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Research Open Science Open Research Award

Publishing all research items open access in a research field which lacks open acces publishing

Timo Plath, PhD candidate, Thermal and fluid engineering, University of Twente

Open Research objectives / Practices

My case study is about making research, data, software and additional material accessible, more reproducible as well as transparent by utilizing specific open source tools.

Introduction

In this case all research items were published open access. Everyone will be able to reproduce the data gathered by the experimental design we utilized in the research article. Furthermore Python was used to create codes for the data analysis, process analytical technology and reproducibility on calibration of analysis methods. The developed process analytical technology (post processing videos to measure residence time distributions by the concentration of a dye) can now be used by other researchers and does not have to be reconstructed by each research group independently. Having codes for the data analysis and calibration of analytical methods will greatly benefit the reproducibility and transparency provided by the dataset. Moreover all figures of the article can be reproduced by the python codes. On top of this Jupyter notebooks were created to give a template on how to access the dataset and will hopefully facilitate open research practices along with the other published material.

Motivation

In research articles about twin-screw wet granulation for pharmaceutical formulations a lot of experimental designs are reported. All of these designs are highly dependent on formulations and screw geometries and thus report many different and contrary findings. Furthermore most of these articles are not published open access and the corresponding data is not published. By publishing all developed code and software open access all researchers in the field can investigate the research outputs. Moreover the experimental design is beneficial for the development of predictive models and the published dataset can now serve as a basis for this.

Lessons learned

It was a challenge to make everything work according to the FAIR principles. It was hard to keep the data clean and keep track of the data which should be published. I think this is a point where the infrastructure is missing a useful tool. Furthermore,

URLs, references and further information

Last modified:11 January 2024 1.27 p.m.