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Without logging in to Dataverse, users can browse Dataverse, search for dataverses, datasets, and files, view dataset descriptions and files for published datasets, and subset, analyze, and visualize data for published (restricted & not restricted) data files. To view an unpublished dataverse, dataset, or file, a user will need to be given permission from that dataverse’s administrator to access it.
A user can search within a specific dataverse for the dataverses, datasets, and files it contains by using the search bar and facets displayed on that dataverse’s page.
You can search the entire contents of the Dataverse installation, including dataverses, datasets, and files. You can access the search through the search bar on the homepage, or by clicking the magnifying glass icon in the header of every page. The search bar accepts search terms, queries, or exact phrases (in quotations).
To perform an advanced search, click the “Advanced Search” link next to the search bar. There you will have the ability to enter search terms for dataverses, dataset metadata (citation and domain-specific), and file-level metadata. If you are searching for tabular data files you can also search at the variable level for name and label. To find out more about what each field searches, hover over the field name for a detailed description of the field.
In Dataverse, browsing is the default view when a user hasn’t begun a search on the homepage or on a specific dataverse’s page. When browsing, only dataverses and datasets appear in the results list and the results can be sorted by Name (A-Z or Z-A) and by Newest or Oldest.
Saved Search is currently an experimental feature only available to superusers. Please see the Native API section of the API Guide for more information.
After performing a search and finding the dataverse or dataset you are looking for, click on the name of the dataverse or dataset or on the thumbnail image to be taken to the page for that dataverse or dataset. Once on a dataverse page, you can view the dataverses, datasets, and files within that dataverse.
Once on a dataset page, you will see the title, citation, description, and several other fields, as well as a button to email the dataset contact and a button to share the dataset on social media. Below that information, the files, metadata, terms of use, and version information for the dataset are available.
Files in Dataverse each have their own page that can be reached through the search results or through the Files table on their parent dataset’s page. The dataset page and file page offer much the same functionality in terms of viewing and editing files, with a few small exceptions. The file page includes the file’s persistent identifier (DOI or handle), which can be found under the Metadata tab. Also, the file page’s Versions tab gives you a version history that is more focused on the individual file rather than the dataset as a whole.
You can find the citation for the dataset at the top of the dataset page in a blue box. Additionally, there is a Cite Data button that offers the option to download the citation as EndNote XML, RIS Format, or BibTeX Format.
Within the Files tab on a dataset page, you can download the files in that dataset. To download more than one file at a time, select the files you would like to download and then click the Download button above the files. The selected files will download in zip format.
You may also download a file from its file page by clicking the Download button in the upper right corner of the page, or by using the Download URL listed under the Metadata tab on the lower half of the page. The Download URL can be used to directly access the file via API (or in a web browser, if needed). Certain files do not provide Download URLs for technical reasons: those that are restricted, have terms of use associated with them, or are part of a dataverse with a guestbook enabled.
Tabular data files offer additional options: You can explore using the TwoRavens data visualization tool (or other External Tools if they have been enabled) by clicking the Explore button, or choose from a number of tabular-data-specific download options available as a dropdown under the Download button.
Ingested files can be downloaded in several different ways.
rsync is typically used for synchronizing files and directories between two different systems, using SSH to connect rather than HTTP. Some Dataverse installations allow downloads using rsync, to facilitate large file transfers in a reliable and secure manner.
rsync-enabled Dataverse installations have a new file download process that differs from traditional browser-based downloading. Instead of multiple files, each dataset contains a single “Dataverse Package”. When you download this package you will receive a folder that contains all files from the dataset, arranged in the exact folder structure in which they were originally uploaded.
At the bottom of the dataset page, under the Data Access tab, instead of a download button you will find the information you need in order to download a Dataverse Package using rsync. If the data is locally available to you (on a shared drive, for example) then you can find it at the folder path under Local Access. Otherwise, to download the Dataverse Package you will have to use one of the rsync commands under Download Access. There may be multiple commands listed, each corresponding to a different mirror that hosts the Dataverse Package. Go outside your browser and open a terminal (AKA command line) window on your computer. Use the terminal to run the command that corresponds with the mirror of your choice. It’s usually best to choose the mirror that is geographically closest to you. Running this command will initiate the download process.
After you’ve downloaded the Dataverse Package, you may want to double-check that your download went perfectly. Under Verify Data, you’ll find a command that you can run in your terminal that will initiate a checksum to ensure that the data you downloaded matches the data in Dataverse precisely. This way, you can ensure the integrity of the data you’re working with.
Please see the Data Exploration Guide.