D3: A Massive Dataset of Scholarly Metadata for Analyzing the State of Computer Science Research

TL;DR

This paper introduces D3, a comprehensive dataset of over 6 million computer science publications from DBLP, enabling analysis of research trends, productivity, and impact, with initial findings showing growth and evolving topic focus.

Contribution

The paper presents the creation of D3, a large-scale, publicly available dataset of scholarly metadata, and provides initial analyses of research activity and trends in computer science.

Findings

Computer science research is growing at approximately 15% annually.

Recent papers have more bibliographical entries but fewer citations on average.

Topic trends are clearly reflected in the dataset, D3.

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 (approx. 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.