1. Overview
The AMiner team is proud to unveil the latest evolution of the Open Academic Graph (OAG) with the official release of Version 3.2. Building upon the foundational Version 3.0 dataset first introduced in 2023, this iteration represents a significant leap forward in academic knowledge graph construction and data reliability.
As the world's most comprehensive heterogeneous academic graph encompassing papers, authors, institutions, and publication venues, OAG 3.2 introduces groundbreaking improvements through our enhanced data fusion framework. Our engineering team has implemented two core advancements:
- Duplicate Paper Resolution System
- Intelligent Relationship Mapping
The OAG 3.3 dataset now includes:
- 170,897,622 papers (2000-2026)
- 34,443,192 researcher profiles
- 331,779 academic institutions
- 95,811 journals/conference series
For detailed technical specifications and access options, please visit:
2. Data Statistics
Table1: Node Statistics
| Dataset | Count |
|---|---|
| Affiliation | 331,779 |
| Venue | 95,811 |
| Person | 34,443,192 |
| Publication | 170,897,622 |
Table2: Edge Statistics
| Lable | Count |
|---|---|
| Pub-Pub[Reference] | 1,269,112,709 |
| PubAuthor-Org | 223,504,560 |
| PubAuthor-Person | 378,158,989 |
| Pub-Venue | 64,646,216 |
3. Data Schema
Table3: Affiliation Schema
| Field Name | Field Type | Description | Example |
|---|---|---|---|
| id | string/long | affiliation id | 6bf574641c5a1dcdd96f88c |
| name | string | affiliation name | Harvard University |
Table4: Venue Schema
| Field Name | Field Type | Description | Example |
|---|---|---|---|
| id | string/long | venue id | 5bf574641c5a1dcdd96f817b |
| type | string | Journal/Conference | Journal |
| name | string | normalized venue name | nature |
Table5: Person Schema
| Field Name | Field Type | Description | Example |
|---|---|---|---|
| id | string/long | author id | 53f42f36dabfaedce54dcd0c |
| name | string | author name | Jiawei Han |
| org | string | author organization | Department of Computer Science, University of Illinois at Urbana-Champaign |
Table6: Publication Schema
| Field Name | Field Type | Description | Example |
|---|---|---|---|
| id | string/long | paper ID | 53e9ab9eb7602d970354a97e |
| title | string | paper title | Data mining: concepts and techniques |
| authors.name | string | author name | Jiawei Han |
| author.org | string | author affiliation | Department of Computer Science, University of Illinois at Urbana-Champaign |
| author.org_id | long | author affiliation id | 157725225 |
| author.id | string/long | author ID | 53f42f36dabfaedce54dcd0c |
| venue_id | string/long | paper venue ID | 53e17f5b20f7dfbc07e8ac6e |
| venue | string | paper venue name | Inteligencia Artificial, Revista Iberoamericana de Inteligencia Artificial |
| year | int | published year | 2000 |
| keywords | list of strings | keywords | ["data mining", "structured data", "world wide web", "social network", "relational data"] |
| references | list of long | paper references | [53e9ab9eb7602d970354a97f, 53e9ab9eb7602d970354a98e, 53e9ab9eb7602d970354a97d, 53e9ab9eb7602d970354a97a] |
| n_citation | string | citation number | 82 |
| doi | string | doi | 10.4114/ia.v10i29.873 |
| abstract | string | abstract | Our ability to generate... |
4. Downloads
- Affiliation
- Venue
- Person
- Publication
5. References
We kindly request that any published research that makes use of this data cites the following papers.
Jie Tang, Jing Zhang, Limin Yao, Juanzi Li, Li Zhang, and Zhong Su. ArnetMiner: Extraction and Mining of Academic Social Networks. In Proceedings of the Fourteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD'2008). pp.990-998. [PDF] [Slides] [System] [API]
Fanjin Zhang, Xiao Liu, Jie Tang, Yuxiao Dong, Peiran Yao, Jie Zhang, Xiaotao Gu, Yan Wang, Bin Shao, Rui Li, and Kuansan Wang. OAG: Toward Linking Large-scale Heterogeneous Entity Graphs. In Proceedings of the Twenty-Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'19).
Fanjin Zhang, Xiao Liu, Jie Tang, Yuxiao Dong, Peiran Yao, Jie Zhang, Xiaotao Gu, Yan Wang, Evgeny Kharlamov, Bin Shao, Rui Li, and Kuansan Wang. OAG: Linking Entities across Large-Scale Heterogeneous Knowledge Graphs. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022.
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