RDMC UNC Dataverse: Quick Guide

This article describes how to perform common functions in UNC Dataverse. It is designed as a reference for all UNC Dataverse users.

 

In this article:

• Getting Started
  • Create an Account
• Navigating the Dataverse
  • The User Dashboard
  • Search and Browse
  • Understand and Leverage Metadata
  • Request Access to Restricted Data
• Creating a Dataverse
  • Create Your Dataverse
  • Customize Your Dataverse
  • Grant Permissions
  • Create Groups
• Creating a Dataset
  • Create a New Dataset
  • Manage Access Controls
  • Publish Your Dataset
• Using Dataverse Metrics
  • Use Built-In Dataverse Metrics
  • Use Dataverse API Metrics
  • Use Guestbooks
• Deleting or Deaccessioning a Published Dataset
  • Delete a Draft Dataverse
  • Delete a Draft Dataset
  • Deaccession a Published Dataset
• Advanced Features
  • Featured Dataverses
  • Submit for Review

 

 

Getting Started

Create an Account

If you are a first-time UNC Dataverse user, you will need to create an account using: 1) your UNC Onyen, 2) your institutional credentials from any institution that uses Shibboleth single sign-on (SSO), or 3) your ORCID.

To create your UNC Dataverse account via ONYEN or institutional credentials that uses Shibboleth single sign-on (SSO):

1. Visit UNC Dataverse. https://dataverse.unc.edu/
2. Click on the Log In link in the main navigation menu.
3. Select University of North Carolina at Chapel Hill [or your institution name] in the drop down list.
4. Enter your user name and password in the single sign-on application.
5. Review and agree to the UNC Dataverse Terms of Use.
6. You can now log in to UNC Dataverse using your institution’s single sign-on.

If you do not see your institution in the dropdown menu and you know it uses Shibboleth SSO, contact your university’s identity management team (usually part of ITS) and ask them to do one of the following:   

• offer the "Research and Scholarship Attribute Set" to all Shibboleth service providers, or
• explicitly share the attribute set with UNC Dataverse.

If your institution does not use Shibboleth SSO and you have an ORCID, you can create an account with your ORCID:

1. Visit UNC Dataverse. https://dataverse.unc.edu/
2. Click on the Log In link in the main navigation menu.
3. Select ORCID at the bottom of the Login page.
4. Enter your ORCID user name and password.
5. Grant UNC Dataverse permission to use ORCID.
6. Complete UNC Dataverse account information
7. Review and agree to the UNC Dataverse Terms of Use.
8. You can now log in to UNC Dataverse using your ORCID.

If you cannot login via your institution's Shibboleth Single Sign On (SSO) or ORCID, please see our New User Permissions page.

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Navigating the Dataverse

In this Section:

• The User Dashboard
• Search and Browse
• Understand and Leverage Metadata
• Request Access to Restricted Data

The User Dashboard

The User Dashboard (the dropdown menu below your username at the top right of the page) allows you to access your account information, dataset records, and notifications, and generate API tokens.

Account Information 

This section displays your account information. If you are using an Institutional login, account information is not editable.

If you are leaving your institution and would like to transfer your account, please contact UNC Dataverse Support.

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My Data

The My Data tab displays a list of all dataverse collections, datasets, and files that you own or have permissions to access. You can search through the list by keyword or using the filters on the left side of the page.

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Notifications

Notifications appear here. Each includes a link to the dataset record and the dataverse it refers to, and each includes the date the notification was sent. Remove notifications by clicking the "x" in the upper right of each notification box.

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API Token

This tab allows you to generate an API token to access the Dataverse application's APIs. API tokens are valid for one year. Review the Dataverse API Guide (v5.9) for more information on available APIs and their functions.

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Search and Browse

A dataverse is a collection that can hold datasets and/or other dataverse collections. You can think of it as a file folder that can contain files or other folders. 

To locate datasets or accessible dataverses, you can search the UNC Dataverse using either basic or advanced search.

Basic search: In the basic search bar above the results list on the main page, enter keywords and click "Find."

Advanced search: To narrow down your results, click "Advanced Search" beside the basic search bar. You will be redirected to a new search page. Enter as many keywords as you like as you like into as many variable fields as you like and click "Find." Your results will load in a new UNC Dataverse page. 

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Facets

Facets are specific terms used to filter the results in the UNC Dataverse results list. Facets appear on the far left of the main page. Clicking on a facet will narrow the results list to show only results related to the selected facet. To remove a facet from your search, navigate to the top of the results list and click the "x" beside the facet label.

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Refine the Results List

Your results list appears in the middle of the UNC Dataverse main page. The list automatically updates whenever you perform a search or add/remove a facet. You can sort the list by clicking on the "Sort" button to the right. The list contains only published dataverses, datasets, and files. (Admins, curators, or contributors of unpublished draft dataverses or datasets may also see those in the results list.)

