Data-Intensive Research & Scientific Discovery

Abstract

Modern research is becoming data-intensive. Data-intensive refers to volume, velocity, heterogeneity, and complexity of data as well as the intricate interactions among combinations of research objectives, models, users, and information systems that deal with these data. Increasingly, scientific discovery will be powered by advanced computing capabilities that help researchers explore, manipulate, analyze, visualize, and synthesize big datasets.Computation is a fundamental element of modern research. Information Technology (IT) professionals use algorithms to design experiments, simulate real-world operations, analyze scientific problems, and suggest practical solutions. The speed at which any given scientific discipline advances will depend on how well its researchers collaborate with one another and with IT professionals in areas such as cloud computing, workflow management, databases, modeling, analytics, and others. As a result, computation changes the role of IT professionals from service providers to collaborators whose input is critical to the success of the research. Through their understanding of technology and best practices, IT professionals contribute substantive knowledge to the advancement of research methodology and modern science.This presentation discusses a new paradigm of scientific discovery based on data-intensive research and offers insights into how it can be realized through a few real-world research projects at the Agricultural Research Service.