Funding to develop a creative concept for a new big data traveling science exhibition was recently awarded to the University of Chicago. As a result, NIDA Center of Excellence Education & Outreach Director, Dr. Barry Aprison, will use the a supplemental NIH grant to the P50 Center project (PI: Dr. Abraham Palmer), “Integrated GWAS of Complex Behavioral and Gene Expression Traits in Outbred Rats,” to form a working group to develop design plans and raise money to support the development, fabrication, and implementation of a museum exhibition. Interactive displays will include real model organisms (behavioral mutant flies and nematode worms) and scientific equipment analyzing genomes real-time. These authentic encounters will engage high school and college students, and the general public with hands-on learning experiences about genes, gene networks, neural circuit systems, environmental factors, and physiological traits that contribute to brain function. The goal is to foster direct involvement with real things and real processes. Science content will include experiments, tools, and technologies used to produce and analyze multiple streams of data about living things and their behavior. Informal learning experiences will demonstrate how large data sets are translated into understandable forms, such as biological circuits and regulatory networks through the use of statistical tools and computational modeling. These findings will be shown to result in better understandings about the mechanisms of life, including the role of genes and the environment in regulating behavior. Graphics and software animations will explain how scientists study data to detect important molecular patterns and relationships through scrutiny of nonlinear information representing multiple scales of space and time. The goal is to acculturate students and teachers about the practice of this kind of quantitative biology. Interactive modules will demonstrate the utility of harmonizing incompatible large dataset structures, combining results across biomedical disciplines, and hypothesis-generating, rather than hypothesis-driven, science that data mining offers. The project will produce high school/college curriculum and online educational resources about genes and behavior. Learning goals will be aligned with Next Generation Science Standards.