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 repository.
  • 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)
    • If you are a linguist and have got access to TROLLing, choose TROLLing (
    • 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. Instead of “Replication Data for” you may use “Background Data for”, “Supporting Data for” or another suitable suffix.
  • 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.
  • Keyword:
    • 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.
  • Related Publication:
    • If the files you are depositing are the background data for a publication, you should include a reference to the publication here.
    • Note! If your manuscript has been submitted for review but has not yet been accepted, DO NOT list the name of the journal or publisher. Instead you may simply write “Submitted for review” or similar.
    • Note! If the review of your manuscript is going to be double blind (both author and reviewer are anonymous), you must add a note about it in the Related Publication field. This way, the curators can assist you in anonymizing the dataset.
    • (When adding more than one publication, only the first of them will be visible on the overview page of the dataset. If you don’t want to highlight any of the publications in this way, you may add the following text in the first publication field: “Click Metadata tab below to see related publication(s).” This text will show up on the overview page, and to see the actual publications, user will have to click the Metadata tab.)
  • 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 legal restrictions on reuse of your data. However, as is also stated in the Terms tab, good scientific practice and basic research-ethical principles entail 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.
  • A single dataset should not contain more than 200-300 files. If you need to deposit more files, you may opt for one of these alternatives:
    • Pack the files into one or more (max. 200-300) container files.
    • Distribute your data files across multiple (sub-)datasets.
  • For container files, please adhere to the following recommendations:
    • Create archives (container files) only with extensions .zip or .tar (do not use .7z, tar.gz, .rar, and so on).
    • Do not use archives within your ZIP or tar files, except for double-zipped zip files to maintain the folder structure of your dataset; see below.
    • Please create your archives without any data compression (compression level “store”)
    • Avoid encrypting your files with a password.
  • DataverseNO has no upper size limit for a dataset. However, below are some advices and procedures for handling uploads of large files. The following advice, size limits and procedures apply to single files, file uploads and datasets:
    • The size of individual files should not exceed 5 GB. Bigger files can create problems for others when it comes to downloading and reusing data.
    • A file upload should not exceed 10 GB in total size to minimize the likelihood that errors will occur when transmitting data over the Internet Protocol (http).
  • If you are not able to upload your data according to the guidelines above, or if your dataset exceeds 50 GB, contact the support services of your home institution for more information about how to upload the data.
  • 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. The zip file will be unpacked during upload, and the folders (and sub-folders) in the zip file will be uploaded with their respective folder names. Note! If your dataset contains very many files (several hundreds) we recommend you to deposit them as zip files. Such zip files will need to be zipped once more in order for the “inner” zip file to be retained during upload The name of the “outer” zip doesn’t matter as it will be unpacked during upload.
  • 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”.
  • Note 2! If you have kept your folder structure by uploading a zip file, you need to select Tree View to be able to see the folder structure: Click the Tree button to the right of Change View on top of the file overview.

Enter more metadata

Once you have created a dataset draft, we recommend that enter more information about the dataset. This will increase the chance of others being able to discover your data and interpreting and reusing it correctly.

Select the Metadata tab and click the Add + Edit Metadata button. To the extent applicable, we recommend that you enter information in the fields below. When you are finished, click the Save Changes button at the bottom of the page.


  • Language:
    • Select the language you have used to describe your data. Often this will be English.
  • Contributor:
    • Here you should credit those who have contributed to the dataset, including those who are not to be listed as authors. In the Type field you can choose what role they have had (e.g. Data Collector).
  • Grant Information:
    • Note! Important information about possible funding. Use the full name of the funder, e.g. “The Research Council of Norway”.
  • Time Period Covered:
    • What time period is the data from or about?
  • Date of Collection:
    • When was the data collected / generated?
  • Kind of Data
    • What kind of data is it? Hover your mouse over the question mark to the right of the field name, and you will see some suggestions, e.g. survey data, experimental data, observation data.
  • Related Material:
    • Material related to the dataset.
  • Related Datasets:
    • Other data sets related to the dataset. This may be your own or others’ data sets. If available, use full reference, including persistent identifier (e.g. DOI).
  • Data Sources:
    • If you have not generated or collected the data yourself, enter information here about your sources. This can for example be an archive, a corpus, or a website from which you downloaded the data.


Many datasets are related to one or more geographical locations. Entering geographical information in this section will make your dataset more discoverable in search engines that use a geographical entrance point, e.g. a map. You can specify a geographic location under Geographic Coverage, and / or enter coordinates under Geographic Bounding Box. A geographical point has the same value for West Longitude and East Longitude, and the same value for North Latitude and South Latitude. A box, on the other hand, has four different values ​​in these fields. The values ​​must be specified as decimal degrees. For example, mainland Norway has these values: West Longitude: 4.09; East Longitude: 31.76; North Latitude: 71.38; South Latitude: 57.76. Note: Use period (“.”) as decimal separator, not comma. The value for West Longitude must be lower than the value for East Longitude. The value for South Latitude must be lower than the value for North Latitude.


In addition, we encourage you to register domain-specific metadata where applicable. Currently, there are three domain-specific metadata schemas  in DataverseNO:

  • Social Science and Humanities Metadata
  • Astronomy and Astrophysics Metadata
  • Life Sciences 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. Even if the dataset is at the draft stage, it has been given a valid DOI, which will be the same also when the dataset is finally published, but the DOI will not be activated and work until after the dataset is published. Note! If, after the curation (see below), it turns out that the dataset cannot be published in DataverseNO, the dataset will be deleted and the DOI will never be activated. It is therefore important that you do not use the dataset reference until the dataset has been curated and approved for publication in DataverseNO. More information about how to cite research data can be found in the section Refer to your data.
  • Once you have entered all the necessary metadata and uploaded all the data files needed, and your are ready to get it published, click the Submit for Review button. You will receive a notification from DataverseNO that your dataset is submitted.
  • A curator from your institutional collection will review your dataset and if necessary inform you about possible changes to be done before publication. Once the curator has approved your submission, you will be notified, and once you have given the go-ahead to the curator, the curator will publish the dataset and it will be searchable and accessible on the Internet.
  • 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 institutional collection, 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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