 

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Understand and Leverage Metadata

Metadata is information provided along with data files that helps you understand the content and structure of the data and the context of the research project that produced the data. Good metadata answers the questions of who, what, when, why, where, and how of the data. Metadata is critical in searching and discovering of new datasets, deciding whether a data file will answer a research question, evaluating whether analysis and reuse is appropriate, and making data FAIR. 

Each dataverse contains dataset records that provide metadata about the data files, documents, and/or code housed within that record. If a dataverse collection is like a folder that contains files and other folders, you might think of the dataset record as an index card stapled to the folder giving information about the folder's contents. Before you access files, review the dataset record completely to ensure that you understand what it contains and that you are complying with the terms of use.  

Each dataset record is comprised of standardized metadata fields. UNC Dataverse requires specific metadata fields to be populated before a dataset record can be published. These required metadata fields are part of the citation metadata. Required information in the citation metadata block includes Author(s), Title, Date, Repository, Version, and DOI (the dataset's persistent URL).

You can export a data citation from the citation metadata block by selecting Cite Dataset and choosing an export format from the dropdown menu.

 

There are other types of metadata blocks that appear in other dataset records. (If a dataverse is like a folder, these additional dataset records are like additional index cards stapled to that file or folder giving more information about what the folder contains.) For example, there are geospatial information metadata blocks and domain-specific metadata blocks that include information about location of data collection, methodology, modes of analysis, sample size, dates of collection, etc.

Any information entered in domain-specific metadata fields is automatically included in basic search results in UNC Dataverse; advanced search  allows users to narrow their search across these specific fields.

File-level metadata may be included for each individual file. Unlike the domain-specific metadata fields, which describe the entire dataset record, file-level metadata describes the contents of a specific file. (These are like index cards stapled to specific pieces of paper within the file folder.) In the domain-specific metadata fields, a user may find information about how the study was conducted; from the file-level metadata, they may learn the contents of "PFHHP2.tab." 

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Accessing and Downloading Files

All data files provided by a particular data producer are listed under the Files tab of the dataset record. (Any file-level metadata provided by the data producer also appears here.) UNC Dataverse automatically provides certain information about each file within the dataset record, including file type, file size, number of downloads, and an MD5 checksum. Files are listed in alphabetical order by default, but you can click the Sort button to sort in other ways (by newest, oldest, type, size, or Z-A).

To download a single file, click the arrow icon to the right of the filename. Select an option from the "Download options" section of the dropdown menu. We generally recommend that you download the file in its original file format. However, for some original file formats, UNC Dataverse creates preservation formats that make alternative file formats available for download. These alternative file formats are useful if you do not have access to the statistical software required by the original file format. 

To download multiple files within a dataset record, click on the checkbox next to the desired files. If you want to download all files in a dataset record, click the checkbox at the top of the file list and click "Select all # files in this dataset." Next, click the "Download" dropdown menu at the top right of the files list. Choose your desired format (original or, if necessary, an alternative format). UNC Dataverse will create a zip file that includes all the files you selected within that record. 

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Terms of Use and Licensing

Each published dataset record will have a license and/or terms of use that defines what users may do with the contents of that record. There are four different license options and a custom terms, where a data producers writes their own terms of use and requirements. See license options in the Edit License and Terms of Use section.

Each dataset record may also have its own customized terms of use, chosen by the dataset owner. A license and custom terms of use can both be in force for the same dataset record.

Some dataset records use the default Creative Commons CC0 license and have no additional terms of use; however, you should still cite any data sources you use in your own research or publications. To learn more about licensing and data citations, please visit the Dataverse Community Norms. 

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Versions

Every dataset records contains a Versions tab that lists all published versions of a dataset, with information describing how each version differs from its predecessor. This version history tracks changes to dataset records over time, ranging from updates to metadata fields to deletion of obsolete files and upload of new files. The version history also notes the date each new version was published and the entity that published the new version.

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Data Explorer

The Data Explorer is a feature of UNC Dataverse that allows users to browse publicly available data files in certain formats within the Dataverse platform. Through Data Explorer, users can see every variable within a data file and review summary statistics, create cross tabulations, and download subsets from that file.  

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Document Previewer

UNC Dataverse has a built-in document previewer. This feature allows users to read through TXT and PDFs within the Dataverse platform. Simply navigate to the text document you wish to preview, click the download icon, and choose "Read document" from the dropdown menu.

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Request Access to Restricted Data

Contact the Dataset Owner

If you have questions about the contents or availability of the data in a particular dataset, you can contact the dataset owner and ask. All dataset records within UNC Dataverse have a "Contact owner" button. Click the button and a pop-up appears on the page, allowing you to write a message and send it to the dataset owner. The dataset owner will receive the inquiry both in a notification in UNC Dataverse and in their account email.

