Open data are freely and publicly available data structured in a way to be fully accessible and usable, without copyright, patents or control. This is important because data that is open, available, and accessible will help spur innovation and inform how agencies should evolve their programs to better meet the public's needs.The Open, Public, Electronic, and Necessary Government Data Act or the OPEN Government Data Act requires federal agencies to publish their information as open data using standardized, non-proprietary formats. In order to meet the guidelines set forth in the US Government Open Data Initiative and data management requirements set forth by DOE, you may be asked to deposit your data in an open access data repository.
Data Repositories help you:
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Where possible, we seek to adhere to the FAIR principles for scientific data management and stewardship. These principles promote the ideas of managing data so that it is fully contextualized, allowing the raw data to be easily used and reused. The FAIR principles are:
LANL researchers' deposit their data in a variety of places: domain-specific data repositories, general purpose data repositories, and DOE-specific Institutional data repositories. The value of these repositories are in the availability and familiarity with researchers within the discipline and the subject specific metadata searching capabilities and ontologies.General repositories are often recommended by publishers as well as granting agencies for the deposit of data related to research studies. Some recommended open repositories include:
Compare recommended repositories to each other in the LANL Data Repositories Matrix.
There are many ways to share your data openly and freely in open data repositories, which can be found via re3data, a registry of research data repositories). You can search the re3data.org to find appropriate academic discipline repositories.
Below are a selection of DOE and NNSA data repositories:
Data journals bring data publishing into the mainstream of scholarly communication, since data reports are authored, published, indexed, cited and used in much the same way as conventional journal articles. The purpose of a data journal is to provide quick access to high-quality datasets that are of broad interest to the scientific community. They are intended to facilitate reuse of the dataset, which increases its original value and impact, and speeds the pace of research by avoiding unintentional duplication of effort.
Data papers within these journals are typically peer-reviewed in the same manner as articles, providing authorship credit for journal articles, and can accumulate citations just like traditional journal articles, While the field of data papers continues to evolve, the datasets presented in data papers include much more description than datasets deposited to a repository, even if those datasets were deposited to support a manuscript. There is a growing list of data journals, but the most known are:
Walters, W. H. (2020). Data journals: incentivizing data access and documentation within the scholarly communication system. Insights, 33(1), 18. DOI: http://doi.org/10.1629/uksg.510