Inter-university Consortium for Political and Social Research, University of Michigan.
Department of Psychology, University of Michigan.
Am Psychol. 2018 Feb-Mar;73(2):146-156. doi: 10.1037/amp0000258.
Research transparency, reproducibility, and data sharing uphold core principles of science at a time when the integrity of scientific research is being questioned. This article discusses how research data in psychology can be made accessible for reproducibility and reanalysis by describing practical ways to overcome barriers to data sharing. We examine key issues surrounding the sharing of data such as who owns research data, how to protect the confidentiality of the research participant, how to give appropriate credit to the data creator, how to deal with metadata and codebooks, how to address provenance, and other specifics such as versioning and file formats. The protection of research subjects is a fundamental obligation, and we explain frameworks and procedures designed to protect against the harms that may result from disclosure of confidential information. We also advocate greater recognition for data creators and the authors of program code used in the management and analysis of data. We argue that research data and program code are important scientific contributions that should be cited in the same way as publications. (PsycINFO Database Record
研究透明度、可重复性和数据共享在科学研究的完整性受到质疑的时候,维护了科学的核心原则。本文通过描述克服数据共享障碍的实际方法,讨论了如何使心理学研究数据能够进行可重复性和重新分析。我们研究了围绕数据共享的关键问题,例如谁拥有研究数据、如何保护研究参与者的机密性、如何给予数据创建者适当的信用、如何处理元数据和代码本、如何处理出处以及其他具体问题,例如版本控制和文件格式。保护研究对象是一项基本义务,我们解释了旨在防止因披露机密信息而可能造成伤害的框架和程序。我们还主张更多地认可数据创建者和用于管理和分析数据的程序代码的作者。我们认为,研究数据和程序代码是重要的科学贡献,应该以与出版物相同的方式引用。