If these data could talk - Archive ouverte HAL
Article Dans Une Revue Scientific Data Année : 2017

If these data could talk

Résumé

In the last few decades, data-driven methods have come to dominate many fields of scientific inquiry. Open data and open-source software have enabled the rapid implementation of novel methods to manage and analyze the growing flood of data. However, it has become apparent that many scientific fields exhibit distressingly low rates of reproducibility. Although there are many dimensions to this issue, we believe that there is a lack of formalism used when describing end-to-end published results, from the data source to the analysis to the final published results. Even when authors do their best to make their research and data accessible, this lack of formalism reduces the clarity and efficiency of reporting, which contributes to issues of reproducibility. Data provenance aids both reproducibility through systematic and formal records of the relationships among data sources, processes, datasets, publications and researchers.
Fichier principal
Vignette du fichier
sdata2017114.pdf (1.78 Mo) Télécharger le fichier
Origine Fichiers éditeurs autorisés sur une archive ouverte
Loading...

Dates et versions

hal-01651370 , version 1 (29-11-2017)

Identifiants

Citer

Thomas Pasquier, Matthew K Lau, Ana Trisovic, Emery R Boose, Ben Couturier, et al.. If these data could talk. Scientific Data , 2017, 4, pp.170114. ⟨10.1038/sdata.2017.114⟩. ⟨hal-01651370⟩
26 Consultations
31 Téléchargements

Altmetric

Partager

More