Dataverse: A virtual web archive that contains data studies and can be customized by and managed by its administrator or owner.

Study: A container for data files and cataloging information describing the data. It can also contain complementary files, such as documentation or code related to the data.

Studies, Collections and Dataverses

• Search studies and variable metadata: All cataloging fields provided in a study (title, author, dates, producer, abstract, keywords, geospatial information, methodology and data collection, etc) and variable label and descriptions are indexed using Lucene Index Server. Both quick search and advanced search are available across all dataverses and within a dataverse.
• Generate a formal data citation with a persistent identifier and url (a handle registered to the Handle.net service) and Universal Numerical fingerprint for verification and validation of the dataset.
• Subset and analysis for tabular datasets: Files uploaded in SPSS and STATA offer additional subsetting and analysis services, and can be downloaded in multiple formats. 
• Subset for social network data: Files uploaded in GraphML offer additional subsetting and network measurements.
• Full administration options for each dataverse: Customize, manage user permssions, terms of use and other settings, release the dataverse when ready, build collections, add and manage studies within a dataverse.
• User roles for contributing and reviewing: Contributors, curators and admins can be added as privileged users for each dataverse.
• Open dataverses: Option to allow any registered user to add and edit ownstudies. The studies go through a review process and only admins and curators can release new or edited studies.
• Wiki dataverses: Option to allow any registered user to add and edit any study in the dataverse. The studies goes through a review process and only admins and curators can release new or edited studies.
• Study versioning: Save old versions of the study and allow citation to previous version.
• Study deaccession: Never delete permanently a study once is released. Instead, the study can be deaccession and a newer study can be referenced.
• Study Templates: Great flexibility creating templates based on a subset of cataloging fields, with pre-filled values.
• Collections of studies: Flexible hierarchy of collections for each dataverse.
• Static Collections: Build collections from a list of studies.
• Dynamic Collections: Build collections based on a query.
• Link Collections: Add collections from other dataverses to your dataverse.
• Study restriction levels: Public, restrict individual file but leave cataloging information public, or restrictt entire study.
• Full study review workflow: A study can only be released by curators or admins of the dataverse that owns that study.

Dataverse Network Settings

• Full administration options for an entire Dataverse Network: Network admins can customize their Dataverse Network, create groups to organize and browse dataverses, manage settings, administrate OAI settings and harvesting other Dataverse Networks or repositories.
• Set user groups based on registered users or IP address.
• Open Dataverse Network: Option to allow any registered user to create a dataverse in the Network.
• Classification of dataverses: Define classifications to browse and easily find dataverses in the Dataverse Network homepage.
• Settings to register studies to Handle.net, by choosing a prefix for each Dataverse Network
• Settings to use the Dataverse Network as an OAI server and client, defining sets and harvesting from external sources.
• Settings to export all cataloging information (metadata) in various formats:DDI, Dublin Core, FGDC, Marc
• Support for z39.50
• Support for LOCKSS