Paving the Road to Open Science via Automated Data Documentation
In recent years, various social and economic incentives have threatened the ideal of science, where ideas, results, and hypotheses are continuously subjected to rigorous critique and testing.
In our era, there are an increasing number of studies collecting data as part of their research offering an increasingly data-rich environment for open-access science and integrated research. However, the working practices and underlying frameworks of handling data still require substantial improvements. Replicable and reproducible research are intended to ensure reliable results and well interpreted findings.
But the absence of standardization and tediousness of data documentation practices, alongside the general lack of incentives for researchers to partake in open-access science, are substantial obstacles for achieving this. Furthermore, data documentation, often a tediously manual process, requires scholars to expend considerable time collating and detailing every facet of their data, often with only acknowledgments as rewards. The resulting lack of clear documentation can, in turn discourage those seeking to replicate the results.
We propose an automated solution to this problem in the form of a data documentation package called ‘D2’, which is written in the ‘R’ language and mainly employs ‘R-Markdown’ and ‘Knitr` to generate documentation for the most commonly used data formats with minimal inputs from the user. The aim is that ‘D2’ can be used to ease the burden on researchers of partaking in open science.
Speaker
Ahmed Abdelmaksud, University of Essex
How to attend
If not a member of the Dept. Mathematical Science at the University of Essex, you can register your interest in attending the seminar and request the Zoom’s meeting password by emailing Dr Osama Mahmoud (o.mahmoud@essex.ac.uk)