A Knowledge Graph Dataset for Research on Chinese Scientific and Technical Literature

The dataset is constructed as a literature-centered heterogeneous graph network, in which the node types include papers, authors, institutions, keywords, journals, and research fields.

All entities are assigned unified identifiers to ensure consistency and facilitate downstream processing. This dataset can support a variety of research tasks, such as paper recommendation, automatic journal selection, field classification, and graph representation learning. The files in the dataset are described as follows:titleContent.csv: titles of papersabstractContent.csv: abstracts of paperskeywordContent.csv: keywords of papersfieldContent.csv: research fields of papersvenueContent.csv: journals in which the papers were publishedpa.csv: associations between papers and authorspk.csv: associations between papers and keywordspf.csv: associations between papers and research fieldspv.csv: associations between papers and publication journals