This award permits Dr. Jaaroslaw Nabrzyski and his collaborators at Notre Dame University to enable transformative research in the social sciences through the acquisition of a Data Analytics Cluster for Computational Social Sciences (DACCSS). The major capabilities provided by DACCSS will accelerate existing research throttled by insufficient computational capability, enable analysis and discovery at scales previously inaccessible, incubate new research projects and enhance multidisciplinary collaboration between social scientists and their peers. This investigation of broadly defined social phenomena through the medium of computing and advanced information processing technologies can be generally referred to as computational social science (CSS). At the University of Notre Dame, multiple departments have a growing number of faculty leveraging CSS techniques and capabilities. The DACCSS acquisition provides them with over 2,600 CPU cores, 5,300GB of RAM, and 60TB of high performance storage in clustered data analytics servers connected with a state of the art network fabric; running the world's most advanced analytics software.
The size, number, and availability of social science datasets (such as census data, detailed surveys, historic records, and logs from electronic devices/sensors) is growing rapidly. Subsequent data analysis facilitated by high performance computational tools, now shapes the way that scholars discover and communicate their findings with students, colleagues, and the public. The DACCSS system will enable this CSS research supporting social, behavioral, and economics (SBE) research activities such as the following: Sociology: Analysis of social network patterns and dynamics with complex mobile phone topologies. Psychology: Genome-wide analyses of multivariate phenotypes to investigate the genetic underpinnings of mental and personality disorders. Economics: Optimization of complex and dynamic multi-agent utility maximizing models to understand the evolution and impact of household savings rates with important correlations as driving factors for economic growth. DACCSS is essential for transformative discovery in these and numerous additional SBE research endeavors.
The emergence of CSS requires innovation in training for new social science scholars; the DACCSS operation and training management plan will have direct integration with a CSS training plan for faculty, post doctoral researchers and students of sufficient rigor to share with peer universities. DACCSS will also be accessible to the classroom with integration into numerous courses taught by the investigators. DACCSS-supported research will be integrated into multiple existing outreach programs to underrepresented minority and high school students such as the Notre Dame Summer Scholars Research Computing Track and the NSF REU Site program in Computational Science.