BITSS supports universities, research, and policy analysis organizations through training on best practices and development and technical review of internal protocols for transparent and reproducible research. We do this by considering each organization’s research goals and practices and identifying mechanisms for integrating tools and best practices for improved transparency and reproducibility.
BITSS is collaborating with AEA Data Editor Lars Vilhuber as part of the Advancing Computational Reproducibility in Economics (ACRE) project. ACRE includes capacity-building activities for economics researchers, and an online platform to facilitate the systematic sourcing, cataloging, and review of attempts to verify and improve the computational reproducibility of published work in economics.
BITSS supported the IDB through training and the development of a technical note outlining best practices for transparency and reproducibility intended for researchers at the Bank.
Promoting Transparent and Reproducible Research at the Centre for Experimental Research on Fairness, Inequality, and Rationality (FAIR)
BITSS is supporting FAIR, a center at the Norwegian School of Economics, in scaling up transparency and reproducibility through the development of internal quality protocols, training on transparency and reproducibility tools and practices, and support for a network of change-makers at FAIR using the Catalyst model.
As part of a Catalyst training project, BITSS supported the National Institute of Public Health (Instituto Nacional de Salud Pública, INSP), a public research agency in Mexico, in establishing institutional infrastructure for research transparency and reproducibility, including Standard Operating Procedures (SOP), graduate-level public health coursework, a website for sharing resources, and training for INSP research staff.