{{publicationsSize.number|number}}{{publicationsSize.size}} publications deduplicated {{datasetsLinkedSize.number|number}}{{datasetsLinkedSize.size}} datasets interlinked with publications {{datasetsSize.number|number}}{{datasetsSize.size}} research data {{softwareLinkedSize.number|number}}{{softwareLinkedSize.size}} research software interlinked with publications {{softwareSize.number|number}}{{softwareSize.size}} research software Persistent identifiers and registries {{fundersSize.number|number}}{{fundersSize.size}} funders and {{projectsSize.number|number}}{{projectsSize.size}} funded grants

Extracted Metadata Combined.

The OpenAIRE Research Graph is one of the largest open scholarly record collections worldwide, key in fostering Open Science and establishing its practices in the daily research activities. Conceived as a public and transparent good, populated out of data sources trusted by scientists, the Graph aims at bringing discovery, monitoring, and assessment of science back in the hands of the scientific community.

Imagine a vast collection of research products all linked together, contextualised and openly available. For the past ten years OpenAIRE has been working to gather this valuable record. OpenAIRE is pleased to announce the beta release of its Research Graph, a massive collection of metadata and links between scientific products such as articles, datasets, software, and other research products, entities like organisations, funders, funding streams, projects, communities, and data sources.

As of today, the OpenAIRE Research Graph aggregates around 450Mi metadata records with links collecting from 10,000 data sources trusted by scientists! After cleaning, deduplication, and fine-grained classification processes, they narrow down to ~100Mi publications, ~8Mi datasets, ~200K software research products, 8Mi other products linked together with semantic relations.

More than 10Mi full-texts of Open Access publications are mined by algorithms to enrich metadata records with additional properties and links among research products, funders, projects, communities, and organizations. Thanks to the mining algorithm, the graph is completed with 480Mi semantic relations.