Dryad accepts all research data and is intended for complete, re-usable, open research datasets.
- Dryad does not accept submissions that contain personally identifiable human subject information. Human subjects data must be properly anonymized and prepared under applicable legal and ethical guidelines. Please see additional guidance on human subjects data.
- Dryad does not accept any files with licensing terms that are incompatible with the Creative Commons Zero waiver. For more information, please see Good data practices: Removing barriers to data reuse with CC0 licensing.
- For software scripts and snapshots of software source code, files can be uploaded via Dryad and published at Zenodo, which allows public software deposits with version control for the ongoing maintenance of software packages. If you are only seeking to store code, software, and/or supplemental materials please visit Zenodo.
Preferred file formats
Most types of files can be submitted (e.g., text, spreadsheets, video, photographs, code) including compressed archives of multiple files. Dryad welcomes the submission of data in multiple formats to enable various reuse scenarios. For instance, Dryad's preferred format for tabular data is CSV, however, an Excel spreadsheet may optimize reuse in some cases. Thus, Dryad accepts more than just the preservation-friendly formats listed below.
- README files should be in plain text format (
- Comma-separated values (
CSV) for tabular data
- Semi-structured plain text formats for non-tabular data (e.g., protein sequences)
- Structured plain text (
- README files should be in plain text format (
PDF, JPEG, PNG, TIFF, SVG
FLAC, AIFF, WAV, MP3, OGG
AVI, MPEG, MP4
- Compressed file archive:
TAR.GZ, 7Z, ZIP
We recommend that individual files should not exceed 10GB. This ensures files are easily accessed and downloaded by Dryad users.
There is a limit of 300GB per data publication uploaded through the web interface.
Good metadata helps make a dataset more discoverable and reusable. The metadata should describe the data themselves, rather than the study hypotheses, results, motivations, or conclusions. A thorough description of the data file, the context in which the data were collected, the measurements that were made, and the quality of the data are all important.
- Journal name: If associated with a manuscript, fields for journal name and manuscript number are required; if associated with a published or in-press article, fields for journal name and DOI are required.
- Title: The title should be a succinct summary of both the data and study subject or focus. A good title typically contains 8 to 10 words that adequately describe the content of the dataset.
- Author(s): Name, email address, primary institutional affiliation of main researcher(s) involved in producing the data.
- Abstract: Brief summary of the dataset’s structure and concepts including information regarding values, contents of the dataset, reuse potential and any legal or ethical considerations. If this dataset is associated with a study, abstract language can be similar, but it should focus on the information relevant to the data itself, rather than to the study.
- Research domain: Primary research domain. Domains are drawn from the OECD Fields of Science and Technology classification.
- Keyword(s): Descriptive words that may help others discover your dataset. We recommend that you determine whether your discipline has an existing controlled vocabulary from which to choose your keywords. Please enter as many keywords as applicable.
- Funding Information: Name of the funding organization that supported the creation of the resource, including applicable grant number(s). Each grant and associated award number should be input separately. Options in the drop-down menu are populated from the Research Organization Registry (ROR).
- Research facility: Where the research was conducted, if different from your current affiliation (e.g., a field station). Options in the drop-down menu are populated from the Research Organization Registry (ROR).
- Methods: Any methodological information that may help others to understand how the data were generated (i.e. equipment/tools/reagents used, or procedures followed).
- Related works: Use this field to indicate resources, other than the primary article, that are associated with the data. Examples include related datasets, preprints, etc.
Dryad is a nonprofit organization that provides long-term access to its contents at no cost to users. We are able to provide free access to data due to financial support from members and data submitters. Dryad's Data Publishing Charges (DPCs) are designed to recover the core costs of curating and preserving data.
Fee waivers are automatically granted for submissions originating from researchers based in countries classified by the World Bank (opens in new window) as low-income or lower-middle-income economies. We’re sensitive to the fact that fees for individual researchers are a burden and create inequities. To better accommodate researchers who lack funds to pay the fee for any reason, beyond and including their geographic location, we’ve expanded our waiver policy so that any author may request one by contacting us.
The base DPC per data submission is $150 USD. DPCs are invoiced upon curator approval/publication, unless the submitter is based at a member institution (determined by login credentials), an associated journal or publisher has an agreement with Dryad to sponsor the DPC, or the submitter is based in a fee-waiver country (see above).
For submissions without a sponsor or waiver, Dryad charges excess storage fees for data totaling over 50GB. For data packages in excess of 50GB, submitters will be charged $50 for each additional 10GB, or part thereof (submissions between 50 and 60GB = $50 USD, between 60 and 70GB = $100 USD, and so on).