The Henry A. Murray Research Archive (MRA) at Harvard University’s Institute for Quantitative Social Science (IQSS) is a permanent repository for qualitative and quantitative research data. Founded in 1976, tucked away in Radcliffe Yard, the MRA was fondly known as The Murray Center, emphasizing the study of lives over time, with a particular focus on the lives and concerns of women. Even from these early years, the MRA was defined by its commitment...
We are extremely excited to announce the latest progression for our Dataverse community with the forming of a new Global Dataverse Community Consortium.
The vision is that the Global Dataverse Community Consortium (GDCC) will provide international organization to existing community efforts and will provide a collaborative venue for institutions to leverage economies of scale in support of Dataverse repositories around the world. It is our intention that the consortium be community driven and ultimately the goals to be defined by the participants. But recent developments...
This release introduces a modular Explore feature to support external tools. It includes performance enhancements for S3 storage, provides an API endpoint to move datasets and other improvements, includes documentation improvements and fixes a number of bugs.
For a full list of new features, enhancements, and bug fixes, check out the release notes.
Dataverse’s latest update adds more metadata to dataset landing pages, using a community-driven vocabulary supported by major search engines to make it even easier to find open data online.
Search results account for a large portion of traffic to datasets published online. For example, since Dataverse 4 was released in June 2015, at least a fifth of the traffic to dataset pages in the largest Dataverse installation, Harvard Dataverse, has come from search engines, mostly Google. Giving search engines and other systems richer metadata to index datasets will help people...
In this release we introduce support for AWS S3 file storage, providing Dataverse installations with a cloud option. We also include support for Large Data upload via rsync and integration with an external application, the Data Capture Module (DCM). Other enhancements include improved Swift object storage, csv file ingest improvements, support for increased password complexity, downloading large guestbooks, removal of a user's roles, improved documentation, and various bug fixes.
Any fish can tell you: It’s important to know the waters you’re swimming in. To that end, Usability Researcher Derek Murphy and Product Research Specialist Julian Gautier have put together a spreadsheet that compares Dataverse’s features, usage, and governance with other prominent online data repositories. In this way, we sought to discover trends in repository design to help inform future development of Dataverse. Now we would like to share our findings with the community.
This release introduces a user management view to the administrator dashboard, listing relevant user information, providing search and super user promotion/demotion functionality. A few other community requested fixes and modifications are also provided.
Display installation users in table format.
Provide super user toggle functionality.
Add additional information to user table: creation time, last login, last api use.
Last week, more than 200 participants from around the world gathered to learn about, discuss, and improve Harvard’s own open-source research data repository software, Dataverse. Dataverse is developed at the Institute for Quantitative Social Science (IQSS) and used by researchers and journals at Harvard University and beyond to archive, share and receive credit for data. At the 2017 Dataverse Community Meeting, attendees and speakers from over 60 universities and other research organizations convened to discuss and address subjects such as data sharing, reproducibility of research, the data lifecycle, and integrating Dataverse with visualization tools, computational resources, and expanded data storage options.