SN SciGraph

A Linked Open Data platform for the scholarly domain

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Welcome to SN SciGraph, our Linked Open Data offering which aggregates data sources from Springer Nature and key partners from the scholarly domain. The Linked Open Data platform collates information from across the research landscape, for example funders, research projects, conferences, affiliations and publications.

Additional data, such as citations, patents, clinical trials and usage numbers will follow over time. This high quality data from trusted and reliable sources provides a rich semantic description of how information is related, as well as enabling innovative visualizations of the scholarly domain.

By doing so, SN SciGraph overcomes former boundaries by relating comprehensive information about the research landscape. It represents a further step in data integration and it will continue to grow organically. Our aim is to increase the discoverability of high quality data as larger parts of our datasets are being made available under CC-BY licensing.

SciGraph visual

The data in SN SciGraph is projected to contain 1.5 to 2 billion triples. We are constantly iterating on adding more metadata from journals and articles, books and chapters, organizations, institutions, funders, research grants, patents, clinical trials, substances, conference series, events, citations and reference networks, Altmetrics, links to research datasets and much more.

SN SciGraph in 90 seconds

Benefits for the research community

  • Researchers benefit by overcoming internal and external data silos in research communities
  • Users of the scholarly domain broaden their perspective by semantic relations being revealed visually
  • Developers are actively encouraged to reuse Springer Nature’s datasets
  • Authors and editors enjoy easy access to high quality data from trusted and reliable sources
  • Funders, librarians, conference organizers find optimal data for analysis and recommendation tools
  • Large parts of the datasets are being made available under CC-BY licensing.

Statements

Our vision is to create the largest state of the art linked data aggregation platform for the scholarly domain. We ingest data across internal and external data silos to transform it for re-usage across the entire enterprise and research area.

Henning Schoenenberger, Director Product Data and Metadata

Data is infinitely more valuable when you look beyond the individual datasets to the relationship between them. We are thrilled to be collaborating with Springer Nature to bring this openly available platform to the larger community.

MARIO DIWERSY, MANAGING DIRECTOR, ÜBERRESEARCH (PART OF DIGITAL SCIENCE)

The Springer Nature SciGraph architecture is the result of more than five years of research and development with semantic technologies, linked data, and, in particular, their application to the scholarly publishing domain which both Nature and Springer had been working on – at first separately, now united.

Michele Pasin, PhD, Lead Data Architect 

We are happy to support SpringerNature in their journey of interlinking and making huge amounts of diverse data discoverable. Ontotext's vision is to provide a reliable semantic graph database that offers fast data loading, efficient data updates and is easy to use.

Atanas Kiryakov, CEO Ontotext

Our leading principle was always to be as open with the data and as passionate with support for applications as possible. We are proud to say that this new product was implemented with cutting edge semantic web technologies applying a sophisticated, internally developed ontology.

Markus Kaindl, Senior Manager Semantic Data and product owner

Key partners

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Digital Science is a primary data provider and development partner on the project - also helping to kick-start the project with senior staff joining our team.

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derivo is supporting the project with their expertise in knowledge modeling. They also provide an instance of SemSpect for visually exploring SN SciGraph data: http://scigraph.semspect.de

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We are using Ontotext’s triple store GraphDB as scalable semantic graph database. Their support during the initiation of the project and afterwards has been excellent.

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InfoChem provides named entity recognition in the chemical domain, annotating relevant substances, chemical compounds & molecules.

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We will be storing the main concepts of our publications as extracted by Unsilo in our graph to cluster documents around certain topic areas.