Being Open-minded About Open Science

Over the past decade, psychology has endured a reproducibility crisis. The reproducibility crisis brought into question the validity of many research findings, as well as shining a light on unfavorable or poor research practices in the field of psychology. As a result, there has been a rise of open science practices and techniques that promote transparency in research from start to finish. This article will outline three of the main techniques used to produce transparent research, as well as how to get started with them.

Preregistration

Preregistration means taking a moment before you begin your research, to describe your hypotheses, methods/research design, and analytic strategy. The goal of preregistration is to shape your research ideas from past theory, and to not mold a research article around the results you find. Preregistration can be flexible as long as you are honest. If you have already collected data, you could preregister your hypotheses and analytic strategy and upload them to an open repository like the Open Science Framework (OSF) before completing your analyses. Additionally, issues do arise during research, and creating amendments to a preregistration is okay, as long as you are transparent about what has changed and why. If you have not collected data, consider submitting a registered report, which allows your research to be accepted for publication in a peer-reviewed journal based on the merit of the theory and research design. If you want to get started with preregistration, check out the As Predicted template on OSF, which contains 8 essential preregistration questions. A bonus of preregistration is that it can help remind you of your hypotheses and intentions if you take a pause from a research project.

Open Materials

Being open with your research material means simply sharing your materials on an open repository, like OSF, GitHub, Dataverse, or within the supplemental materials of a manuscript. Placing your research materials in an open repository allows others to easily and directly replicate your work. This is an excellent and easy way to get started with open science research practices.

Open Data

The final open science practice is open data. This means sharing your data set on an open repository. Open data can help reviewers and other researchers check your work. Additionally, by publicly sharing your data set, it can be used for other publications or can provide resources to those who do not have access to collect their own data. Conversely, if your research is part of a larger data set that you would not like to share, you could make a smaller data file with only the variables of interest. Again, open science practices can be flexible and are meant to help researchers.

I hope this article outlines how easy and flexible open science practices can be. If you want to get started, you can create an Open Science Framework account for free at osf.io and consider using it to store preregistrations, open materials, or open data for your next research article. 

If you have any questions about open science please feel free to email me at [email protected]