An empirical analysis of journal policy effectiveness for computational reproducibility

Publishing date: 2018-03-13

Published on: PNAS

summary: A key component of scientific communication is sufficient information for other researchers in the field to reproduce published findings. For computational and data-enabled research, this has often been interpreted to mean making available the raw data from which results were generated, the computer code that generated the findings, and any additional information needed such as workflows and input parameters. Many journals are revising author guidelines to include data and code availability. This work evaluates the effectiveness of journal policy that requires the data and code necessary for reproducibility be made available postpublication by the authors upon request.

authors: Victoria Stodden, Jennifer Seiler, Zhaokun Ma

link to paper: https://doi.org/10.1073/pnas.1708290115

Icons made by catkuro from www.flaticon.com