Reproducible Research: Where do we stand ?

Arnaud Legrand is a tenured CNRS researcher at Grenoble University, France since 2004. He obtained his M.S. and Ph.D. from the Ecole Normale Supérieure de Lyon, France in 2000 and 2003, and his Habilitation Thesis in 2015 from Grenoble University, France.  His research interests encompass the study of large scale distributed computing infrastructures such as clusters, grids, desktop grids, volunteer computing platforms, clouds, ... when used for scientific computing. More specifically, his research focuses on theoretical tools for optimizing the exploitation of such platforms (scheduling techniques, combinatorial optimization and game theory) and on performance evaluation of such systems, in particular through simulation, visualization and statistical analysis. He is one of the leaders of the SimGrid project, an open source simulation toolkit whose specific goal is to facilitate research in the area of parallel and distributed system optimization. In the last four years, he has been actively promoting better experimental practices and scientific methodology of through numerous tutorials and keynotes in conferences and summer schools.

Résumé :

Reproducibility of experiments and analysis by others is one of the pillars of modern science. Yet, the description of experimental protocols, software, and analysis is often lacunar and rarely allows a third party to reproduce a study.  Such inaccuracies has become more and more problematic and are probably the cause of the increasing number of article withdrawal even in prestigious journals and the realization by both the scientific community and the general public that many research results and studies are actually flawed and misleading.  Open science is the umbrella term of the movement that strives to make scientific research, data and dissemination accessible to all levels of an inquiring society. Reproducible research encompasses the technical and social aspects of science allowing and promoting better research practices. In this talk, I will give a broad overview of the challenges at stake and of emerging solutions. I will also particularly discuss the role computer science can play in this topic.