Introduction: The distribution of research data across a wide range of repositories can make accessibility a complex issue. Difficulties can range from ownership of data and intellectual property to security and maintenance of the data. This becomes a greater challenge since hosting collections of large datasets is a custom Confluence template that is intended to be re-used in the creation of workshops presented by ARCC on the Wiki. All of the content in these sections is intended to be replaced by the author of the workshop. The first step in this style guide is to ensure that the the page is in wide mode to maximize the real estate for content when possible. The Title of the Page should be the same as the Title of the workshop and this section should include a quick intro to the topic, why it’s important for ARCC users, and what users should expect to get out of this workshop. Next should be a Table of Contents macro in vertical format. The Table is intended to be used as an agenda section for presenter mode as well as navigation for non-presenting viewing so that users can find the documentation and navigate to what they need to brush up on. Finally, at the end of each section, there should be a divider to indicate the separation of “slides”
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Headers and Sections
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Code Examples
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Two Column Tables are nice ways to separate content/ Background info along with a code example on the same “Slide”. Please notice the table width. This should stop scroll bars from appearing
Bullets are nice to include for distinct points
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Please use the "code snippet" in the + button when creating code examples.
Also please do not go past the width of the table.
This is to prevent scroll bars appearing This is the Max number of code lines to show an example
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Straight Code - No context
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Limit to 16 lines in the example. This is the end |
Same Thing With Images
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Two Column Tables are nice ways to separate content/ Background info along with an image example on the same “Slide”. Please notice the table width. This should stop scroll bars from appearing
Bullets are nice to include for distinct points
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they
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This is 14 lines
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Finally The End
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Link to Previous sub-module or Home Module
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often a significant financial burden. The Wyoming Data Repository (WDR) meets this long-standing need from Researchers at the University of Wyoming and around the state. This service provides a consolidated repository for research datasets produced by UW and potentially other state entities. In addition, it provides ongoing support from qualified curators at the UW Libraries Digital Collections Office and technical support from experienced professionals at UW's Advanced Research Computing Center. The repository is hosted on-premise in a cost-effective, sustainable manner, within UW ARCC's advanced infrastructure. Support, collaboration and buy-in from all entities associated with the project ensure that data placed in the repository is well maintained, more easily searchable and highly available. This workshop covers, signing up, logging in, and uploading a dataset to The Wyoming Data Repository.
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What is Dataverse?
The Wyoming Data Repository is powered by the Dataverse Project. The Dataverse Project is different than what many may know the term Dataverse as the Microsoft product. Dataverse is an open source web application to share, preserve, cite, explore, and analyze research data. It facilitates making data available to others, and allows you to replicate others' work more easily. Researchers, journals, data authors, publishers, data distributors, and affiliated institutions all receive academic credit and web visibility.
A Dataverse repository is the software platform, which hosts multiple virtual data archives. Each of these archives contains a collection, a collection contains datasets, and each dataset contains descriptive metadata and data files. However, these archives are referred to within the Dataverse ecosystem as a “dataverse” and each dataverse can contain multiple sub-dataverses. For the sake of clarity, we will only refer to the “University of Wyoming Dataverse Collection” throughout the rest of this user guide and if there is any interest in creating a separate dataverse or sub-dataverse please contact wyodata@uwyo.edu to consult with the UW-libraries on the best path forward.
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Signing Up
In order to use the WDR, researchers must first sign up. All University of Wyoming users (students, faculty, and staff) are eligible to submit datasets to the WDR . The UW Libraries and ARCC will review all requests and will endeavor to publish submissions within five (5) business days. In some cases we will have questions about your dataset that need to be clarified before publication. If you have a tight deadline for a dataset, we cannot guarantee that we will be able to meet that deadline without reasonable notice. Please plan ahead!
In order to sign up, please navigate to the Wyoming Data Repository website at https://dataverse.arcc.uwyo.edu and click on the “Sign Up” link on the top menu bar.
