This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
Reproducibility is a fundamental pillar in science but it has recently been described as hard and challenging to achieve, as stated in numerous editorials and papers, some of which alert on a “reproducibility crisis”. In this article we outline 1/ the approach taken to put Reproducible Research (RR) in the agenda of the GIScience community, 2/ first actions and initial lessons learned towards the discussion and adoption of RR principles and practices in the workflows and habits of researchers, and finally, we present 3/ our short-term strategy (two years) and specific actions to achieve the main goal of making RR an integral part of scientific workflows of the GIScience community.
This preprint submission is intended for the OGRS'2018 Collection
Figure 1: Actors ecosystem layered in hierarchical levels
Thanks, always nice to have other people point to your own projects!
I agree with you that a concept which could be added is that the next workshop should be "packaging" of research (parts of research are mentioned already), for which o2r's ERC are an example, but so are ReproZip's packages, plain R packages, or Research Objects (RO). I think from the level of detail it would not fit to reference specific tools though.
this article boards a pertinent subject that is increasingly important in modern research. The experiments reported are relevant and concur with previous studies. However, it is not clear why are these experiments classified as a "Community" approach, when it exclusively targets individual behaviour (fitting in the bottom-up framework described in the introduction). It is neither clear how this individual-centric approach propagates upwards in the hierarchies identified.
I also miss some reflection on the influence the "Community" can have on scientific publications. Beyond daily practices, researchers are also reviewers and editors. Each individual researcher can promoting RR not only by practicing it, but also by demanding it in peer review. For instance, when reviewing an article reporting a novel algorithm, the reviewer should demand the necessary materials to run it by her/himself.
Finally I would note that the text would benefit of some further polishing to eliminate some grammar glitches here and there.