Science needs to rethink how it interacts with big data: Five principles for effective scientific big data systems

We should be in a golden age of scientific discovery, given that we have more data and more compute power available than ever before. But paradoxically, in many data-driven fields, the eureka moments are becoming more and more rare. Scientists, and the software tools they use, are struggling to keep pace with the explosion in the volume and complexity of scientific data. We describe here, five architectural principles we believe are essential in order to create effective, robust, and flexible platforms that make us of the best of emerging technology.