Research On The Organization And Visualization Of Cross-platform Medical Science Datasets

With the development of the new era,science and technology and Internet technology have made new breakthroughs and achievements in different stages,and the degree of information and intelligence of the society has also been deepened,and a large number of scientific data resources were born here.In terms of scientific research,the value of scientific data is self-evident.High-quality scientific data can not only improve the efficiency of scientific research,but also help researchers generate research results.Scientific data platform is an effective way to help researchers realize the sharing and utilization of scientific data,maximize the value of scientific data quickly,and promote scientific research in various fields.Since the emergence of the novel coronavirus outbreak,scientific research on the novel coronavirus pneumonia has gradually deepened,and related scientific data and concepts have increased rapidly.Therefore,it is of practical significance to organize and integrate COVID-19 scientific data from different platforms in an orderly manner,establish relevant metadata framework,and realize its visualization,while ensuring interoperability between terms.Based on the current medical scientific dataset and the research results of the novel coronavirus knowledge map,this study summarized the research overview of the existing scientific data information resources of the novel coronavirus.Taking the novel coronavirus scientific dataset in Re3 data.org and Data MED as the research object,it made reference to the existing metadata standards.The metadata framework of the COVID-19 scientific dataset is constructed to carry out knowledge extraction and ontology modeling of the COVID-19 scientific data set,and finally realize visual presentation.First,the research status of medical and COVID-19 scientific datasets and knowledge organizations at home and abroad was investigated.Secondly,the structure of scientific data platform Re3 data.org and Data MED and their metadata standard structure are clarified by combing related theories of scientific data concept definition,metadata,ontology,knowledge graph,etc.Thirdly,the content features of the COVID-19 scientific data set are summarized and analyzed,the common attributes among the external features of the scientific dataset resources are summarized,and the metadata framework of the COVID-19 scientific dataset is constructed,which is described from the core metadata and the extended metadata.On this basis,after further mining the content features of the scientific data set of COVID-19,the ontology model is constructed by referring to the existing ontology model and customizing the research feature objects,which to a certain extent realizes the fine-grained description of scientific data resources.Finally,the Neo4 j database was used to deeply reveal the correlation between the scientific datasets of COVID-19 between different platforms.The analysis was carried out from the dimensions of "scientific datasets","institutions","policies" and "categories",and the expansion of the related data was extended from the narrow sense to the broad sense,providing a reference for future resource research based on related data.It provides more possibilities for the development and research of scientific dataset resources.