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NeuroLibre Reproducible Preprints¶
As a registered preprint publisher, NeuroLibre goes beyond the traditional boundaries of research dissemination by offering NeuroLibre Reproducible Preprints (NRPs).
Code, data, and computational runtime are not supplementary but rather integral components of published research.
Embracing this principle, NRPs are built by seamlessly combining the outputs of your preprint’s executable content with the scientific prose, all within the same execution runtime required for your analyses.
Moving from static PDFs with code and data availability statements to NRPs is the quantum leap that modern research yearns for. With NeuroLibre, we are dedicated to make that leap as easy as it gets.
Explore a published NRP
For further details on why moving beyond static text and illustrations is a central challenge for scientific publishing in the 21st century, see the following perspective article by the NeuroLibre team (DuPre et al. 2022):
Bird’s eye view of the NRP publication workflow¶
To submit an NRP you need to provide the following:
- A public code repository that has a single or a collection of Jupyter Notebooks and/or MyST markdown files.
- A public data repository needed to generate the outputs (typically figures) from the executable part of your content.
- Reproducible runtime configurations recognized by BinderHub.
- A bibtex formatted bibliography (paper.bib) and author information (paper.md).
Using your ORCID, you can login to NeuroLibre’s submission portal and fill out a simple form. After content moderation, NeuroLibre starts a technical screening process, which takes place on GitHub using NeuroLibre’s one-of-a-kind editorial workflow, powered by the OpenJournals.
During the technical screening process, our editorial bot RoboNeuro and a screener works with you to ensure a successful build of your NRP on NeuroLibre test servers.
After a successful build, the following reproducibility assets are transferred from our preview server (public) to our production servers (reserved for published NRRs only) and archived individually on Zenodo:
- Docker image
- Dataset (unless already archived)
- Repository (version cut at the latest successful build)
- Built NRP (HTML pages of the executable book)
Each of these reproducibility assets is attributed to every author on the NRP, and they are assigned a DOI (Digital Object Identifier).
Once the archival process is complete, a summary PDF is generated. This PDF is necessary to officially register NRPs as preprints.
All the archived reproducibility assets, cited references, and the link to the reproducible preprint are resource linked to the DOI assigned by NeuroLibre upon publication (DOI: 10.55458/neurolibre).
Similar to that in traditional preprint repositories (e.g. arXiv), NeuroLibre updates metadata relationship to an Author Accepted Manuscript (AAM) or Version of Record (VoR) after your article has been accepted for publication by a journal, following the peer review process and any revisions requested by the reviewers or editors.
Contributions are welcome!¶
- Full-stack server components
- Deploy and configure NeuroLibre servers
- Monitor, Debug, and Improve
- Hosting DashBoards with Dokku
- Infrastructure overview
- Bare-metal to BinderHub
- Bare-metal to local Docker registry and volumes
- BinderHub test mode
- Submission workflow backend
- FAQ - Frequently Asked Questions
- How can I test a NeuroLibre submission ?
- Can I submit a non-github repository ?
- What are the hardware limits on NeuroLibre ?
- I want to contribute, how can I do that ?
- Which languages does NeuroLibre support ?
- What type of review are you doing ?
- How do I manage datasets with NeuroLibre ?
- Which version of
repo2datashould I use ?
- How can I cache my experiments ?
- Can I use Dockerfile for my submission ?