Some data will not be immediately accessible via the UNC Dataverse platform. These restricted files have a red lock icon beside the file image within the dataset record. Instead of a download option, users will be able to "request access" to a restricted file.

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Request Access to Restricted Data

Clicking the "Request access" button brings up a form for you to fill in to submit a request to the data owner. The data owner will be notified both via notification in UNC Dataverse and via email, and they can grant or deny the access request.

When a data owner has granted you permission to access their data, you will receive an email from UNC Dataverse indicating the file is available for download. Log back into UNC Dataverse and navigate to the file via either the link provided in the email or the Notifications tab under your User Dashboard. 

User permissions may be revoked at any time by the data owner.

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Creating a Dataverse

In this section:

• Create Your Dataverse
• Customize Your Dataverse
• Grant Permissions
• Create Groups

Create Your Dataverse

To create a project dataverse in UNC Dataverse, first log in to UNC Dataverse. Scroll down to the "Add Data" button on the main page. Select "New Dataverse."


This takes you to a New Dataverse page, where you will fill in the following required information:

• Dataverse name
• Identifier (the shortname used for the URL of the dataverse)
• Category 
• Email  

You can also provide a description of the dataverse to help users understand the contents and purpose of your dataverse.

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Choose Metadata Fields

In the Metadata Fields section, you can choose which metadata fields to include when creating a dataset within your dataverse. You may choose the default "Use metadata fields from UNC Dataverse" or select one or more of the metadata option(s) listed. If you are not sure which metadata option is most appropriate, you can click the "[+] View fields" button to see what each metadata option includes. 

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Add/Remove Search Facets

As the administrator of your project dataverse, you determine which facets appear on the left side of your dataverse main page. The facets allow users to refine their results lists and can help them locate the most relevant datasets, sub-dataverses, or files within your project dataverse.  

The "Use browse/search facets from UNC Dataverse" is enabled by default, but you may deselect this option and choose custom facets from the list underneath that default option.

To add a facet, select the desired facet(s) in the list on the left and then click the right arrow [→] to move it to the "Selected" list. The selected facets will now show up on the left side of your dataverse.

To remove a facet, click on the facet under the "Selected" list and then select the left arrow [←] to remove it from the "Selected" list.

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Publish Your Dataverse

Once you have added all the necessary information and selected your metadata and facet customizations, click the "Create dataverse" button. To share the data that is in your dataverse, click "Publish" on the main page of your dataverse.

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Customize Your Dataverse

You may customize your project dataverse by selecting the Edit tab and choosing customizations from the dropdown menu. Customizations include setting permissions levels, assigning roles to  users or groups, adding design elements such as logos and project links, developing dataset templates, and creating guestbooks to track user metrics.

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General Information

On the General Information page, dataverse admins can update the description of their dataverse, change the contact information, and make changes to the metadata and facet selections that will display on their dataverse page. You can return to this page at any time to make updates as needed.

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Theme and Widgets

Admins may customize the look of their project dataverse using the Theme and Widgets interface.

From the Themes tab, you can upload a logo for your project dataverse, choose colors (background colors, link colors, and text colors for the header), include a tagline and URL to a project website, and add a footer image. This helps brand your project dataverse and differentiate it from the UNC Dataverse.
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The Widgets tab provides HTML code that you can embed within your project website. Select the "Dataverse Search Box HTML" code to generate an embedded search box in your website that links back to results in your project dataverse; select the "Dataverse Listing HTML code" to embed your project dataverse results list within your website. This is another useful mechanism for branding your project dataverse and making it more accessible to users exploring your project website.

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Grant Permissions

Dataverse allows admins to set permission and access levels to limit how users may interact with their project dataverse. Permission levels may be changed at any time.

To edit permissions, select "Edit Access" under the Permissions section. You will be prompted to answer two questions in the pop-up window. Together, these two questions determine what roles will be assigned to users who can create or contribute content.

1. "Who can add to this dataverse?"
   1. Anyone adding to this dataverse needs to be given access.
   2. Anyone with a Dataverse account can add sub-dataverses.
   3. Anyone with a Dataverse account can add datasets.
   4. Anyone with a Dataverse account can add sub-dataverses and datasets.
2. "When a user adds a new dataset to this dataverse, which role should be automatically assigned to them on that dataset?"
   1. Contributors (recommended for those who chose Option 3 above)
   2. Curators (recommended for those who chose Option 1 above)

Contributors can edit metadata, upload files, and edit files, edit Terms and Conditions, enable a guestbook, and submit their datasets for review. Contributors can not directly publish a dataset within your dataverse. They submit the dataset for review; an admin or a curator may publish the dataset. 

Curators can edit metadata, upload files, and edit files, edit Terms and Conditions, enable and create a guestbook, enable file restrictions and grant file access, edit permissions, assign roles, and publish a dataset record. Curators can do most things within a dataverse; this role is ideal for project team members who are responsible for sharing data, such as project managers, data archivists, or research assistants.