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This takes you to a form on the ARCC Service Portal where you will need to enter some information for your account creation. This includes name, email, institution affiliation, college/department, suggested name of a Dataverse Collection, and additional information.
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Once you add the required information, ARCC and the Libraries will receive the request for review and create the account. You will be notified as an emailed reply to the request.
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Logging In
Once you get the confirmation of the account creation, it is now possible to login to the Wyoming Data Repository. To do this, you will need to click on the “Log In” link on the top menu bar.
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This then takes you to a page that asks how you would like to login, whether within the university of Wyoming or by username and email. This is a default setting on the Dataverse Project, ALL accounts that have been created should use the University of Wyoming button.
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This takes you to the ARCC login page where you can enter your username and password that you signed up with.
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WARNING: you must have your Two-Factor authentication configured before continuing to this step. Be ready to accept the push notification once you click the “Sign In” button |
You can confirm that you have logged in by looking at the far right of top menu bar, where your name should be displayed.
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When you log in for the first time, click on your user account (in red text, upper right corner), then go to “Account Information.” From there, click on the “Send Verification Email” button. You will receive a verification email from wyodata@uwyo.edu asking you to verify your email address. Check your clutter and spam folders if you don’t receive that verification email. Click the link when you receive the email within 24 hours.
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Adding a Dataset
Once logged in, you can add a dataset that you would like published. To do so, please take the following steps:
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Click on the “University of Wyoming Dataverse Collection” logo near the center left.
Click on the “Add Data” button on the right and select “New Dataset”.
Proceed to add the metadata for the dataset.
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Adding Metadata for a Dataset
When adding a new Dataset, there will be some required metadata (Information about the Dataset to be published) that will need to be added in a form before the dataset can be published. Some of the required Metadata will be pre-populated based on your account/login information. The remaining required metadata will be marked with asterisks.
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Basic citation metadata instructions
Keep in mind that this basic citation metadata is how your data will be cited in research literature and it is how it will be discovered & indexed on the web. The more specific it is, the better (the opposite is also true!).
Unless you have been granted authorization to create a new Dataverse Collection, the “Host Dataverse” will be “University of Wyoming Dataverse Collection.”
Title field:
Enter a title that is actually useful to a person who is not familiar with your data. If it is replication data, you may use the “Add Replication Data for” button and enter the title of your associated article/study.Author field:
Enter your name (Lastname, Firstname) and affiliation. We *require* that you add an ORCID Identifier Type and Identifier (which is a 16 digit string) to your author information. If you don’t have an ORCID, sign up for one at https://orcid.org/If you have co-authors, enter additional authors by clicking on the “+” button to the right of that field.
ORCID's are not required for co-authors, but we highly recommend adding them if possible.
Point of Contact field:
This is how users will contact you if they have questions about your dataset. We strongly suggest that you use your UW email and not a personal email.Description field:
Much like the title, the description should be populated with information that describes your data which will also be useful for someone who is not familiar with it.Subject field:
This is a controlled vocabulary with 14 different selections available. Pick the one that most closely matches your data. We will not add custom subject fields.Keyword field:
If you want to add keywords that will be associated with your dataset, add them in the ‘Term’ box. This is a repeatable field.Related Publication field:
If you are publishing an article with which your data is associated, we highly recommend you enter that citation information here. If you have a DOI for that publication, add the ID type (DOI) and enter the DOI string in the Identifier sub-field. This will show up as a link to that publication on your dataset record.
Readme.txt instructions and template
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We require a readme.txt file for your dataset. There are no exceptions. You must include this in your uploaded files or we will reject your submission. We have a template available on the Libraries website. |
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Adding Files
Once the metadata is added and you are ready to upload your data files that you would like to be published, you may drag and drop them OR click the “Select Files to Add” button.
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Once you are ready, click the “Save Dataset” button.
