
OSF Preprints
Accelerating scientific discovery through open, versioned, and DOI-indexed scholarly dissemination.

Accelerate research discovery with an open, FAIR-compliant repository for all your scientific datasets.

Mendeley Data, an integral component of the Elsevier Research Intelligence ecosystem, is a cloud-native repository designed to facilitate the storage, sharing, and publication of research datasets according to FAIR (Findable, Accessible, Interoperable, and Reusable) principles. As of 2026, it has evolved into a sophisticated platform leveraging machine learning for automated metadata enrichment and intelligent cross-referencing with global academic literature via Scopus and ScienceDirect. The technical architecture supports a wide array of scientific file formats, providing researchers with permanent Digital Object Identifiers (DOIs) for their datasets, ensuring long-term citability and compliance with global funding mandates. Its market position is unique, serving both as a free tool for individual researchers and a robust 'Data-as-a-Service' (DaaS) solution for institutions that require enterprise-grade governance, private collaborative environments, and comprehensive data management planning (DMP) integration. The platform's ability to handle multi-terabyte datasets while maintaining high availability and rigorous security standards makes it a cornerstone for modern data-driven scientific discovery and institutional audit readiness.
Mendeley Data, an integral component of the Elsevier Research Intelligence ecosystem, is a cloud-native repository designed to facilitate the storage, sharing, and publication of research datasets according to FAIR (Findable, Accessible, Interoperable, and Reusable) principles.
Explore all tools that specialize in doi generation. This domain focus ensures Mendeley Data delivers optimized results for this specific requirement.
Open side-by-side comparison first, then move to deeper alternatives guidance.
Uses NLP to extract key terms from uploaded documentation and suggest DataCite tags.
Supports multiple iterations of a dataset while maintaining a link to the original DOI via 'IsVersionOf' relationships.
Server-side rendering of tabular and image data for instant inspection without downloading large files.
Deep integration with the Scopus database to display data citations alongside paper citations.
Encrypted environments for pre-publication data sharing among globally distributed teams.
Allows institutional admins to review datasets before they are minted with a DOI.
Automatic indexing in Google Dataset Search, DataCite, and Mendeley Search.
Create an Elsevier account or log in via institutional SSO.
Navigate to the 'My Datasets' dashboard to initialize a new data project.
Define project visibility settings (Private, Shared with specific contributors, or Public).
Upload raw data files and associated documentation (e.g., Readme, Codebooks).
Select a standardized license (e.g., CC BY 4.0, CC0) to define usage rights.
Input mandatory DataCite metadata, including Author ORCID, methodology, and funding sources.
Invite lab collaborators via email to contribute or review the dataset draft.
Utilize the 'Link to Article' feature to connect the dataset to a peer-reviewed publication.
Submit the dataset for a permanent DOI assignment and indexing.
Monitor dataset impact through integrated citation and download metrics.
All Set
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Verified feedback from other users.
“Users highly value the seamless integration with Elsevier's publishing ecosystem, though some find the interface less modern compared to Figshare.”
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