Once a role is assigned, it can be removed at any time by an admin or curator. 

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Users/Groups Permissions

This section of the Permissions page allows admins and curators to assign and revoke roles to other UNC Dataverse users, granting them the ability to perform certain actions within your project dataverse.

To assign a user a role within your project dataverse, click the "Assign roles to users/groups" button. A pop-up window will appear where you can enter a username into the Users/Groups field.


Find the user or group in the dropdown and select their name. Under Role, select the role that is most appropriate for this user. When you click on a role, UNC Dataverse will provide a description of all actions that role type may take within a dataverse. Once you have decided on the appropriate role, select "Save changes." The pop-up window will disappear, and the Users/Groups section will update to reflect the new user and their assigned role.

To remove a user from Users/Groups and revoke their role, simply locate the user in the Users/Groups section and click on "Remove Assigned Role." The user will no longer have access to the project dataverse.

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Roles Permissions

The final section of the Permissions page is the Roles section. This is a list of all existing roles within a dataverse, describing each action that users with that role may take. We recommend using the existing roles; however, if you are interested in creating a custom role for your dataverse, please submit a help ticket first to ensure that the role will function as intended.

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Create Groups

Groups are a useful way of bundling users to quickly assign or revoke permissions. UNC Dataverse allows admins and curators to create groups through a simple pop-up window in the interface.

Enter the information into the required fields and enter a description, then use the Users/Groups field to locate the individual users or pre-existing groups you’d like to include in your group. Once you’ve added everyone you want, click "Create group." You may now use the Permissions page to assign roles to this group.

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Creating a Dataset

In this section:

• Create a New Dataset
• Manage Access Controls
• Publish Your Dataset

Create a New Dataset

To create a dataset record, navigate to your project dataverse and select the "[+] Add data" button, then select "New dataset" from the dropdown menu. You will be taken to the dataset creation page, where you can provide metadata that describes the contents of your dataset record and upload data, documentation, and code files.

You can also create a new dataset from a dataset template, which allows admins, contributors, and curators the ability to create a new dataset record within their project dataverse using a pre-populated metadata template. This can speed up the dataset record creation process for project dataverses that will house many dataset records with similar metadata. 

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Create a Dataset Template

Dataset templates help you organize and share metadata about your research. In your dataset template, you can pre-populate metadata (e.g., project title and description, funder information) and include naming conventions. Templates are useful when a set of dataset records share the same metadata. 

To create a dataset template, log in to UNC Dataverse and navigate to your project dataverse. Click on Edit in the far right of the page and select "Dataset templates" from the dropdown menu. Select the "[+] Create dataset template" button on the right side of the Dataset Templates page.

 

Before you begin filling the metadata fields in the citation metadata block, you must first name your dataset template in the Template Name field. Enter a name for the template and then continue down the page.

In each field, provide the information or formatting that will be used for multiple dataset records. For example, if your project will have multiple dataset records across different years, but all will share the same title, you would include formatting in the Title field.

Continue down the dataset template page, entering information into the fields that your datasets will share (Subject, Keywords, Related Publications, Producer, Grant Information, etc.)
When you have finished entering the information, click "Save [+] add terms" button at the bottom of the page. This will take you to the Terms of Use (ToU) page, where you can edit your ToU. Once you have finished editing the ToU, click "Save dataset template."

Your new dataset template will appear in the table on the Dataset Templates page; from there, you can view, edit, and delete the template.

To set this dataset template as the default template for future datasets, click the "Make default" button under the Action section of the table. Any new datasets created within your project dataverse will automatically default to this template, although users can deselect the template during dataset creation. 

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Create a New Dataset from a Dataset Template

If a dataset template is enabled within the project dataverse, the dataset creation page will be customized to the specifications of that template. You can see which template you are using at the top of the page. To choose a different template or remove the template entirely, use the dropdown menu under Dataset Template.

If you do not wish to use a dataset template, continue filling out the dataset creation page, including the citation metadata and other metadata blocks.

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Citation Metadata

The Citation Metadata section of the dataset creation page contains the fields required to generate a complete data citation for your dataset record (Title, Author(s), Contact(s), Description, and Subject). Within this block are required metadata fields, denoted by an asterisk. Fill in each of the required fields. If you need additional fields for multiple authors and/or contacts, click the [+] button beside the appropriate field.

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Additional Metadata Blocks

When creating a dataset record for the first time, a limited set of metadata fields is offered. However, UNC Dataverse offers several additional metadata blocks that provide subject-specific metadata fields that follow the metadata standards and practices of your particular research community. These domain-specific metadata blocks include Life Sciences, Geospatial, Social Sciences and Humanities, Astronomy and Astrophysics, and Journal metadata.

