Monthly Archives: March 2017

Announcing: Springer Nature SciGraph, the new Linked Open Data platform

SpringerNature announces Springer Nature SciGraph:

See Announcement at http://www.springernature.com/gp/researchers/scigraph?countryChanged=true

We are pleased to introduce Springer Nature SciGraph, the new Linked Open Data platform aggregating data sources from Springer Nature and key partners from the scholarly domain. The Linked Open Data platform will initially collate information from across the research landscape, such as 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, Springer Nature 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. This platform will increase the discoverability of high quality data as larger parts of our datasets will be made freely available under a CC BY-NC 4.0 license.

The data in Springer Nature SciGraph is projected to contain 1.5 to 2 billion triples. It will comprise 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.

See also

Springer Nature SciGraph: Supporting open science and the wider understanding of research

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 will be freely accessible (CC BY-NC 4.0 license)