Abstract
We are entering an era where large volumes of scientific data, coupled with algorithmic and computational advances, can reduce both the time and cost of developing new materials. This emerging field known as materials informatics has gained acceptance for a number of classes of materials, including metals and oxides. In the particular case of polymer science, however, there are important challenges that must be addressed before one can start to deploy advanced machine learning approaches for designing new materials. These challenges are primarily related to the manner in which polymeric systems and their properties are reported. In this viewpoint, we discuss the opportunities and challenges for making materials informatics as applied to polymers, or equivalently polymer informatics, a reality.