You may add these metadata blocks in two ways:

• access Choose Metadata Fields section while you are creating your dataverse, or 
• edit a preexisting dataverse (select "Edit > General information > Edit metadata"). 

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Upload Files

Once you’ve completed your citation metadata, scroll down to the Upload Files section at the bottom of the page. You can either drag and drop files into this section or click the "[+] Select files to add" button to browse. 

Dataverse will show a brief progress bar beside each file while uploading them to the system. As soon as the files are uploaded, the page will display an updated file(s) list; this is where you can add file-level metadata.

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File-level Metadata

Dataverse provides basic metadata about each file: filename and MD5 checksum. An MD5 checksum is a unique hash value that is generated for your file and used to validate the integrity of the file. If a file is changed in any way, the MD5 checksum value will change. Dataverse platform calculates the MD5 value every time a file is uploaded, published and downloaded to ensure the integrity of the file.

You can add description information about your files. Below the file’s MD5, a section labeled Description allows you to enter file-level information about your data or documentation file. For example, you may use this section to clarify the contents within your codebook.

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File Paths

UNC Dataverse can create folders to help keep your files organized within the platform. If you need a folder hierarchy to organize and group certain files, use the File Paths feature.

To create a file path, scroll to the file you want to move to a specific folder. In the File Path field, enter the name of the new folder you want to create for that file to exist within.

When you save the changes, UNC Dataverse will automatically create a folder and place the selected file(s) within it.

You can view your folder organization using the Tree View.

It should look something like this:

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File Tags

Dataverse also allows you to further categorize your files using file tags. Tags are a way to easily denote file types and categories. To select a File Tag for you file, navigate to the triple … button on the far right of the file uploader. From the dropdown menu, select "Tags."

There are three options available under File Tags: data, documentation, and code. Click the checkbox next to the appropriate tag(s). A gray tag with the selected label will appear above the File Tags dropdown.

You can also create custom file tags. Simply type your tag in the custom file tags field and click "Apply." The new tag will appear in the Selected Tags area.

When you’ve finished adding tags to your file, click the "Save changes" button. The gray tag label will appear underneath your file description.

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Save a Draft Dataset

Once you’ve finished adding metadata and uploading your files, click "Save dataset." This will create your new dataset record as a draft for further review and editing. UNC Dataverse sets new dataset records as a draft by default to allow you to customize the record and review its contents before publishing and registering the persistent identifier (DOI).

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Edit Metadata

When you first create your dataset, you will see only a limited range of metadata fields. When you go back into your draft and edit the metadata, you will have access to all available metadata fields, and to additional metadata blocks with subject-specific metadata fields that follow the metadata standards and practices of your particular research community, including Life Sciences, Geospatial, Social Sciences and Humanities, Astronomy and Astrophysics, and Journal metadata.  

Before you publish your record, do a thorough review of the metadata. First, read through the dataset record to make sure that all formatting and existing content is accurate and describes the context of your research data.

To correct errors or add more information, you can edit the metadata.

One way to access the metadata editing field is to click "Edit dataset" in the upper right side of the dataset record page and choose "Metadata" from the dropdown menu. You will be redirected to an expanded metadata record where you can edit and add more information about your dataset.

 

A second way to access the expanded metadata page for editing is to select "Edit files" from the file list section of your dataset record and choose "Metadata" from the dropdown menu.

The extended metadata page will look very similar to the "New dataset" page where you created your draft dataset record; however, if you scroll further down you will now see more metadata fields and options for describing your data and research.

Make any edits and fill in any new metadata fields as needed. The more information you provide, the easier it will be for users to find and understand your research and the contents of your dataset record.

When you have completed your review and edits, scroll to the very bottom of the page and click "Save changes." You will be taken back to the draft dataset record.

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Edit Files

While reviewing your draft dataset record, you may notice missing or erroneously shared files. To add missing files, click on "Edit dataset" in the upper right of the dataset record and select "Files (upload)" from the dropdown.

You will be redirected to the file upload manager where you can select files or drag-and-drop them into the uploader. Once UNC Dataverse has finished uploading the files, you can add file-level metadata as needed. Click "Save changes" when you have finished adding files.

If you need to delete a file, scroll down to the Files tab of the draft dataset record. Click the checkbox beside each file you wish to delete. Select "Edit files" on the far right and choose "Delete."

Note: You may also use this method to edit individual file-level metadata and tags as needed.

 

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Edit License and Terms of Use

A license for your research data enables you to communicate to future users any terms of use or restrictions that apply to your data. Can users modify and/or re-distribute the data? Do users need to re-distribute products from your data under the same license? Licenses range from more restrictive to permissive in what others can do with your data, code, and materials. 

