Today’s scientific instruments, sensors and computer simulations are producing complex data at exponential rates—creating a virtual data deluge. Although these data represent an unprecedented resource, their size and complexity are overwhelming scientists’ current practices to extract useful information.
Effectively harnessing these large and complex scientific datasets requires better tools, practices and new solutions. We need fundamentally different techniques for taking advantage of modern science data developed by an emerging, multidisciplinary type of research—data science.
Data scientists combine scientific expertise, computational knowledge and statistical skills to solve critical problems and make new discoveries. The research community recognizes the need for these skills, but the lack of academic incentives creates a critical shortage of practitioners. In other words, science may be data-rich, but will remain discovery-poor without the institutional commitment, people-power and technology needed to mine the data and reveal hidden breakthroughs.
That’s why we are supporting the people who innovate around data-driven discovery—through the creation of data science hubs at major research universities, and through investigator awards and data science projects.