The DBLP Discovery Dataset (D3) is a newly created dataset of research papers in the field of Computer Science which can support several tasks like identifying trends in research activity, productivity, focus, bias, accessibility, and impact. This dataset stems from DBLP and integrates additional information from the full-texts. We argue that papers classified with their research topics can improve the identification of research trends. To this end, we used the CSO Classifier to annotate all the papers within D3 and we made such extension available for research purposes. More info: https://www.salatino.org/wp/annotating-d3-dataset-with-the-cso-classifier/ More info pdf: https://www.salatino.org/wp/wp-content/uploads/2022/09/Annotating-D3-dataset-with-the-CSO-Classifier.pdf

{"references": ["Salatino, Angelo A., Francesco Osborne, Thiviyan Thanapalasingam, and Enrico Motta. \"The CSO classifier: Ontology-driven detection of research topics in scholarly articles.\" In International Conference on Theory and Practice of Digital Libraries, pp. 296-311. Springer, Cham, 2019."]}

This version follows the version 2.0 of the D3 Dataset