Automation Is Coming to Research [In the Spotlight]

The rapid advancement and proliferation of information and communication technologies in the past two decades significantly impacted how we do research. The research process has been digitalized and is increasingly relying on growing computing power and storage capacity to gather and process a constant production of data-our observations of systems and phenomena we would like to understand, control, and improve. To turn these observations into useful knowledge, findings, discoveries, and better decisions, the data needs to be intelligently processed, and the results of such processing suitably visualized. In research communities, the process of obtaining, processing, and visualizing data to yield new insights is usually captured and shared through scientific papers, which normally cite other papers to connect new and previous findings. This creates an intricate web of interlinked papers comprising most of our scientific knowledge. This web is growing exponentially, so it is increasingly more difficult to search and navigate. It is also not easy to validate all published results, and we may often rediscover things that are already known.