In the ongoing efforts to enhance data quality and accessibility, the new AGRIS 2.0 has faced technical challenges indexing files from Mendeley Desktop. To ensure a smoother data integration process, the technical team behind AGRIS strongly recommends data providers from using Mendeley Desktop to Mendeley Reference Manager (MRM). 

Why switch to MRM?

Mendeley Desktop, a valuable tool for researchers and data providers, has been succeeded by Mendeley Reference Manager (MRM). This transition began on September 1, 2022, when the download facility for Mendeley Desktop was disabled. While users can still access Mendeley Desktop and synchronize their saved information, this may lead to issues, especially when preparing data for submission to AGRIS.

To seamlessly transition to MRM, follow these steps:

1. Sync your Mendeley Desktop library: Begin by opening your existing Mendeley Desktop application and syncing your library. Wait for the synchronization process to complete.

2. Download and install MRM: Next, download and install MRM. Sign in with your Mendeley ID when prompted.

3. Seamless transition: All your folders - now called collections - along with groups, references, metadata, files, and annotations, will seamlessly appear in the new MRM window. You can now work with your existing library in MRM.

For more information on how to migrate from Mendeley Desktop to MRM, click here.

Once you start using the new MRM, there's no need to uninstall Mendeley Desktop. You can continue using it alongside MRM on the same computer. However, Data Providers preparing files to be shared with AGRIS must use MRM to export their data.

In summary, the transition from Mendeley Desktop to MRM ensures that AGRIS data providers can share files effectively for their indexing in AGRIS. It's a step towards seamless integration with other reference management software to improve data sharing and accessibility, which is core to AGRIS’ mission.

Stay tuned for further updates and announcements, and thank you for your dedication to enhancing data quality in agricultural research.