Reproducible Research is like riding a bike

Carlos Granell; Daniel Nüst; Frank O Ostermann; Rusne Sileryte

doi:10.7287/peerj.preprints.27216v1

Reproducible Research is like riding a bike

Carlos Granell ¹, Daniel Nüst², Frank O Ostermann³, Rusne Sileryte⁴

1 Institute of New Imaging Technologies, Universitat Jaume I de Castellón, Castellón, Spain

2 Institute for Geoinformatics, University of Münster, Münster, Germany

3 Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, The Netherlands

4 Faculty of Architecture and the Built Environment, Delft University of Technolog, Delft, The Netherlands

DOI: 10.7287/peerj.preprints.27216v1

Published: 2018-09-16
Accepted: 2018-09-16

Subject Areas: Data Science, Spatial and Geographic Information Systems
Keywords: Open science, GIScience, Reproducible conference publications, Open access, AGILE, Data science, Reproducible research

Copyright: © 2018 Granell et al.
Licence: 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.

Cite this article: Granell C, Nüst D, Ostermann FO, Sileryte R. 2018. Reproducible Research is like riding a bike. PeerJ Preprints 6:e27216v1 https://doi.org/10.7287/peerj.preprints.27216v1

Abstract

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.