We present the Microsoft Academic Knowledge Graph (MAKG), a large RDF data set with over eight billion triples with information about scientific publications and related entities, such as authors, institutions, journals, and fields of study. The data set is based on the Microsoft Academic Graph and licensed under the Open Data Attributions license. Furthermore, we provide entity embeddings for all 210M represented scientific papers.

What exactly do we provide?

  1. Periodically updated RDF dump files of the whole Microsoft Academic Knowledge Graph.
  2. URI resolution of the Microsoft Academic Knowledge Graph within the Linked Open Data.
  3. A publicly accessible SPARQL endpoint containing the latest Microsoft Academic Knowledge Graph data.
  4. HTML page descriptions of resources in the Microsoft Academic Knowledge Graph via pubby.
  5. Entity embeddings for all papers in the Microsoft Academic Knowledge Graph.

How big is the Microsoft Academic Knowledge Graph?

The Microsoft Academic Knowledge Graph as of 2018-11 contains, among others,

Potential use cases:

  • Entity-centric exploration of papers, researchers, affiliations, etc. (e.g., concerning some research area)
  • Easier data integration through use of RDF and by linking resources to other data sources (e.g., combining the MAG knowledge graph with digital library collections in RDF).
  • Data analysis and knowledge discovery (e.g., measuring the popularity of papers and authors; recommending papers, researchers, and venues; and analyzing the evolution of topics, research methods and data sets over time).