Everything Matters: The ReproNim Perspective on Reproducible Neuroimaging
| dc.contributor.author | Kennedy, David N. | |
| dc.contributor.author | Bates, Julianna F. | |
| dc.contributor.author | Haselgrove, Christian | |
| dc.contributor.author | Hodge, Steven M. | |
| dc.date | 2022-08-11T08:09:52.000 | |
| dc.date.accessioned | 2022-08-23T16:46:40Z | |
| dc.date.available | 2022-08-23T16:46:40Z | |
| dc.date.issued | 2019-02-07 | |
| dc.date.submitted | 2019-03-12 | |
| dc.identifier.citation | <p>Front Neuroinform. 2019 Feb 7;13:1. doi: 10.3389/fninf.2019.00001. eCollection 2019. <a href="https://doi.org/10.3389/fninf.2019.00001">Link to article on publisher's site</a></p> | |
| dc.identifier.issn | 1662-5196 (Linking) | |
| dc.identifier.doi | 10.3389/fninf.2019.00001 | |
| dc.identifier.pmid | 30792636 | |
| dc.identifier.uri | http://hdl.handle.net/20.500.14038/40926 | |
| dc.description | <p>Full author list omitted for brevity. For the full list of authors, see article.</p> | |
| dc.description.abstract | There has been a recent major upsurge in the concerns about reproducibility in many areas of science. Within the neuroimaging domain, one approach is to promote reproducibility is to target the re-executability of the publication. The information supporting such re-executability can enable the detailed examination of how an initial finding generalizes across changes in the processing approach, and sampled population, in a controlled scientific fashion. ReproNim: A Center for Reproducible Neuroimaging Computation is a recently funded initiative that seeks to facilitate the "last mile" implementations of core re-executability tools in order to reduce the accessibility barrier and increase adoption of standards and best practices at the neuroimaging research laboratory level. In this report, we summarize the overall approach and tools we have developed in this domain. | |
| dc.language.iso | en_US | |
| dc.relation | <p><a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&list_uids=30792636&dopt=Abstract">Link to Article in PubMed</a></p> | |
| dc.rights | Copyright © 2019 Kennedy, Abraham, Bates, Crowley, Ghosh, Gillespie, Goncalves, Grethe, Halchenko, Hanke, Haselgrove, Hodge, Jarecka, Kaczmarzyk, Keator, Meyer, Martone, Padhy, Poline, Preuss, Sincomb and Travers. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | data model | |
| dc.subject | neuroimaging | |
| dc.subject | publication | |
| dc.subject | re-executability | |
| dc.subject | reproducibility | |
| dc.subject | Bioinformatics | |
| dc.subject | Computer Sciences | |
| dc.subject | Neuroscience and Neurobiology | |
| dc.subject | Scholarly Communication | |
| dc.subject | Scholarly Publishing | |
| dc.title | Everything Matters: The ReproNim Perspective on Reproducible Neuroimaging | |
| dc.type | Journal Article | |
| dc.source.journaltitle | Frontiers in neuroinformatics | |
| dc.source.volume | 13 | |
| dc.identifier.legacyfulltext | https://escholarship.umassmed.edu/cgi/viewcontent.cgi?article=4739&context=oapubs&unstamped=1 | |
| dc.identifier.legacycoverpage | https://escholarship.umassmed.edu/oapubs/3725 | |
| dc.identifier.contextkey | 14008318 | |
| refterms.dateFOA | 2022-08-23T16:46:40Z | |
| html.description.abstract | <p>There has been a recent major upsurge in the concerns about reproducibility in many areas of science. Within the neuroimaging domain, one approach is to promote reproducibility is to target the re-executability of the publication. The information supporting such re-executability can enable the detailed examination of how an initial finding generalizes across changes in the processing approach, and sampled population, in a controlled scientific fashion. ReproNim: A Center for Reproducible Neuroimaging Computation is a recently funded initiative that seeks to facilitate the "last mile" implementations of core re-executability tools in order to reduce the accessibility barrier and increase adoption of standards and best practices at the neuroimaging research laboratory level. In this report, we summarize the overall approach and tools we have developed in this domain.</p> | |
| dc.identifier.submissionpath | oapubs/3725 | |
| dc.contributor.department | Eunice Kennedy Shriver Center, Department of Psychiatry | |
| dc.source.pages | 1 |

