Dataverse and Research Space are pleased to announce an integration of the RSpace electronic lab notebook with Dataverse. This integration, described in the following brief video, enables researchers to deposit datasets directly from RSpace to any Dataverse.

By capturing lab data electronically in the RSpace ELN, and providing a simple deposit interface to Dataverse, we hope to make Dataverse more accessible to researchers, to foster a greater number of submissions, and to streamline the process of making datasets publicly available. Further curation can then be performed by data archivists using the full feature set of the Dataverse repository.

The growth in usage of both electronic lab notebooks and data repositories brings with it the need for the two kinds of digital environments to talk to each other. Researchers can now take advantage of RSpace to collect, share and organize research data, and directly deposit datasets of any complexity, including multiple documents in any format that can be structured in folders, and links to attachments, directly into Dataverse. The researcher’s ORCID id can be included as part of the export.

The integration enables researchers to take full advantage of Dataverse’s innovative approach to making datasets accessible and useful. Datasets archived in Dataverse can take advantage of persistent identifiers, automatically generated citations, robust metadata, and summary statistics and analysis for tabular files. Researchers depositing datasets into the Dataverse are offered tools allowing them to self-curate content deposited in the repository, with expanded curation services to be available in the near future.

The RSpace – Dataverse integration will be presented at the Dataverse Community call taking place on December 6 at 12 pm EST.

To learn more about the features of the Dataverse Project, visit Dataverse.org. To learn more about the features of RSpace, visit researchspace.com.