Article: Monitoring Applications with Process Mining

Name: Article: Monitoring Applications with Process Mining
Creator: Science Data Bank
Published: 2024-01-05T01:10:27+08:00

DataCite Commons2025-04-27 更新2025-04-16 收录

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Three tables created as a support for the article: Monitoring Applications with Process Mining

提供机构：

Science Data Bank

创建时间：

2024-01-05

Da Xing'an Mountains Large Fungi Dataset (2010)

真菌学

生态学研究

a. Data content (data file/table name, including observation index content) The Great Xing'an Mountains Large Fungi Dataset (2010) reflects the species, characteristics, and distribution of fungi in

DataCite Commons2025-04-27 更新110

Remote Sensing Monitoring and Simulation Dataset of Ecological Habitat Quality in the 250m Ecological System of Changbai Mountain and Wanda Mountain Nature Reserve Project Area (2015)

生态监测

遥感技术

a. Data content (data file/table name, including observation index content) This dataset includes remote sensing monitoring and simulation data on the ecosystem service capacity of the Changbai Mount

DataCite Commons2025-04-27 更新70

Mendelian randomization study of the causal association between peripheral blood cell levels and IgA nephropathy

孟德尔随机化

疾病遗传关联

Objective To explore the causal relationship between peripheral blood cell levels (total white blood cells, neutrophils, monocytes, basophils, eosinophils, lymphocytes) and IgA nephropathy, and to pro

DataCite Commons2025-04-27 更新60

Quinoline Alkaloid Derivatives Database

药物化学

抗癌研究

Quinoline alkaloid refers to a class of alkaloids containing quinoline rings in their structure, mainly distributed in rutaceae and rubiaceae plants. The quinoline alkaloids extracted from plants have

DataCite Commons2025-04-27 更新70

North Korea's 30m arable land reduction spatial dataset (1990-2015)

土地变化

地理信息系统

The 30m arable land reduction spatial dataset in North Korea (1990-2015) reflects the spatial distribution of arable land reduction in North Korea from 1990 to 2015.

DataCite Commons2025-04-27 更新60

Article: Monitoring Applications with Process Mining

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