By default, UNC Dataverse assigns all datasets records a Creative Commons CC0 license. However, you can easily customize the license and Terms of Use for each dataset record. UNC Dataverse has the following license options: 

• Creative Commons "No Rights Reserved" License (CC0): https://creativecommons.org/public-domain/cc0/ 
• Creative Commons Attribution 4.0 International License (CC-BY 4.0):  http://creativecommons.org/licenses/by/4.0 
• General Public Version 3 License (GPL v3): https://www.gnu.org/licenses/gpl-3.0.en.html#license-text 
• MIT Open Source License: https://opensource.org/licenses/MIT 
• Custom Terms: Write your own terms of use and requirements

To update the Terms of Use, select a different license, or add usage requirements for your dataset record, please scroll to the bottom of your draft dataset record and click on the "Terms" tab. On the right side of this section, select "Edit Terms of Use."

You will be redirected to the Edit Terms of Use page, where you can remove the CC0 default public domain license and include your own custom terms of use. 

Additional information and conditions for re-use of your data may be included in the metadata fields on the Terms of Use page.

If your data are restricted, please include access request instructions and information in the section labeled "Restricted Files + Terms of Access."

When you have finished updating the Terms of Use, scroll to the bottom of the page and click "Save changes." Your draft will be updated with the new terms. 

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Manage Access Controls for Data

If you need to control access to your research data (for example, if your funding agency or institution requires a data use agreement before sharing data with researchers), UNC Dataverse allows you to restrict access to or embargo data at the file level.

 

Restrict Access to Data

UNC Dataverse offers data access restrictions as part of the data sharing workflow. Restricting data removes the download option from data files and replaces it with a "Request access" button. Users must request access to the data file(s) and be granted permission to download. 

Permission to download may be granted by the dataset record admin or a designated curator. Some dataverse admins require users to also email a completed data use agreement outside of the UNC Dataverse platform.

To restrict access to a data file, navigate to the draft dataset record and scroll down to the Files tab. Select the checkbox next to the file(s) you wish to restrict. On the far right of the page, choose "Edit files" and select "Restrict" from the dropdown menu,

When you click "Restrict," a pop-up window will appear; you can enter specific Terms of Access here.

Click "Save changes."

Your data file(s) is now  restricted. As an admin or curator, you will  see a green lock icon underneath the file in your draft dataset record; when your dataset record is published, users will see a red lock icon, and the download button will be replaced with the "Request access" button.

UNC Dataverse will automatically notify all dataset admin and curators of an access request. You will receive the notification via email, as well as in the Notifications section of your UNC Dataverse User Dashboard. Follow the link provided in the email message, or the link provided in the user dashboard, to grant or deny the request.

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Grant Permissions to Restricted Data

When a user requests access to restricted data, UNC Dataverse sends the dataset admin and curator(s) an email notification of the request. To approve a data access request, navigate to the Permissions page. The link provided in the email from UNC Dataverse will take you there, or you can log in to UNC Dataverse, click on your account in the upper right, scroll down to "Notifications," and select the link to the request in your notifications list.

If neither of these methods works, locate the dataset within your project dataverse, click on the dataset record, select "Edit dataset," and choose "Permissions > File" from the dropdown menu.

This will take you to the Users/Groups Access Restrictions management page. This displays the list of users requesting access, with buttons to grant or deny each request. Select which option is appropriate and UNC Dataverse will update that user’s permission level.

You can also assign access under the Restricted Files section of this page. Navigate to the file and click the "Assign access" button. In the pop-up that appears, enter the user’s UNC Dataverse account name and grant them permissions to access the file.

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Unrestrict Access to Data

To unrestrict access to a data file, click the checkbox beside the file(s) and selecting "Edit files." In the dropdown menu, choose "Unrestrict." UNC Dataverse will update the dataset record to remove the restriction. When the updated draft page reloads, you will notice that the lock icon by the file(s) is removed. Once you publish the updated draft dataset record, UNC Dataverse users will be able to download the file(s) without requesting access.

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Embargo Data

In some cases, you may wish to embargo your data for a period of time. For example, some funding agencies will permit you to keep the data embargoed for up to a year while still allowing you to publish on your research. UNC Dataverse has a built-in embargo feature that lets you schedule the embargo period for up to 36 months.

To set an embargo on your data, navigate to your dataset record and scroll down to the Files list. Select the checkbox beside each file you want to embargo.

Open embargoexample.png
Image of Embargo pop-up in Dataverse where a user can designate the end date for a file embargo

After selecting the embargo end-date, enter a brief reason as to why the embargo exists. Click ‘Save Changes’ when you are finished.
The record will be updated, and an embargo message will be present in the file metadata.

Open embargoexample2.png
Image of an Embargo message within UNC Dataverse

Once published, users will not be able to download the embargoed files until the embargo date has been reached. When the embargo date is reached, UNC Dataverse will terminate the embargo and activate the download function for the embargoed files.

Caution: Curators and/or Admins will not be able to edit the embargo date once the dataset has been published. Please be certain that the embargo date you’ve selected is correct before you publish your dataset within UNC Dataverse..

