Analysis of Autonomy in Geosciences Data Processing and Analysis Software
field of Earth science involves multi-scale,multi-type,and multi-source data in research,leading to a strong demand for data processing and analysis software.This study,aimed at the characteristics of the earth science field,analyzes the current state of its main data processing and analysis software,identifies the degree of software autonomy in China,and expects to propose corresponding development suggestions.The survey covers 16 topics including geography,oceanography,geology,atmospheric sciences,ecology,disasters,agriculture,etc.,and selects 177 mainstream software/tools,focusing on obtaining indicators such as software/tool names,summaries,main functions,application services/typical cases,advantages and disadvantages,and benchmarking software.The analysis found that these software/tools in the field of geoscience data processing and analysis are completely open(open source)accounting for two-thirds,the last one-thirds are commercial,restrictive,or unknown openness.The main software/tools are developed in countries such as the United States,China,Canada,the United Kingdom,and some international organizations.From the perspective of topic distribution,this is mainly reflected in the following areas:land degradation,socio-economic demographics,knowledge graphs,and remote sensing big data processing.From the perspective of autonomy,the main high-risk software packages are mainly distributed in fields such as spatialization,atmosphere,wildfires,and permafrost.Among the surveyed software/tools,about one-third of the professional software/tool can be applied to the National Science Data Center,and can be used in Cloud Platform.Combining the era of artificial intelligence and the development of"Data Element X",the future should strongly enhance the development and deployment application of China's autonomous scientific data processing software/tool from 5 perspectives.
earth sciencescientific datasoftwareautonomyNational Scientific Data Center
万方数据
维普
