Transforming Data Sharing: The Role of Streamlit in Enhancing Research Transparency

Transparency in scientific research is integral to high quality research and reinforcing public trust in the scientific community. This has been reflected in the policies of several funding agencies such as the NSF and NIH, which encourage transparent approaches for result dissemination and plans for data sharing. Although data can be made available in repositories, it may still be a significant challenge for others to explore and interact with it. One option for researchers to share data and visualizations in interactable and interoperable ways is via Streamlit, an open-source library that translates the output of Python scripts into an interactive web application. Streamlit can then deploy the application on its web page, allowing others to explore data in real-time. Python scripts and data files are stored in a GitHub repository, which itself can be either public or private. This allows quantitative data to be made publicly available and interactable, in a way that would not require users to have explicit knowledge of programming to make queries or generate and explore figures. In this talk we will discuss the process of establishing one such page, and offer examples of how we have used it to display findings from a large-scale study of quantum mechanics courses in the United States.