Haaf Julia M, Hoffstadt Madlen, Lesche Sven
University of Potsdam, Karl-Liebknecht-Str. 24/25, 14476, Potsdam, Germany.
University of Amsterdam, Amsterdam, The Netherlands.
Behav Res Methods. 2025 Jun 24;57(8):208. doi: 10.3758/s13428-025-02717-z.
Publicly available data are required to (1) assess the reproducibility of each individual findings in the literature, and (2) promote the reuse of data for a more efficient use of participants' time and public resources. Current data-sharing efforts are well suited for the first goal, yet they do not sufficiently address the second goal. Here, we show how structured collections of open data can be useful, as they allow a larger community of researchers easy access to a large body of data from their own research area. We introduce the Attentional Control Data Collection, a SQL database for attentional control experiments. We illustrate the structure of the database, how it can be easily accessed using a Shiny app and an R-package, and how researchers can contribute data from their studies to the database. Finally, we conduct our own initial analysis of the 64 data sets in our database, assessing the reliability of individual differences. The analysis highlights that reliability is generally low, and provides insights into planning future studies. For example, researchers should consider increasing the number of trials per person and condition to at least 400. The analysis highlights how an open database like ACDC can aid meta-analytic efforts as well as methodological innovation.
（1）评估文献中每个单独研究结果的可重复性，以及（2）促进数据的再利用，以便更有效地利用参与者的时间和公共资源。当前的数据共享工作非常适合第一个目标，但它们没有充分解决第二个目标。在这里，我们展示了结构化的开放数据集合如何有用，因为它们使更大的研究人员群体能够轻松访问来自其自身研究领域的大量数据。我们介绍了注意力控制数据收集，这是一个用于注意力控制实验的SQL数据库。我们说明了数据库的结构、如何使用Shiny应用程序和R包轻松访问它，以及研究人员如何将他们研究中的数据贡献到数据库中。最后，我们对数据库中的64个数据集进行了自己的初步分析，评估个体差异的可靠性。分析突出表明可靠性普遍较低，并为规划未来研究提供了见解。例如，研究人员应考虑将每人每种条件下的试验次数增加到至少400次。该分析突出了像ACDC这样的开放数据库如何有助于元分析工作以及方法创新。
