In computational sciences such as image processing, publishing usually isn't enough to allow other researchers to verify results. Often, supplementary materials such as source code and measurement data are required. Yet most researchers choose not to make their code available because of the extra time required to prepare it. Are such efforts actually worthwhile, though? © 2012 IEEE.status: publishe
Journal policy on research data and code availability is an important part of the ongoing shift towa...
International audienceYour editorial "A problem shared is a problem halved" raises several important...
We believe computational science as practiced today suffers from a growing credibility gap - it is i...
Reproducing computational results described in a publication often requires more than only the artic...
Whilst many funders and publishers require or encourage researchers to share data underlying publica...
This poster was presented at Reproducibility, Replicability and Trust in Science Conference, 7th Sep...
Scientific computation is emerging as absolutely central to the scientific method, but the prevalen...
Ensuring reproducibility is one of the main goals of open science. To achieve reproducibility of sci...
Presented at the Society for Industrial Mathematics 2019 meeting on Computational Science and Engine...
Sharing code is becoming increasingly important in the wake of Open Science. In this review I descri...
Though computational methods are widely used in many disciplines, many researchers do not share the ...
Presentation given on October 27, 2016 at Data Reproducibility: Integrity and Transparency program a...
Across science disciplines, software code is being written by scientists and deemed critical to rese...
SORTEE Conf 2022 Why don’t we share data and code? July 11th, 15:00 AEST (GMT +10) Abstract: In ...
Computational analyses are playing an increasingly central role in research. Journals, funders, and ...
Journal policy on research data and code availability is an important part of the ongoing shift towa...
International audienceYour editorial "A problem shared is a problem halved" raises several important...
We believe computational science as practiced today suffers from a growing credibility gap - it is i...
Reproducing computational results described in a publication often requires more than only the artic...
Whilst many funders and publishers require or encourage researchers to share data underlying publica...
This poster was presented at Reproducibility, Replicability and Trust in Science Conference, 7th Sep...
Scientific computation is emerging as absolutely central to the scientific method, but the prevalen...
Ensuring reproducibility is one of the main goals of open science. To achieve reproducibility of sci...
Presented at the Society for Industrial Mathematics 2019 meeting on Computational Science and Engine...
Sharing code is becoming increasingly important in the wake of Open Science. In this review I descri...
Though computational methods are widely used in many disciplines, many researchers do not share the ...
Presentation given on October 27, 2016 at Data Reproducibility: Integrity and Transparency program a...
Across science disciplines, software code is being written by scientists and deemed critical to rese...
SORTEE Conf 2022 Why don’t we share data and code? July 11th, 15:00 AEST (GMT +10) Abstract: In ...
Computational analyses are playing an increasingly central role in research. Journals, funders, and ...
Journal policy on research data and code availability is an important part of the ongoing shift towa...
International audienceYour editorial "A problem shared is a problem halved" raises several important...
We believe computational science as practiced today suffers from a growing credibility gap - it is i...