Case Study: Springer Nature accelerates materials research with Stardog

Springer Nature accelerates materials research with Stardog using a 100-million-triple knowledge graph

Springer Nature, a global academic publisher, faced a challenge with its SpringerMaterials research platform. Its legacy XML-based infrastructure was unable to support the semantic search functionality its 50,000 users relied on, hindering research by obscuring data relationships and slowing down the platform's release cadence. To meet user and internal needs, they turned to vendor Stardog for a solution.

By implementing Stardog's knowledge graph platform, Springer Nature unified its data into a single model containing 100 million triples. This solution provided sub-second query times and enabled powerful new semantic search features that understand user intent. The measurable impact includes expedited research for users through accurate, focused search results and the ability to easily integrate materials data into various workflows. Stardog's flexibility also allows for quarterly updates to the knowledge graph.

Springer Nature