Abstract

We propose a symposium that will present interdisciplinary methods and innovations aimed at fostering a research culture that values replicability and reproducibility. Specifically, the symposium will include the following contributions:

“Accelerating Computational Reproducibility with the Social Science Reproduction Platform” by Fernando Hoces de la Guardia and Aleksandar Bogdanoski. Presents the Social Science Reproduction Platform (SSRP), an open-source platform that crowdsources and catalogs attempts to assess and improve the computational reproducibility of published research. The SSRP will produce metrics on the levels of reproducibility of various bodies of literature and can be used as a teaching tool to introduce students to fundamental concepts and research methods in the social sciences.

“Systematizing Confidence in Open Research and Evidence” by Olivia Miske and Nick Fox. Provides an overview of the SCORE project approach to processes and procedures in attempting large-scale global replication and reproduction projects, including sourcing collaborators, ethics, peer reviewed pre-registration, and reporting.

“Improving Research Code Quality and Execution” by Ana Trisovic. Presents lessons learned and recommendations for researchers based on a large-scale evaluation of the quality, programming literacy, and reproducibility of over 2100 datasets that contain research code in R from the Harvard Dataverse repository.

“Internal replication of computational workflows in scientific research” by Jade Benjamin-Chung. Presents a process through which investigators from an original study team independently reproduce their computational workflow in order to identify and resolve errors, helping prevent biases that occur during computational analyses prior to publication.