Frequently Asked Questions

What's the difference between a Dataset and a Dataverse?

A Dataverse is like a bucket (container) which can have other Dataverses or Datasets in it. Meanwhile, a Dataset must reside inside a Dataverse (for example, the Scholars Portal Dataverse or the CU Dataverse). A Dataset contains files and metadata about those files.

How do I create a new account?

In order to create an account, you need to go to the Scholars Portal webpage: https://dataverse.scholarsportal.info

In the top right corner, click Login. From there, you can choose to Sign Up and make a new account. More information on this process can be found on our Getting Started guide.

I can't find the "+Add Data" button. Help!

The most likely reason why you can't find the Add Data button is because you are in the Scholars Portal Dataverse and not the Carleton University Dataverse. To get to the Carleton University Dataverse, scroll to the left or right of the university buttons shown at the top of the page, and then click on Carleton University once you see it. If you still cannot see the Add Data button once you're in the Carleton University Dataverse, please contact us at dataverse@library.carleton.ca

What is Tabular Ingest?

Tabular ingest extracts data from a tabular file that you upload and archives it in an application-neutral and easily readable format. It does not harm the original file that you uploaded and users can still download the file in its original format. By converting the files to TAB-delimited files, the tabular ingest simply allows the files to be read and used in the Dataverse Explorer tool.

It says "Tabular Ingest Failed." What does that mean? Is my data ok?

For tabular file types (e.g., Excel, csv, SPSS, etc), Dataverse tries to produce a non-proprietary format (tab-delimited) as part of its tabular ingest process. Users can still download the original format, in addition to this derivative file. More details can be found here: http://guides.dataverse.org/en/latest/user/tabulardataingest/ingestprocess.html

The tabular ingest can fail for a number of reasons. Common issues include commas within the cells. If the data is a text string, you could wrap the text in quotation marks. If you would like us to look at it in more detail, you could send us the name of the dataset. However, you can also ignore the error. The file will still be downloadable by other users as is, and users won't be able to see the caution symbol (viewable only by admins/curators/contributors of the dataset). Just so you know, if Dataverse cannot convert it into a .tab file, it won't be able to be used with the Data Explorer or the Data Curation tool, for example.

What should I do if my file size is more than 2.5 GB?

If you have data files larger than 2.5 GBs, there are a few options available.

If possible, you can zip the files to reduce their size. Or if you have a tabular file, consider breaking it into multiple files each less than the 2.5 GB limit. If you take this route, make sure to upload a ReadMe file explaining what you've done.

If those options don't fit for your dataset, you may need to look into other data repositories such as FRDR. Please contact us for more information at dataverse@library.carleton.ca

What does "Submit for Review" mean?

When your dataset is done; your files are uploaded, your metadata is all entered correctly, and you're ready to show it off to the public, you will need to click the Submit for Review button. Prior to this point, everything that you've done has only been visible to you and the Dataverse admins. No one else is able to view your unpublished dataset. Once you submit your dataset for review, CU Data Services will be notified to review the dataset before they decide to either "Publish" the dataset or "Return to Author".

Can I make my data visible to only a few people or no one?

Yes you can. You can set files to be restricted and you can change your restrictions to allow specific users to access your files. If you would like to restrict files or are working with sensitive data, we suggest contacting us at dataverse@library.carleton.ca. Then we can help you set up your dataset the best way possible.

What is FRDR?

FRDR (Federated Research Data Repository) has 2 main purposes.
First, it is used as a data repository for large datasets. If you are a researcher affiliated with a Canadian institution, you are able to deposit your large dataset into FRDR knowing that it will be preserved.
Second, FRDR can be used as a search tool to discover datasets in other repositories across Canada.

More FAQ?

Check out the Scholar's Portal Dataverse FAQ

Content last reviewed: May 7, 2021