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If you have a dataset larger than 5GB, you will need to use the DVWebLoader option. To load files this way, add your readme.txt now, but skip adding your data files in this step, then simply click the “Save Dataset” button for now (you will add your data files later). Instructions for submitting a dataset that is larger than 5GB are available in the next section. |
Once you click “Save Dataset” you will see a draft of your submission as follows.
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From here, you may click on ”Edit Dataset” to add additional metadata. These are additional fields that were not available on the initial “Citation Metadata“ form.
We suggest that you fill out the following metadata fields:
Metadata Field | Description | Examples |
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Topic Classification | Indicates a broad, important topic or subject that the dataset covers | solid state physics, quantum chemistry, ethnopaleontology |
Date of Collection | The dates when the data were collected or generated | Start: 2020-05-10, End: 2020-09-30 |
Production Location | The location where the data and any related materials were produced or collected | Beartooth Mountain, Latitude: X Longitude: Y |
Funding Information | Information about the dataset's financial support | SF grant no. 1234567, School of Energy Resources |
Software | Information about the software used to generate the dataset | LabVIEW, Python v. 3.11.9, ORCA |
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Submitting Datasets Over 5GB
If you skipped the “Add Files” step on the last form because the dataset you wanted to publish was too large, you may add them on the draft page of your dataset by clicking on the “Upload Files” button in the lower right side of the page.
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If your dataset is over 5GB, click on the “Upload a folder” button. |
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The “Upload a Folder” button will open a new tab which will let you select an entire directory or folder to upload using DVWebLoader. WDR will keep the organizational structure of your directory and everything in it. If you are uploading a large dataset, we suggest that you use a very fast connection and that you do not use campus or personal wifi as that will significantly slow down the process. Note that there will be no upload progress shown, but you will see a green message notifying of successful upload once the upload is complete.
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Setting Terms/Licensing for your Data
By default, WDR is set to attach a CC0 license to all data submitted to the system. A CC0 license means that your data will be in the public domain, with no restrictions on use and no copyright. If you would like to change the license for your dataset, click the “Edit Dataset” button, then click on “Terms.”
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You may now select a different license from the drop-down menu and save your changes. Read more about the licenses in the following links:
If you have questions about these licenses, please contact us at wyodata@uwyo.edu
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Placing an Embargo on your Dataset
Should you, your co-authors, or your publisher opt to embargo your dataset, you must do that before submitting for review. You must upload your data before you can set an embargo. To do this, select the files you wish to embargo, then go to the “Edit Files” button, then select “Embargo.”
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You may now enter the precise date using the calendar or simply typing it in the ”Embargo end date” field and save your changes. Once that date is reached, the data will be openly available for download to any user but up until that date, only the metadata record and citation will be available. Please note that the embargo feature is not to be used for restricted access or peer review of your data. Should you require that, we will not publish the dataset but can provide you with a private URL for users to access your data before publication.
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Submitting for Review
Once you have all of your metadata entered, your files (including your readme.txt file) added, and are satisfied. Click on the “Submit for Review” link and then click on the “Submit” button.
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This will enter your dataset into a review queue and you will receive an email indicating that your dataset is under review. We endeavor to publish submitted datasets within 5 working days. Please plan ahead. We may, upon review, ask for changes to the metadata, files, or the readme.txt.
Once your dataset is published, you will receive another email letting you know that it has been published. Should you choose to cite or share your own data, please use the DOI (Digital Object Identifier) assigned to your dataset and not the URL at which it is accessible.
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De-accessioning Data/Take Down Requests
Generally speaking, we do not remove data once it has been published in WDR. If you need us to remove your data, we will review your request. Please do note that we cannot delete a DOI once it has been created and we cannot permanently delete a record either. The existence of the record will still be available in WDR, but the content will not.
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If you have questions, please contact us at wyodata@uwyo.edu |
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Getting Support
For support or any questions that you may have, please contact wyodata@uwyo.edu to consult with the UW-libraries for publishing related questions or ARCC at arcc-help@uwyo.edu for technical related questions.