jpwahle commited on
Commit
fd04e4f
1 Parent(s): 679dae3

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +3 -10
README.md CHANGED
@@ -51,13 +51,8 @@ task_ids: []
51
  - [Citation Information](#citation-information)
52
  - [Contributions](#contributions)
53
  ## Dataset Description
54
- - **Homepage:**
55
- - **Repository:**
56
- https://github.com/jpwahle/lrec22-d3-dataset
57
- - **Paper:**
58
- https://aclanthology.org/2022.lrec-1.283/
59
- - **Leaderboard:**
60
- - **Point of Contact:**
61
  ### Dataset Summary
62
  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.
63
  ### Supported Tasks and Leaderboards
@@ -107,12 +102,10 @@ English
107
  `papers` and `authors`
108
  ## Dataset Creation
109
  ### Curation Rationale
110
- [More Information Needed]
111
  ### Source Data
112
  #### Initial Data Collection and Normalization
113
  DBLP and from v2.0 SemanticScholar
114
- #### Who are the source language producers?
115
- [More Information Needed]
116
  ## Additional Information
117
  ### Dataset Curators
118
  [Jan Philip Wahle](https://jpwahle.com/)
 
51
  - [Citation Information](#citation-information)
52
  - [Contributions](#contributions)
53
  ## Dataset Description
54
+ - **Repository:** https://github.com/jpwahle/lrec22-d3-dataset
55
+ - **Paper:** https://aclanthology.org/2022.lrec-1.283/
 
 
 
 
 
56
  ### Dataset Summary
57
  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.
58
  ### Supported Tasks and Leaderboards
 
102
  `papers` and `authors`
103
  ## Dataset Creation
104
  ### Curation Rationale
105
+ Providing a resource to analyze the state of computer science research statistically and semantically.
106
  ### Source Data
107
  #### Initial Data Collection and Normalization
108
  DBLP and from v2.0 SemanticScholar
 
 
109
  ## Additional Information
110
  ### Dataset Curators
111
  [Jan Philip Wahle](https://jpwahle.com/)