This release includes a complete refactoring of the SN SciGraph data model. Following up on users feedback, we have simplified it using Schema.org and JSON-LD, so to make it easier to understand and consume the data also for non-linked data specialists.  

This release includes two brand new datasets – Patents and Clinical Trials linked to Springer Nature publications – which have been made available by our partner Digital Science, and in particular the Dimensions team.

Highlights:

• New Datasets. Data about clinical trials and patents connected to Springer Nature publications have been added. This data is sourced from Dimensions.ai.
• New Ontology. Schema.org is now the main model used to represent SN SciGraph data.
• References data. Publications data now include references as well (= outgoing citations).
• Simpler Identifiers. URIs for SciGraph objects have been dramatically simplified, reusing common identifiers whenever possible. In particular all articles and chapters use the URI format prefix (‘pub.’) + DOI (eg pub.10.1007/s11199-007-9209-1).
• JSON-LD. JSON-LD is now the primary serialization format used by SN SciGraph.
• Downloads. Data dumps are now managed externally on FigShare and are referenceable via DOIs.
• Continuous updates. New publications data is released on a daily basis. All the other datasets are refreshed on a monthly basis.

Note: crossposted on https://researchdata.springernature.com

Graphs are essentially composed by two kinds of objects: nodes and edges. Nodes are like the stations in a train map, while edges are the links that connect the different stations.

Of course one wants to be able to move from station to station in any direction! Similarly in a graph one wants to be able to jump back and forth from node to node using any of the links provided. That’s the beauty of it!

Although the underlying data allowed for this, the SN SciGraph Explorer website wasn’t fully supporting this kind of navigation. So we’ve now started to add a number of ‘related objects’ sections that reveal these pathways more clearly.

For example, now it’s much easier to get to the organizations and grants an article relates to:

Or, for a book edition, to see its chapters and related organizations:

And much more..  Take a look at the site yourself to find out.

Finally, we improved the linked data visualization included in every page by adding distinctive icons to each object type – so to make it easier to understand the immediate network of an object at a glance. E.g. see this grant:

SN SciGraph is primarily about opening up new opportunities for open data and metadata enthusiasts who want to do more things with our content, so we hope that these additions will make discovering data items easier and more fun.

Any comments? We’d love to hear from you. Otherwise, thanks for reading and stay tuned for more updates.

PS: this blog was posted on the SN Research Data space too.