportunities. To inquire, please contact the institute's executive director, Cal Ribbens.