In Clinical Trial Data Notes, Data Notes are designed to present highly-legible, interoperable data sets that have the potential to improve understanding for end users anywhere in the clinical trials value chain. The data described therein will be available via our ClinicalTrialDataDB data repository, and must align with FAIR Principles
for scientific data.
Data Notes center a particular dataset, provide thorough methodology on data regarding production and validation, and highlight potential opportunities for reuse. If a manuscript contains more detailed biological, medical or technical analyses of data, the authors should instead submit a Research Article.
Our aim with Data Notes is to incentivize the production and dissemination of useful data, even in cases where the author themselves does not plan to publish more detailed analysis, or believe this analysis will take a good deal more time.
Our Editorial process assesses the following:
- FAIR principle agreement, or how Findable, Accessible, Interoperable and Reusable the data is.
- Legibility, with respect to how comprehensible the data set is for patients, sponsors, and other would-be researchers.
- Comprehensiveness, considered in context of historically available data and limitations communicated by the author.
- Potential for reuse, either by sponsors, clinical research organizations, or patients. We prioritize datasets which are thoroughly documented, supported by metadata, and add value to similar data already available.
Our editorial team explicitly will not consider the following, so as not to disadvantage unglamorous contributions:
- Whether the data is rare or unusual in nature.
- Whether a novel methodology or technology was used to create dataset.
- Whether any subset of the data has been referenced in prior publications (so long as novel contributions to the dataset are present).
The following word processor file formats are acceptable for the main manuscript document:
- Microsoft word (DOC, DOCX)
- Rich text format (RTF)
- Portable document format (PDF)
- TeX/LaTeX (use OUP TeX template)
- DeVice Independent format (DVI)
If submitting via TeX, all editable sources are required so as to mitigate unnecessary publication delays.
Data Access Requirements
Dataset(s) included within a Data Note must be available for our reviewers to assess along with the manuscript. This should be done via submission to our Clinical Trial Data Note Archive
Following approval, said datasets must be made available under a Creative Commons CC0
waiver, without restrictions but subject to student opt-in to sharing the data. When submitting a dataset(s) which builds upon prior work, said prior work must be clearly referenced within a citation.
Clinical Trial Data Notes was built with large datasets in mind. There is no data processing or storage fee. The journal will provide a direct link from the published manuscripts to our Data Archive. Datasets will be provided with DOI’s following publication, in order to facilitate credit sharing and discoverability.
If you have sensitive data only appropriate for controlled-access databases (e.g. medical data), please indicate this when submitting your manuscript. When data therein has been consented to be openly shared, the editors may ask that you include an incomplete, unsigned version of the consent form alongside the data. You will also be asked to confirm that you have followed all national guidelines on data collection and release in the country the research was carried out. If you have any questions, feel free to reach out via email@example.com.
Data submission is required at the point of manuscript submission, so as to minimize delays that are inevitable with multiple submission cycles or phases.
When submitting said data, you need to include sufficient description of said data, not just submission of the data alone. For this, please provide our team with the following information:
1. Descriptive, unique title for said data. This title typically begins with “The data for…”
2. Data Abstract: a brief description of the dataset(s) included and their potential use for the scientific community.
3. Data Author(s): This can differ from that of the submitted manuscript.
4. Data Type(s): For example, adverse effect data, demographic data, transcriptome, imaging, movies, etc.
5. Data Size: An estimate of dataset size.
6. Readme File: The Readme should contain information about the files (to be) hosted in a dataset, including naming conventions and directory format of any zipped files.
7. Relevant Link(s): Hypertext links for any relevant data that is publicly available, or any related accession numbers in other repositories.
8. Acknowledgements: Please be sure to include a list of grants and funding agencies and information on consortium or projects if there are any associated with these data.