In light of the ongoing ‘replication crisis’ across the disciplines of the social sciences, there is increased pressure on scholars to engage in research practices that are ‘open’ meaning transparent, verifiable, and reproducible. Our course aims to develop the perspectives, knowledge, and skills needed by researchers to make their research more open. Broadly, we will cover the what, why, and how of open science practices.
The course follows the research cycle through four key stages:
- Open Mind;
- Open Protocols;
- Open Workflows;
- Open Reports.
Course participants will read materials and hear lectures on the theories and philosophy of openness, engage with applied examples of open (and less open) research, and work hands-on with software tools to develop and apply open research practices to their own scientific workflow.
Examples will be drawn from across the social sciences and students will have the opportunity to work their preferred statistical software (with a strong preference shown for R or Stata).
Upon completion of the course, students will be able to:
– Define open science and evaluate the openness of current research;
– Discuss the main drivers and obstacles to openness and critically assess the proposed solutions;
– Implement fundamental open science practices in their own workflows;
– Apply these skills through the use of open science software and apps
Additional Suggested texts include:
Manual of Best Practices in Transparent Social Science Research, by Garret Christensen (BITSS, 2016). Available at: http://www.bitss.org/education/manual-of-best-practices/
The Workflow of Data Analysis Using Stata by J. Scott Long (Stata Press, 2008)
Reproducible Research with R & RStudio by Christopher Gandrud (Chapman & Hall/CRC, 2013)
Implementing Reproducible Research edited by Victoria Stodden, Friedrich Leisch, and Roger D. Peng (Chapman & Hall/CRC, 2014).
The Practice of Reproducible Research edited by Justin Kitzes, Daniel Turek, and Fatma Imamoglu (under review at Oxford and UC Press).