FAQs

How does EDX address data security?

  • EDX uses a tiered approach to data security.
  • Private and Semi-Private data is organized in workspaces.
  • Public data is organized in submissions and is accessible to registered and unregistered users.
  • All data resources contain a data license.
  • All published submissions contain a data citation.
  • EDX is not recommended for classified data.

Does EDX have a user registration review process?

Yes, EDX has 2 separate user review workflows.

  • Registrants who register with a .GOV email address obtain immediate inclusion as soon as they click on the validation link sent to their .GOV email address.
  • Registrants who register with a non-.GOV email address must list an NETL POC that can verify that they are actively engaged in NETL/FECM funded research. If the NETL POC approves the account the registrant will receive an email from EDX with a validation link.  As soon as they click on the validation link the account will be activated.

Does EDX have a submission review process?

Yes, EDX has 2 separate submission review workflows.

  • Submissions affiliated with NETL/FECM funded research must be reviewed and approved by an NETL/FECM Project Manager prior to publication,
  • Submissions not affiliated with NETL/FECM funded research must be reviewed and approved by an EDX Reviewer prior to publication.

How often does EDX release new features and functionality?

EDX has periodic version releases (typically every month) that provide new features, functionality, and security patches.

If you have a feature enhancement that you would like to suggest please contact edxsupport@netl.doe.gov

What’s a DOI and what should I know about citing datasets?

Data citation is analogous to the citation of any other published work. Cite the dataset (and software) supporting your research using a standard citation in the reference section of your published work. This gives credit to the data authors and make research datasets findable and accessible.

Most journals now provide standards for how to cite datasets (e.g. and most data repositories automatically generate a citation when a dataset is published, which includes the data authors, the repository where the data are archived, and a persistent identifier, most often a digital object identifier (DOI).

A DOI is a unique string of numbers, letters, and symbols assigned by a central non-profit registration agency to provide a persistent link to the location of content (such as a paper or dataset) on the Internet. DOIs are standardized by the International Organization for Standardization (ISO) and are used to unambiguously identify (and access) published content, usually by resolving to a URL.

You have likely seen DOIs in the references of journal articles, probably in the form of a url, e.g. https://doi.org/10.1000/182, though they can also be found in the form of “doi:” followed by the alphanumeric identifier, e.g. doi:10.1000/182

DOIs are a widely, internationally adopted way to provide persistent, unambiguous links to content online and should be included when citing datasets.

The Joint Declaration of Data Citation Principles provides general guidance on why data citation is important and how it is defined.

You can also find more information, including specific examples of how to cite datasets, here: https://libguides.princeton.edu/citingdata

If you have any questions that aren’t answered here, please contact edxsupport@netl.doe.gov.