Dataverse: A container for research data studies (see Study definition below) that can be customized and managed by its owner.

Study: A container for a research data set. It includes cataloging information, data files and complementary files.

Studies, Collections and Dataverses

Search studies and variable metadata: 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 Basic 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 (UNF) 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. This will also include R with the upcoming Dataverse Network 3.5 Release.
Subset for social network data: Files uploaded in GraphML offer additional subsetting and network measurements. See example of a dataverse with graph data files.
Full administration options for each dataverse: Customize branding, terms of use, manage user permssions, build collections, add and manage studies within a dataverse, and release the dataverse when ready.
User roles for contributing and reviewing: Contributors, curators and admins can be added as privileged users for each dataverse.
Workflows for all:
- Regular dataverses: Option to allow a Contributor (added by admin or curator) to add and edit their own studies. They may also be given permission to edit any study in this Dataverse. The studies go through a review process and only admins and curators can release new or edited studies. See example.
- Open dataverses: Option to allow any registered user to add and edit their own studies. The studies go through a review process and only admins and curators can release new or edited studies. See example.
- Wiki dataverses: Option to allow any registered user to add and edit any study in the dataverse. The studies go through a review process and only admins and curators can release new or edited studies. See example.
Study versioning: Save old versions of the study and allow citation to previous version(s).
Study restriction levels:
- Public
- Restrict individual file(s) but leave cataloging information public
- Restrict entire study
Study deaccession: Never need to delete a study permanently once it is released. Instead, the study can be deaccessioned and a newer study can be referenced.
Study Templates: Great flexibility creating templates based on a subset of cataloging fields, with pre-filled values.
Full study review workflow: A study can only be released by curators or admins of the dataverse that own that study.
Guestbook to log traffic to a dataset.
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.

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 harvest other Dataverse Networks or repositories.
Setup 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. See example.
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.
z39.50 support for distributed search.
LOCKSS (Lots Of Copies Keep Stuff Safe) support for data duplication to multiple locations.
E-Z proxy support to authenticate data access.