Mendeley Data Williamina Fleming release
As part of the March 2020 Williamina Fleming release, we have updates to Mendeley Data Repository and Data Search, as well as our new module — Mendeley Data Monitor.
Mendeley Data Repository
For institutions
- Add new options for local data storage to give institutions full control of their public research data
- Datasets are retrievable using OAI-PMH protocol, for easy harvesting of records
- Institutional Admins can now add article links to datasets for enhanced viability
We have expanded our integration with the following S3-compatible storage options that institutions can choose to host their public research data in: Minio, Wasabi, Digital Ocean Spaces, Dreamhost.
We now provide the full set of Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH) endpoints to support metadata harvesting, to make dataset records easy to discover, access and index. The record set can be filtered by institution, so customer institutions can enable harvesting and indexing their datasets.

Admins can now link datasets at their institution to their associated research paper. This can enhance a dataset alongside the context of the article and also, to allow readers of the article to discover the underlying data, via a bi-directional link (please note, this is only available for supported journal platforms, such as ScienceDirect).

For researchers
- Thanks to an improved “Download all” option, public datasets are now ready for re-use with just one-click, irrespective of the dataset size and the number of files and folders it contains
- Researchers can now create both private and public Collections, to collate research data on any theme or topic
In support of FAIR data with Mendeley Data, we have improved the “Download all” option (available above the file tree) making the download of the entire dataset as a single zip archive file possible. Each archive contains the exact same folders and subfolders as the original dataset, making the dataset immediately available for re-use. Each dataset archive name includes the dataset version to help keeping track of versioning.
Researchers at customer institutions can now create and manage private and public collections, so that they can organise datasets for sharing, or for future reference.

Mendeley Data Search
For researchers
- Better guidance on the use of Advanced Search is now available
Advanced search allows users to construct targeted queries using Field Codes (e.g. TITLE(xxxx), AUTHOR(xxxx), AUTHOR_ID(xxxx) and many others), and boolean operators (AND, OR or NOT). Unfortunately, not all researchers are aware of the full capabilities. With this release, we have updated the user experience to provide on screen guidance on how best to use the advanced search syntax.

New module
Mendeley Data Monitor
We have launched this new Mendeley Data module to allow librarians and research officers to monitor public research data at their institution and keep track of compliance with the institutional RDM policy and funder mandates.
- as a standalone module, or alongside the other Mendeley Data modules as part of the Mendeley Data platform
- as an integration with Elsevier’s CRIS solution, Pure
Mendeley Data Monitor is available for institutions in several ways:
Would you like to learn more about how Mendeley Data Monitor can meet your needs?

For librarians and research officers: tracking of public institutional research data held in 1700+ open data repositories
- View the list of public datasets shared by researchers from your Institution
- View metadata of the individual datasets one by one
- Quickly access actual public datasets and linked publications
To stay up to date with research data sharing habits of researchers from your Institution:
- Ability to export the list of all/selected datasets in Excel and CSV file formats
- Information how the actual datasets can be modified or retracted at the source
To support research data archival needs and/or for further analysis:
For institutions: version disambiguation for datasets with an institutional association
We have enhanced our content quality by introducing an improved algorithm for dataset version detection into our metadata curation pipeline. This means that each dataset appears only once, despite having multiple versions, which provides a more accurate representation of the dataset output of your institution. User’s of Elsevier’s CRIS solution — Pure — can immediately benefit from this improvement by getting more accurate dataset metadata via the Data Monitor integration. This is also the case for any other user of our Data Monitor API.