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See if they have preferences, conventions, or advice for https://dataverse.org/, or something similar.
From what I've read so far, the data citation documentation seems to be more suited for repositories of original datasources that the research collects, as opposed to derivative datasources, like our NLSY Kinship links.
The archived applied papers can have datasets (like this one), but I don't see an explicit link back to the original BLS source. That example has a README file that gives credit to the NLSY, but I don't see anything special in the structured metadata that could help with metrics of NLSY popularity.
@smasongarrison, I cc'd you on my recent email to them. Have you done anything like this?
The text was updated successfully, but these errors were encountered:
See if they have preferences, conventions, or advice for https://dataverse.org/, or something similar.
From what I've read so far, the data citation documentation seems to be more suited for repositories of original datasources that the research collects, as opposed to derivative datasources, like our NLSY Kinship links.
The archived applied papers can have datasets (like this one), but I don't see an explicit link back to the original BLS source. That example has a README file that gives credit to the NLSY, but I don't see anything special in the structured metadata that could help with metrics of NLSY popularity.
@smasongarrison, I cc'd you on my recent email to them. Have you done anything like this?
The text was updated successfully, but these errors were encountered: