The Computer Science Ontology (CSO)

Abstract

the Computer Science Ontology (CSO),\r\na large-scale, automatically generated ontology of research areas, which includes about 14K topics and 162K\r\nsemantic relationships. It was created by applying the Klink-2 algorithm on a very large data set of 16M\r\nscientific articles. CSO presents two main advantages over the alternatives: i) it includes a very large number\r\nof topics that do not appear in other classifications, and ii) it can be updated automatically by running Klink-2\r\non recent corpora of publications. CSO powers several tools adopted by the editorial team at Springer Nature\r\nand has been used to enable a variety of solutions, such as classifying research publications, detecting\r\nresearch communities, and predicting research trends. To facilitate the uptake of CSO, we have also released\r\nthe CSO Classifier, a tool for automatically classifying research papers, and the CSO Portal, a Web application\r\nthat enables users to download, explore, and provide granular feedback on CSO. Users can use the portal to\r\nnavigate and visualize sections of the ontology, rate topics and relationships, and suggest missing ones. The\r\nportal will support the publication of and access to regular new releases of CSO, with the aim of providing\r\na comprehensive resource to the various research communities engaged with scholarly data.\r\n