rdm-review-dashboard

Review Dashboard Frontend

The Review Dashboard provides the user interface for reviewing datasets in Dataverse. It requires a running review dashboard backend and is built using Angular CLI 14.1.2. The frontend communicates exclusively with the backend API and cannot function independently.

Usage

The frontend provides an overview of the Datasets in the various stages of curation and guides the reviewer through the dataset review process. User needs to be logged on through their institutional logins, and have a reviewer or admin role in the Dataverse to access the Review Dashboard.

The dashboard organizes review into the following screens:

Selection -> Details -> Feedback -> Publish/Return

Frontend configuration

The frontend is configured through: src/assets/settings.json

The following configuration properties are available:

• "dataverseUrl": URL of your dataverse installation. It is used to produce the links to datasets.
• "apiURL": address of the Review Dashboard backend API.
• "dataverseName": name of your installation. By default it’s set to ‘Dataverse.’

User access

Users without the required permissions cannot access the Review Dashboard. More information, see: Roles.

User interface overview

Selection

In this screen, the user can see a list of datasets in Dataverse, organized into tabs. To adjust the number of datasets per page, enter the number in the textbox at the bottom of the page and press enter.

Available tabs:

• My reviews: datasets that are in review stage and are assigned to them
• Submitted for review: datasets that were submitted for review but not yet picked by a reviewer. The user can select a dataset for review using the Assign button, or View Details of the dataset before assigning it. Admins can assign the dataset to other reviewers as well by selecting reviewer from the pop-up list.
• In review: presents all the datasets that are currently in review. The assigned reviewer’s name can be seen in a tag, with the user icon. Admins can review datasets even without assigning them to themselves. This can be useful when they need to take over the review temporarily.
• Published: the datasets that are already published
• All: all of the datasets in the Dataverse

[!TIP] The button representing the next stage of the review (in this case Review), is always highlighted in blue.

Reviewers can:

• Assign datasets
• Unassign themselves from the dataset
• Start reviews
• Inspect dataset details

Administrators can additionally Change Reviewer of the dataset.

Details

The details screen presents not only more detailed information, such as the disk size of the dataset, but also the Review Checklist and Internal Notes.

The first section contains the following buttons:

• View dataset in [Dataverse name]: A link to the dataset in the dataverse, for the reviewer to examine in detail.
• Contact dataset creators: A mailto link, which will open an email compose in the locally installed email editor with the dataset contact’s email, name and dataset DOI are automatically added.
• Ask for support: Selecting this option will add a Support requested flag to the dataset that is visible in the selection screen. It will also notify with an email the helpdesk, that support has been requested for the dataset. The Internal Notes are added to the support email.

Review checklist

This section contains a checklist of criteria to be checked by the reviewer which datasets must meet before being published.

This list is generated based on dataset_issue_definitions.json in the backend. It is organized into categories based on the category property in the json file, and the items are based on the condition property. For information on the configuration, see the backend configuration docs. The checklist state is automatically saved.

Internal notes

In this section, the user can take notes about the review. The contents of the internal notes field are automatically saved.

[!IMPORTANT] The internal notes are not shared with the dataset creators, but are shared with the helpdesk when ask for support is clicked. They also persist between reviewers and reviews.

Feedback

The feedback screen provides:

• Summary: overview of the review
  • Issues: The issues found in the dataset. These are the checkboxes that are unchecked in the previous screen, populated using the warning field in the dataset_issue_definitions.json.
  • Notes: Notes that were saved in the previous screen
• Feedback: contains the latest saved state of the feedback email to be sent to the author that was autogenerated using the information from the checkbox and edited by the user. The Clear button deletes the email, and Generate from the Checklist regenerates the email. The feedback email is persistent and saved after each edit.

Note that, changing the checkboxes do not regenerate the email automatically after it was generated once. If you made changes in the checkboxes, you need to click Generate from Checklist to autogenerate a new email from them. This will also delete the previously saved email.

Two options below:

• Publish: To proceed to publishing the dataset.
• Return: Return the dataset to the author. A feedback email will be sent to the dataset contact.

Publish/Return

This screen lets the user to finalize their decision to publish the dataset or return it to the author.

Publish

Reviewers can publish datasets and select:

• Major release: increases the major version of the dataset, such as 1.0 to 2.0.
• Minor release: increases the minor version, such as 1.0 to 1.1.
• Update current version

If the dataset is previously not released it will be released as 1.0.

[!Note] If dataset files were modified, only a major release is possible.

Select Publish dataset in this screen to finalize publishing.

Return

If the user has selected Return, this screen will give a preview of the feedback email.

Select Return dataset in this screen to return the dataset and send the feedback email.

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