DrWatson: the perfect sidekick for your scientific inquiries

Abstract

Doing scientific work always involves a lot of focus and scrutiny, since producing a scientific result requires several levels of depth of analysis, all of which must be as accurate and as reproducible as possible. All this required scrutiny should be naturally translated into the codebase of the scientific project. One should strive for a code that is doing what it is supposed to, is reproducible, doesn't break over time, is sufficiently clear of bugs, and with simulation results that are appropriately labelled, and more. The challenges associated with carrying out scientific work should not be made any worse by the difficulties of managing the codebase and resulting data/simulations. An unfortunate but likely outcome of this stress is that scientific codebases tend to be sloppy: folders are not organized, there is no version control, data are not provenanced properly, most scripts break over time, and the whole project is very hard, if not impossible, to reproduce. We have created the software DrWatson to make the process of scientific project management easier. In this paper we will describe how DrWatson results in an efficient scientific workflow, taking time away from project management and giving it to doing science.

An Analysis of Approximation Algorithms for Iterated Stochastic Integrals and a Julia and MATLAB Simulation Toolbox

“…. By integrating (9) with respect to the Wiener process (W j t ) t∈[0,h] and following the representation in [29,30], we get the representation…”

“…The benchmark is performed on a computer with an Intel Xeon E3-1245 v5 CPU at 3.50 GHz and 32 GB of memory using Julia version 1.6. Furthermore, the Julia package DrWatson.jl [9] is employed. The simulation results for both settings with m = 100 and m = 1000 are shown in Figure 3.…”

Of Animal Husbandry and Food Production—A First Step towards a Modular Agent-Based Modelling Platform for Socio-Ecological Dynamics

“…In order to enable reproducibility of the simulation and its results, the complete code and the input data, including a detailed model description, following the second update of the 'ODD' protocol [74], are available online at https://doi.org/10.5281/zenodo.5141854, accessed on 7 December 2021. To further establish the simulation's reproducibility, the simulation environment was set up and can be instantiated using DrWatson.jl [75].…”

Reproducible Spectrum and Hyperspectrum Data Analysis Using NeXL

“…Third parties may add packages to the repository but must follow strict guidelines as to versioning, continuous integration testing and other best practices. When the package manager is combined with libraries like DrWatson (Datseris et al, 2020), a toolkit for reproducible data analysis, Julia has all the features necessary to implement reproducible data analysis. Tutorials on Julia syntax and packages are available through resources like JuliaAcademy (https://juliaacademy.com/), the Julia website (https://julialang.…”