Data Availability Statements are included in publications to describe where the data associated with the paper is available, and under what conditions the data can be accessed. They are required by many funders and journals.
|Availability of data||Template for data availability statement|
|Data openly available in a public repository (that supports FAIR principles) that issues datasets with DOIs under open licence (e.g. CC0)||The data that support the findings of this study are openly available in [repository name e.g “figshare” at http://doi.org/[doi], reference number [reference number].|
|Data openly available under open licence (e.g. CC0) in a public repository (that supports FAIR principles) that does not issue DOIs||The data that support the findings of this study are openly available in [repository name] [check finder tool] at [URL], reference number [reference number].|
|Data derived from public domain resources||The data that support the findings of this study are available in [repository name] at [URL/DOI], reference number [reference number]. These data were derived from the following resources available in the public domain: [list resources and URLs]|
|Data sharing not applicable – no new data generated||Data sharing is not applicable to this article as no new data were created or analyzed in this study.|
|Data not available due to [ethical/legal/commercial] restrictions||Due to the nature of this research, participants of this study did not agree for their data to be shared publicly, so supporting data is not available.|
Source: Taylor and Francis
Datasets are increasingly being recognized as scholarly products in their own right, and as such, are now being submitted for standalone publication. In many cases, the greatest value of a dataset lies in sharing it, not necessarily in providing interpretation or analysis. Data papers thoroughly describe datasets, and do not usually include any interpretation or discussion. Data papers facilitate the sharing of data in a standardized framework that provides value, impact, and recognition for authors. Data papers also provide much more thorough context and description than datasets that are simply deposited to a repository (which may have very minimal metadata requirements). Data papers typically go through a peer review process in the same manner as articles, but being new to scientific practice, the quality and scope of the process is variable across publishers. Data papers serve a different purpose to data repositories. Usually data journals do not store data in-house; instead, a data paper will include directions on how to access the data set.
Adapted from: Oregon State Libraries
This database contains descriptions of and links to Publisher and Publication data management, sharing, and availability policies. Use the dropdown to find the journal you are interested in.
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