TY - JOUR
T1 - PubMed knowledge graph 2.0
T2 - Connecting papers, patents, and clinical trials in biomedical science
AU - Xu, Jian
AU - Yu, Chao
AU - Xu, Jiawei
AU - Torvik, Vetle I.
AU - Kang, Jaewoo
AU - Sung, Mujeen
AU - Song, Min
AU - Bu, Yi
AU - Ding, Ying
N1 - This work was supported by the National Natural Science Foundation of China [Grant Number: 72374233], Natural Science Foundation of Guangdong Province [Grant Number: 2024A1515011778]. We would like to express our sincere gratitude to the reviewers and editors for their meticulous evaluation and insightful suggestions. Their valuable feedback has significantly contributed to the improvement of this manuscript, helping us to refine our work and present a more comprehensive and accurate study.
PY - 2025/6/17
Y1 - 2025/6/17
N2 - Papers, patents, and clinical trials are essential scientific resources in biomedicine, crucial for knowledge sharing and dissemination. However, these documents are often stored in disparate databases with varying management standards and data formats, making it challenging to form systematic and fine-grained connections among them. To address this issue, we construct PKG 2.0, a comprehensive knowledge graph dataset encompassing over 36 million papers, 1.3 million patents, and 0.48 million clinical trials in the biomedical field. PKG 2.0 integrates these dispersed resources through 482 million biomedical entity linkages, 19 million citation linkages, and 7 million project linkages. The construction of PKG 2.0 wove together fine-grained biomedical entity extraction, high-performance author name disambiguation, multi-source citation integration, and high-quality project data from the NIH Exporter. Data validation demonstrates that PKG 2.0 excels in key tasks such as author disambiguation and biomedical entity recognition. This dataset provides valuable resources for biomedical researchers, bibliometric scholars, and those engaged in literature mining.
AB - Papers, patents, and clinical trials are essential scientific resources in biomedicine, crucial for knowledge sharing and dissemination. However, these documents are often stored in disparate databases with varying management standards and data formats, making it challenging to form systematic and fine-grained connections among them. To address this issue, we construct PKG 2.0, a comprehensive knowledge graph dataset encompassing over 36 million papers, 1.3 million patents, and 0.48 million clinical trials in the biomedical field. PKG 2.0 integrates these dispersed resources through 482 million biomedical entity linkages, 19 million citation linkages, and 7 million project linkages. The construction of PKG 2.0 wove together fine-grained biomedical entity extraction, high-performance author name disambiguation, multi-source citation integration, and high-quality project data from the NIH Exporter. Data validation demonstrates that PKG 2.0 excels in key tasks such as author disambiguation and biomedical entity recognition. This dataset provides valuable resources for biomedical researchers, bibliometric scholars, and those engaged in literature mining.
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U2 - 10.1038/s41597-025-05343-8
DO - 10.1038/s41597-025-05343-8
M3 - Article
C2 - 40527887
AN - SCOPUS:105008440222
SN - 2052-4463
VL - 12
JO - Scientific Data
JF - Scientific Data
IS - 1
M1 - 1018
ER -