Deposit your data

Before archiving your data in DataverseNO, we recommend you to read the following introduction on how to register and upload your data. For general information about research data management, please see the support services of your home institution.

By using DataverseNO you confirm that you have read and agree to the DataverseNO Deposit Agreement.

Step 1: Create a user account / Log in

Feide users

  • Go to DataverseNO, and click on Log In (in the upper right hand corner). In the log-in section Your Institution, select Feide – Norwegian educational institutions, and click on Continue. In your initial log-in session, you will be asked to grant Feide to forward your user information, and once you have accepted this request, a user account will be created for you in the archive.
  • Note! If your institution is not listed in the log-in menu, please ask the IT user support at your institution to activate Feide log-in for DataverseNO.

Other users

  • If you do not have a Feide account, but still want to use DataverseNO, please register for a user account here.
  • Once we have created a DataverseNO account for you, follow the instructions provided in the email sent to you.

Step 2: Deposit your data

Create a dataset draft

  • Once you have logged in (see step 1), choose the collection in which you are supposed to deposit your data:
    • If you are an employee, student or affiliate at one of the DataverseNO partner institutions, choose the appropriate institutional collection (e.g. UiT Open Research Data)
    • All other users are supposed to choose the top-level collection (DataverseNO).
  • Once you are in the right collection, you can create a dataset draft by clicking on the Add Data button on the right hand side, and choose New Dataset. The Add Data button is only visible if you are in the right collection.

Enter metadata

Information about the various metadata fields can be obtained by placing the cursor on the field names (a roll-over window appears). Here is some more information about some of the fields:

  • Title:
    • Enter a title for your dataset.
    • If your dataset is used in a publication, you may enter the title of the publication, and click on Add “Replication Data for” to Title.
  • Author:
    • Enter your name as you use it in your publications. We recommend you to add your affiliation as well. For entering co-authors, click on the plus button. We also recommend you to add your ORCID (
  • Contact:
    • Enter a contact email address. Also add the name of the contact person or research group/institution.
  • Description:
    • Enter information about the data to be uploaded. Avoid using certain HTML tags and other special characters (e.g. [ or ]). If you need to add paragraphs, add the HTML tags <p> and </p> around each paragraph.
    • If relevant, enter information about the data collection/methodology here.
    • If applicable, also enter the publication abstract. The abstract should be entered into a second description field, which can be added by clicking the plus button to the right. NB! If your article is only submitted and not accepted (yet), DO NOT mention the name of the journal it has been submitted to.
  • Keywords:
    • Information such as the subject area(s) (e.g. morphology or zoology) and the statistical method(s) may be entered into the keyword field.
    • Each keyword needs to be entered separately. Please click the plus button to enter more keywords.
    • Vocabulary and Vocabulary URL are not mandatory and may be left empty.
  • Depositor and Deposit Date:
    • These fields are pre-filled. Do not change them. Deposit Date refers to the date when the dataset first was uploaded to the repository.

Confirm/specify data license and attribution

Note that the default license for reuse of data archived in DataverseNO is Creative Commons Zero (CC0); see the Terms tab. CC0 provide maximal reuse and visibility of your data, but implies also that there are no restrictions on reuse of your data. However, as is also stated in the Terms tab, good scientific practice entails that proper credit is given via citation. In case the CC0 license is not suitable for your data, please contact the support services at your institution.

Upload data files

  • Before uploading your data, we strongly advise you to store and document your data according to best practice. Please refer to the section Prepare your data in our Deposit Guide.
  • To keep the folder structure of your dataset, you have to pack the folders and single files into a container file (.zip). How-to (in Windows): Open Windows File Explorer; open the folder that contains all the folders and files of your dataset; select all (Ctrl+A); right-click, and select 7-zip followed by Add to in “”. Then you upload this container file; see next bullet point.
  • Click on Select Files to Add and choose your files from your computer or server space. You may select multiple files using Shift + arrow keys or Ctrl + mouse click.
  • When you have uploaded all the files in your dataset, click on Save Dataset. A draft of your dataset will be saved.
  • Note! If your dataset contains a lot of files, it is convenient to place the ReadMe file on top of the file list. To achieve this, you can add an initial zero to the file name, e.g. “0_ReadMe.txt”.

(Enter more metadata)

Once your dataset draft has been created, you are encouraged to add more metadata to it.

  • Select the Files or Metadata tab in order to add metadata to your files or to the entire dataset, respectively.
  • Most datasets are related to (a) geographical location(s), and we recommend you to add geographical information in the section Geospatial Metadata at the bottom of the metadata schema.
  • In addition, we recommend you to add any relevant domain-specific metadata in the meta data sections following Geospatial Metadata.

(Specify file embargo)

DataverseNO is a repository for open data. This means that all uploaded files must be made openly available. However, you may restrict access to (some of) your files for a period. During this embargo period the selected files will not be accessible, but the metadata about your dataset will be visible. In order to restrict access to a file, follow these steps:

  • Upload the file (see the step Upload data files above).
  • Select the file by checking the box to the left of the file name.
  • Click on the Edit files button above the file section to the right, and choose Restrict.
  • When you have restricted all necessary files, click on Save Dataset, and enter the terms of access in the pop-up window. Check the box Request Access if you want users to be able to contact you for requesting access. Click Continue.
  • Select the file(s) once again by checking the box to the left of the file name(s).
  • Click on the Edit files button above the file section to the right, and choose Tags. Enter into the Custom File Tag field: “Not available until YYYY-MM-DD”. Click on Apply and Save Changes.
  • Specify the date for when your file(s) will be made accessible using the metadata field Distribution Date (see the step Enter more metadata above).

Step 3: Get your data published

  • Your dataset is still only a draft, and you still may change or delete it. If you would like to grant someone (e.g. a collaborator or a journal editor) access to the unpublished dataset, please contact the support services of your home institution.
  • Once you have entered all the necessary metadata and uploaded all the data files needed, and your are ready to get it published, click on Submit for Review. You will receive a notification from DataverseNO that your dataset is submitted.
  • Once a curator from your archive has approved your submission, you will be notified, and the dataset will be published and searchable open access.
  • If needed, you can modify metadata and/or data files after publication. This will create a new version of the dataset, which needs to be approved by a curator from your archive, so remember to submit new versions for review. Note that previous versions are not deleted but archived open access.
  • NB! Please note also that once a dataset is published, it is NOT possible to delete it. However, in certain cases, the dataset can be deaccessed, which means that the data files no longer are openly available. But information about the dataset (author, title, description etc.) will still be visible. For deaccessing, please contact the support services of your home institution.

For questions, comments or suggestions, see our support services.

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