signac: Simple Data and Workflow Management

The signac data management framework (https://signac.io) helps researchers execute reproducible computational studies, scaling from laptops to supercomputers, while emphasizing portability and fast prototyping. Through signac, users can track, search, and archive data and metadata in file-based workflows and automate job submission to high performance computing clusters (http://doi.org/10.1016/j.commatsci.2018.01.035). The signac framework is driven by the data management needs of computational researchers, which increasingly involve large collaborations and open data, where the research data needs to be stored in a coherent and queryable manner. We will discuss how signac facilitates the sharing and archiving of research data and workflows. In addition, we will emphasize recent developments in the framework that have increased flexibility in metadata storage, workflow execution, and data visualization. To demonstrate signac's utility, we will showcase scientific publications that have made use of the project, particularly those that have made their data public. We will highlight our push toward better documentation and community engagement, including promoting best practices in data management, encouraging contributions, and providing support.