2024/08/29 by Franziska Usée, Christiane A. Melzig, Dirk Ostwald · 1 voice
Computer Science · Decision Sciences · #Data Visualization and Analytics #Research Data Management Practices #Scientific Computing and Data Management
paper · pdf · doi:10.5964/ejop.12811
openalex publication_date 2024/08/29 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/22
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.