Established in 2016, The Big Data Discovery and Diversity- Research Education Advancement and Partnership (BD3-REAP) program at California State University, Fullerton (CSUF) in partnership with University of Southern California (USC) aims to engage students and faculty in Big Data science (BDs). By integrating CSUF’s strong history in training underrepresented students, as well as existing epidemiology, neuroscience and statistical expertise with USC’s Big Data for Discovery Science (BDDS), we aim to establish an innovative program on BDs comprehension, computation, and analysis related to neuroimaging, genomics/proteomics and epidemiologic factors that incorporates BDs concepts into classroom learning while emphasizing multi-faceted undergraduate research experiences for predominantly underrepresented students.
The advent of BDs has generated enormous amounts, varieties, and sources of complex datasets that have vast potential for the creation of new knowledge,particularly in relation to primary and secondary disease prevention (Eaton et al., 2012); yet BDs also brings inherent challenges of utilization and value. A critical cross-cutting issue is the creation of a compelling and effective user experience that can empower biomedical researchers and trainees with limited information technology budgets access to powerful and intuitive tools designed to effectively address the challenges posed by the four dimensions of Big Data: (1) volume: the vast amount of data that is generated through source integration; (2) variety: the lack of standardization that is inherent in combining data from different resources; (3) velocity: the high rate at which data is constantly changing; and (4) veracity: the need for reliability measures and safeguards protecting the confidentiality of the individuals involved (Otero, Hersh, & Jai Ganesh, 2014).
Overall, the increasingly technological and data-driven environments that hold the key to solving critical bioscience questions herald the need for a diverse workforce reflective of community demographics and capable of managing, analyzing, and intelligently organizing and conveying biomedical/health information to scientific and local communities.