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Publish Your Data

Note: Before publishing your data, make sure you have published your project dataverse. Navigate to your main project dataverse and click "Publish" in the upper right of the dataverse page.

When you publish your data in UNC Dataverse, the Dataverse platform will register the persistent identifier (DOI) for your record(s). It will also include the version number within the data citation and will start tracking the version history of your dataset record. It is important to thoroughly review your dataset record for quality and completeness before publishing. This ensures that you are sharing the highest quality materials for public use and will also keep you from making a bunch of version changes in a short time frame due to minor errors like typos or missing metadata. If you do have errors or are missing files, do not worry. You can still go into your record and make edits as needed.

Once you’ve reviewed your dataset record(s) and are ready to publish, click the "Publish dataset" button on the upper right of the dataset record. A pop-up will appear asking if you are ready to publish.

Caution: Once you publish a record in UNC Dataverse, it must remain published. If you accidentally share data that violates the UNC Dataverse Terms of Use, you cannot delete the data; it must be deaccessioned by UNC Dataverse staff. (See Deaccessioning a Public Dataset.).

After you click "Publish dataset," UNC Dataverse will register your DOI, and your draft will update to be Version 1.0. 

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Using Dataverse Metrics 

UNC Dataverse offers three main options for tracking usage and interactions with your shared data file(s) and documentation: built-in dataverse metrics (which count dataset downloads), API use tracking, and guestbook reports, which will track data interactions such as views, downloads, and explorations within the UNC Dataverse platform.

In this section:

• Use Built-In Dataverse Metrics
• Use Dataverse API Metrics
• Use Guestbooks

Use Built-In Dataverse Metrics

Each dataset record has a dataset metrics section that counts the number of downloads for that dataset. You can find this section underneath "Access dataset" on the far right of the dataset record.

Open downloadnumbers.png
Image of Dataset Metrics feature in Dataverse that depicts the number of downloads of the files from that dataset

Use Dataverse API Metrics

The Dataverse Project offers API to track dataset and dataverse metrics within UNC Dataverse. Learn more about Dataverse APIs in the API Guide (v5.9).

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Use Guestbooks

One of the unique features of UNC Dataverse is the Guestbook. Admins can create a custom guestbook that tracks user information, including name, institution, files downloaded, and reason for accessing. This information can be populated in a Guestbook Report that can be viewed in the UNC Dataverse interface or can be downloaded as a CSV. Tracking these metrics helps researchers and funding agencies recognize the value of sharing their data, which data are most popular, and why others may be interested in reusing their data for their own research.

Note: Guestbooks are turned off by default in UNC Dataverse. If you would like to use a guestbook for your dataset, you will need to create and enable the guestbook.

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Create Guestbook

To create a guestbook, log in to UNC Dataverse and navigate to your project dataverse. Click "Edit" on the far right of the page and select "Dataset guestbooks" from the dropdown menu. Click on "Create dataset guestbook."

Enter a name for your guestbook in the Guestbook Name field. Use the "Data collected" checkboxes to make any or all of those fields required.

In the "Custom questions" section, you can add custom questions. Use the question type dropdown, then enter your question text into the field and use the checkbox to mark that field as required. If you need additional custom questions, use the [+] button to add more. Once you’ve finished customizing your guestbook, click on "Create dataset guestbook."

Your new guestbook will appear in a list on the Dataset Guestbooks page. This page will show the name of the guestbook, the date created, how many datasets have this guestbook enabled, and the number of responses to the guestbook. It also allows you to view, copy, edit, or delete the guestbook.

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Enable/Disable Guestbook

To enable the guestbook on your datasets, navigate to the desired dataset. Select "Edit dataset" on the right of the dataset page and choose "Terms" from the dropdown menu. Scroll to the bottom of the Terms page until you reach the Guestbook section. Select the guestbook you wish to enable. Click "Save changes" at the bottom of the page. 

Users who want to download or explore files within this dataset will first be prompted to fill in the dataset guestbook UNC Dataverse will automatically populate user account information within the guestbook, but users may include additional information.

To disable a guestbook, navigate back to the dataset and select "Edit dataset > Terms." Scroll to the bottom of the Terms page to the Guestbook section and click the "Clear selection" button to deselect the guestbook. Click "Save changes." The guestbook is no longer be enabled for that dataset.

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Generate a Guestbook Report

When a guestbook is enabled for a dataset record, UNC Dataverse tracks user downloads and data explorations of the files within that record. These metrics can be viewed within the UNC Dataverse platform or exported as a spreadsheet.

To view guestbook entries, log in to your project dataverse. Click on "Edit" on the far right of the page and select "Dataset guestbooks" from the dropdown menu. You will see a list of your guestbooks with usage statistics for each guestbook.

