jpwahle/dblp-discovery-dataset

Dataset Card for DBLP Discovery Dataset (D3)

Dataset Summary

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.

Supported Tasks and Leaderboards

[More Information Needed]

Languages

English

Dataset Structure

Data Instances

Total size: 8.71 GB Papers size: 8.13 GB Authors size: 0.58 GB

Data Fields

Papers

Feature	Description
corpusid	The unique identifier of the paper.
externalids	The same paper in other repositories (e.g., DOI, ACL).
title	The title of the paper.
authors	The authors of the paper with their authorid and name.
venue	The venue of the paper.
year	The year of the paper publication.
publicationdate	A more precise publication date of the paper.
abstract	The abstract of the paper.
outgoingcitations	The number of references of the paper.
ingoingcitations	The number of citations of the paper.
isopenaccess	Whether the paper is open access.
influentialcitationcount	The number of influential citations of the paper according to SemanticScholar.
s2fieldsofstudy	The fields of study of the paper according to SemanticScholar.
publicationtypes	The publication types of the paper.
journal	The journal of the paper.
updated	The last time the paper was updated.
url	A url to the paper in SemanticScholar.

Authors

Feature	Description
authorid	The unique identifier of the author.
externalids	The same author in other repositories (e.g., ACL, PubMed). This can include ORCID
name	The name of the author.
affiliations	The affiliations of the author.
homepage	The homepage of the author.
papercount	The number of papers the author has written.
citationcount	The number of citations the author has received.
hindex	The h-index of the author.
updated	The last time the author was updated.
email	The email of the author.
s2url	A url to the author in SemanticScholar.

Data Splits

• papers
• authors

Dataset Creation

Curation Rationale

Providing a resource to analyze the state of computer science research statistically and semantically.

Source Data

Initial Data Collection and Normalization

DBLP and from v2.0 SemanticScholar

Additional Information

Dataset Curators

Jan Philip Wahle

Licensing Information

The DBLP Discovery Dataset is released under the CC BY-NC 4.0. By using this corpus, you are agreeing to its usage terms.

Citation Information

If you use the dataset in any way, please cite:

@inproceedings{Wahle2022c,
  title        = {D3: A Massive Dataset of Scholarly Metadata for Analyzing the State of Computer Science Research},
  author       = {Wahle, Jan Philip and Ruas, Terry and Mohammad, Saif M. and Gipp, Bela},
  year         = {2022},
  month        = {July},
  booktitle    = {Proceedings of The 13th Language Resources and Evaluation Conference},
  publisher    = {European Language Resources Association},
  address      = {Marseille, France},
  doi          = {},
}

Also make sure to cite the following papers if you use SemanticScholar data:

@inproceedings{ammar-etal-2018-construction,
    title = "Construction of the Literature Graph in Semantic Scholar",
    author = "Ammar, Waleed  and
      Groeneveld, Dirk  and
      Bhagavatula, Chandra  and
      Beltagy, Iz",
    booktitle = "Proceedings of the 2018 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 3 (Industry Papers)",
    month = jun,
    year = "2018",
    address = "New Orleans - Louisiana",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/N18-3011",
    doi = "10.18653/v1/N18-3011",
    pages = "84--91",
}

@inproceedings{lo-wang-2020-s2orc,
    title = "{S}2{ORC}: The Semantic Scholar Open Research Corpus",
    author = "Lo, Kyle  and Wang, Lucy Lu  and Neumann, Mark  and Kinney, Rodney  and Weld, Daniel",
    booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
    month = jul,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/2020.acl-main.447",
    doi = "10.18653/v1/2020.acl-main.447",
    pages = "4969--4983"
}
```### Contributions
Thanks to [@jpwahle](https://github.com/jpwahle) for adding this dataset.