Usée Franziska, Melzig Christiane A, Ostwald Dirk
Department of Psychology, Clinical Psychology, Experimental Psychopathology, and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany.
Center for Mind, Brain and Behavior, CMBB, Philipps-Universität Marburg and Justus Liebig University Giessen, Giessen, Germany.
Eur J Psychol. 2024 Aug 30;20(3):202-219. doi: 10.5964/ejop.12811. eCollection 2024 Aug.
The value of open research data (ORD), a key feature of open science, lies in their reuse. However, the mere online availability of ORD does not guarantee their reuse by other researchers. Specifically, previous meta-scientific research has indicated that the underutilization of ORD is related to barriers at the level of the ORD themselves, potential reusers of ORD, and the broader academic ecosystem. At the same time, sharing large datasets in an understandable and transparent format that motivates researchers to explore these datasets remains a fundamental challenge. With the present work, we propose interactive data apps (IDAs) as innovative ORD supplements that provide a means to lower barriers of ORD reuse. We demonstrate the use of two open-source Python libraries (Dash, Gradio) for IDA development using two psychological research use cases. The first use case pertains to an experimental quantitative dataset acquired in a clinical psychology setting. The second use case concerns the familiarization with data analysis workflows that are characteristic of natural language processing (NLP). For both use cases, we provide easy-to-adapt Python code that can form the basis for IDA development in similar scenarios.
开放研究数据(ORD)作为开放科学的一个关键特征,其价值在于可重复使用。然而,ORD仅仅在线可用并不能保证其他研究人员会重复使用它们。具体而言,先前的元科学研究表明,ORD未得到充分利用与ORD本身、ORD的潜在使用者以及更广泛的学术生态系统层面的障碍有关。与此同时,以一种易于理解和透明的格式共享大型数据集,从而激励研究人员探索这些数据集,仍然是一项根本性挑战。通过本研究,我们提出交互式数据应用程序(IDA)作为创新性的ORD补充手段,为降低ORD重复使用的障碍提供一种途径。我们使用两个心理学研究用例展示了如何使用两个开源Python库(Dash、Gradio)进行IDA开发。第一个用例涉及在临床心理学环境中获取的一个实验性定量数据集。第二个用例涉及熟悉自然语言处理(NLP)特有的数据分析工作流程。对于这两个用例,我们都提供了易于改编的Python代码,这些代码可作为类似场景中IDA开发的基础。