Abstract

Over the past two decades, computational methods have radically changed the ability of researchers from all areas of scholarship to process and analyze data and to simulate complex systems. But with these advances come challenges that are contributing to broader concerns over irreproducibility in the scholarly literature, among them the lack of transparency in disclosure of computational methods. Current reporting methods are often uneven, incomplete, and still evolving. We present a novel set of Reproducibility Enhancement Principles (REP) targeting disclosure challenges involving computation. These recommendations, which build upon more general proposals from the Transparency and Openness Promotion (TOP) guidelines and recommendations for field data , emerged from workshop discussions among funding agencies, publishers and journal editors, industry participants, and researchers …

Date

December 9, 2016

Authors

Victoria Stodden, Marcia McNutt, David H Bailey, Ewa Deelman, Yolanda Gil, Brooks Hanson, Michael A Heroux, John PA Ioannidis, Michela Taufer

Journal

Science

Volume

354

Issue

6317

Pages

1240-1241

Publisher

American Association for the Advancement of Science