Computational methods for the representation and analysis of data have drastically increased the objectivity, reliability, and the practical implications of research conducted throughout most scientific pursuits. Our rapidly-emerging potential to transform digital data into objective measures of human behavior, thoughts, and feelings has perfectly positioned personality science as a critical discipline that will benefit from today’s ongoing digital revolution. Here, we review and discuss some of the most promising approaches to computational personality assessment based on data from experience sampling, natural language, online social media, mobile sensing, and images. We present a concise overview of key findings, discuss the potential and promise ofcomputational personality assessment, and highlight important remaining questions in their development and application. We conclude with an optimistic outlook on how computational assessment could fuel the transition from personality research to personality science.

We describe the data management bylaws for the Psychological Science Accelerator (PSA), a distributed network of laboratories dedicated to completing large-scale collaborative behavioral science projects. Our bylaws are organized around the principles of ethical data use, security, accuracy, usability, transparency. We describe how these embodied throughout the lifecycle of a PSA project, from project proposal to data release. In addition to setting up the policies and guidelines for the management of PSA data, we hope this document can provide a useful best practices for individual researchers thinking about the management of their own behavioral science data.