Repository:
Authors can deposit their research and data in any public repository that meets archiving, citation, and curation standards through the repository. These repositories store data in its native form, allowing for optimal analysis, verification, and reuse.
Authors should deposit their research and data in public repositories that meet archiving, citation, and curation standards. Recommended repositories, but not limited to, such as Figshare, Zenodo, and Dryad Digital. The chosen repository should be anonymous, allow access to data, be stable, and be suitable for all researchers. Data must be deposited in a repository before article submission. If not, it can be uploaded during submission.
The Indian Journal of Artificial Intelligence and Neural Networking (IJAINN) recommends repositories, but not limited to, such as Figshare, Zenodo, and Dryad Digital, to aid in disseminating research. Authors ensure that the repository used for the peer-review process is anonymous, provides access to data, preserves resources, is stable, and is suitable for all researchers with the appropriate data types.
Authors must deposit their data into the repository as a part of the article submission process to the Indian Journal of Artificial Intelligence and Neural Networking (IJAINN). If data has yet to be deposited to the repository before the article submission, it can be uploaded to Figshare or Dryad Digital during submission.
References: