首页|Biological Classification System Knowledge Graph and Semi-automatic Construction of Its Invertebrate Fossil Branches

Biological Classification System Knowledge Graph and Semi-automatic Construction of Its Invertebrate Fossil Branches

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Biological classification is the foundation of biology and paleontology,as it arranges all the organisms in a hierarchy that humans can easily follow and understand.It is further used to recon-struct the evolution of life.A biological classification system(BCS)that includes all the established fos-sil taxa would be both useful and challenging for uncovering the life history.Since fossil taxa were origi-nally recorded in various published books and articles written by natural languages,the primary step is to organize all those taxa information in a manner that can be deciphered by a computer system.A Knowledge Graph(KG)is a formalized description framework of semantic knowledge,which repre-sents and retrieves knowledge in a machine-understandable way,and therefore provides an eligible method to represent the BCS.In this paper,a model of the BCS KG including the ontology and fact lay-ers is presented.To put it into practice,the ontology layer of the invertebrate fossil branches was manu-ally developed,while the fact layer was automatically constructed by extracting information from 46 volumes of the Treatise of Invertebrate Paleontology series with the help of natural language process-ing technology.As a result,27 348 taxa nodes spanning fourteen taxonomic ranks were extracted with high accuracy and high efficiency,and the invertebrate fossil branches of the BCS KG was thus in-stalled.This study demonstrates that a properly designed KG model and its automatic construction with the help of natural language processing are reliable and efficient.

biological classification systemknowledge graphontologyinvertebrate fossilbig data

Shaochun Dong、Yukun Shi、Yizao Ran、Haijun Wu、Yiying Deng、Junxuan Fan、Xinyu Dai

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School of Earth Sciences and Engineering,Frontiers Science Center for Critical Earth Material Cycling,Nanjing University,Nanjing 210046,China

Jiangsu Deep-Time Digital Earth Research Center for Excellence,Suzhou 215004,China

School of Computer Science,Nanjing University,Nanjing 210046,China

School of Resources and Environmental Engineering,Hefei University of Technology,Hefei 230009,China

State Key Laboratory for Mineral Deposits Research,Nanjing 210046,China

National Key Laboratory for Novel Software Technology,Nanjing 210046,China

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2024

10.1007/s12583-023-1941-y

地球科学学刊(英文版)
中国地质大学

地球科学学刊(英文版)

CSTPCD
影响因子：0.724
ISSN：1674-487X
年,卷(期)：2024.35(6)