Click on "View responses" to see all user downloads and data explorations for your enabled guestbook. Dataverse automatically tracks user information such as name and affiliation. It also records the exact file(s) downloaded and/or viewed and the date of file access.

To download the responses into a CSV spreadsheet, click the "Download all responses" button above the table.

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Deleting or Deaccessioning Datasets

UNC Dataverse admins and curators can delete draft datasets and dataverses. You cannot delete published datasets; instead, they must be deaccessioned by UNC Dataverse staff. 

In this section:

• Delete a Draft Dataverse
• Delete a Draft Dataset
• Deaccession a Published Dataset

Delete a Draft Dataverse

Note: A draft dataverse can only be deleted if there are no dataset records (published or draft) within it. You must delete all draft datasets before deleting a draft dataverse.

To delete a draft dataverse, navigate to the project dataverse and click on "Edit," then select "Delete dataverse."

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Delete a Draft Dataset

A draft dataset has not yet been published or had its DOI registered. You can simply delete draft datasets from your project dataverse.

To delete a draft dataset, click on the dataset record and then select "Edit dataset." Click on "Delete dataset" from the dropdown menu.

A pop-up window will appear asking if you are certain that you want to delete the draft. Deleting the draft will remove it entirely from UNC Dataverse. 

Caution: A deleted draft cannot be recovered, so make sure this is what you want to do!

Click "Continue" to permanently delete your draft dataset. You will see a green success bar at the top of your project dataverse alerting you that the draft dataset has been successfully deleted.

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Deaccession a Published Dataset

Deaccessioning is the term used to describe removing a published dataset from UNC Dataverse. UNC Dataverse does not actually delete the entire dataset; as a data repository, we are committed to transparency and to preserving our holdings. This means that when you deaccession a dataset record within UNC Dataverse, the persistent identifier (DOI) will still resolve to the dataset record, but the data files and most of the metadata will be unavailable. Datasets should only be deaccessioned if the data are in violation of UNC Dataverse Terms of Use (data contain PII or PHI, copyright violations, takedown requests, etc.).

When a dataset has been deaccessioned, the DOI will lead users to a "tombstone" dataset record, which provides information about when the data were removed and why. If the data are available in another location, instructions for accessing those data will be included in the deaccessioned dataset record. This ensures that users can track the version history of the data and can reach out to the data producers if the data are available for download outside of UNC Dataverse.  

Caution: Do not deaccession a record on your own! If you need to deaccession your published dataset, please submit a help ticket with a link to the record in question. We will review the record and work with you to find the most appropriate solution.

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Advanced Features

In this section:

• Submit for Review
• Featured Dataverses

Featured Dataverses

You may wish to organize your dataverse within sub-dataverses.

Tip: Organizing your dataverse using featured dataverses is especially helpful for research projects with multiple studies or research centers conducting multiple projects.

To display all the sub-dataverses within a dataverse, define them as featured dataverses. Featured dataverses will appear above the Results section of your dataverse main page.

To feature a dataverse, navigate to your project dataverse and select "Edit" from the right side of the page. Choose "Featured dataverses" from the dropdown menu.

A pop-up window will appear with a list of published sub-dataverses that can be added as featured dataverses. Select the sub-dataverse you wish to feature and click the right arrow button [→] to add it to the column on the right. Click "Save changes" when you’ve selected the appropriate sub-dataverse(s). 

Your sub-dataverse will now appear above the Results section on the main page of your project dataverse.

To un-feature a dataverse, navigate back to the "Featured dataverses" option in the Edit menu. In the pop-up, select the sub-dataverse in the right column you wish to remove from the Featured Dataverses list, then click the left arrow [←] to move it to the left column. Click the "Save changes" button when you are done.

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Submit for Review Function

On the Permissions page, UNC Dataverse offers a feature called "Submit for review" for dataverse admins. This setting limits how data contributors can interact with your dataverse. With this limitation enabled, contributors can only create and edit new datasets, but they cannot publish their datasets themselves; the "Publish dataset" button will be replaced with a "Submit for review" button. The publish function is reserved for the dataverse admins and curators. 

When a contributor finishes adding data files and updating their metadata, they click the "Submit for review" button. This locks the dataset record so that the contributor can no longer make edits.

This triggers a notification from UNC Dataverse to the project dataverse admin and curator that a dataset record has been submitted for review. After reviewing the dataset record, the admin can click the "Publish dataset" dropdown, which offers two options: "Publish dataset" or "Return to author." "Publish" publishes the dataset as-is; the admin can make edits to the record themselves before choosing to publish the dataset, or they can choose "Return to author" to unlock the record and allow the contributor to make further edits. 

Once the contributor finishes the edits, they click the "Submit for review" button again to request another review of the record, beginning the cycle again. 

Tip: This is a useful feature for large project dataverses with many contributors or for journal dataverses who need to review the submissions to ensure compliance with data sharing policies.

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