Abstract
DBLP is the largest open-access repository of scientific articles on computer science and provides metadata associated with publications, authors, and venues. We retrieved more than 6 million publications from DBLP and extracted pertinent metadata (e.g., abstracts, author affiliations, citations) from the publication texts to create the DBLP Discovery Dataset (D3). D3 can be used to identify trends in research activity, productivity, focus, bias, accessibility, and impact of computer science research. We present an initial analysis focused on the volume of computer science research (e.g., number of papers, authors, research activity), trends in topics of interest, and citation patterns. Our findings show that computer science is a growing research field (15% annually), with an active and collaborative researcher community. While papers in recent years present more bibliographical entries in comparison to previous decades, the average number of citations has been declining. Investigating papers’ abstracts reveals that recent topic trends are clearly reflected in D3. Finally, we list further applications of D3 and pose supplemental research questions. The D3 dataset, our findings, and source code are publicly available for research purposes.- Anthology ID:
- 2022.lrec-1.283
- Volume:
- Proceedings of the Thirteenth Language Resources and Evaluation Conference
- Month:
- June
- Year:
- 2022
- Address:
- Marseille, France
- Editors:
- Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 2642–2651
- Language:
- URL:
- https://aclanthology.org/2022.lrec-1.283
- DOI:
- Cite (ACL):
- Jan Philip Wahle, Terry Ruas, Saif Mohammad, and Bela Gipp. 2022. D3: A Massive Dataset of Scholarly Metadata for Analyzing the State of Computer Science Research. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 2642–2651, Marseille, France. European Language Resources Association.
- Cite (Informal):
- D3: A Massive Dataset of Scholarly Metadata for Analyzing the State of Computer Science Research (Wahle et al., LREC 2022)
- PDF:
- https://preview.aclanthology.org/autopr/2022.lrec-1.283.pdf
- Code
- gipplab/d3-dataset
- Data
- D3, S2ORC