Overview

Computational metascience is an emerging field of research that combines computer science, data science, and scientific inquiry to better understand the scientific process itself. The goal of computational metascience is to use computational methods to study how science is conducted, how knowledge is generated and disseminated, and how scientific practices and norms evolve over time. One key aspect of computational metascience is the use of large-scale data analysis to examine patterns in scientific publications, collaborations, and funding. For example, researchers might use natural language processing techniques to analyze the language and rhetoric used in scientific articles or social network analysis to examine patterns of collaboration between scientists. Another important aspect of computational metascience is the development of tools and methods to improve scientific reproducibility and transparency. This might include the creation of open-source software, data repositories, and standards for reporting and sharing scientific results.