In 2022, the first Open Science Team of the Faculty of Applied Sciences at Delft University of Technology was established, including members from different departments and career stages. The team conducted a series of surveys and meetings, aiming to examine which types of support would be the most useful for improving Open Science practises within the faculty's individual departments.
The conclusions drawn from this effort were summarized and can be found in the following open repository on Zenodo:
https://zenodo.org/record/7641319
To learn about what employees of the Bionanoscience Department think about Open Science, the team set up an online survey on the topic, which was made available from 03/11/2022 to 02/12/2022. The terminology used within this survey can be found here.
For more information, please contact Esther Plomp.
The questions asked within the survey as well as the anonymized answers can be found in the data sheet Open_Science_Survey_BN_cln.xlsx contained within this repository. The file Open Science Survey BN web results.pdf contains the survey results in the representation generated by Microsoft Forms.
Notably, this repository contains a Jupyter notebook Survey_results.ipynb. The notebook analyses and graphically represents the data contained within the Excel sheet, extracted as pandas dataframes. The graphical representations include bar charts, pie charts and stacked bar charts, using matplotlib. Where applicable, data is sorted (multidimensionally) according to counts.
The notebook can be run in Binder:
To run the notebook locally, clone the repository to your local machine and follow the instruction below to set up the required Python environment:
- Open your local folder in a terminal
- Create the environment with
conda env create --file environment.yml --force - Activate the environment with
conda activate open_science_survey - Run JupyterLab with
jupyter lab - In JupyterLab, open the file Survey_results.ipynb and follow the instructions there
The survey results can be viewed either directly within the Jupyter notebook, or in the output auto-generated by it (in the folder plot_results_BN as separate pdf files, with subfolders summarizing results for either a certain type of career stage, or all collected results).