A Dataset of Scientific Topics

The automatic extraction of topics is a standard technique for summarizing text corpora from various domains (e.g., news articles, transport or logistic reports, scientific publications) that has several applications. Since, in many cases, topics are subject to continuous change there is the need to monitor the evolution of a set of topics of interest, as the corresponding corpora are updated. The evolution of scientific topics, in particular, is of great interest for researchers, policy makers, fund managers, and other professionals/engineers in the research and academic community. In this dataset, we provide a set of topics for scientific publications gathered from Crossref. The topics have been produced by performing a topic modeling analysis on two distinct sets of publications, each coming from a different time period. 

Acknowledgements: This research was partially funded by project ENIRISST under grant agreement No. MIS 5027930 (co-financed by Greece and the EU through the European Regional Development Fund).