Maturity Evaluation Of Implementing FAIR Principles In Scientific Data Centers

The rapid renewal and iteration of information technology has affected the behavior pattern of modern science.The broad application prospects of big data and artificial intelligence have brought new challenges and opportunities to scientific data management.Under such circumstances,the fair principle came into being.Many foreign institutions and organizations have taken the fair principle as an important guiding principle of scientific data management.As the carrier of scientific data,the scientific data center implements the fair principle at this level,that is to say,it implements the fair principle at the bottom.In view of the fact that foreign scientific data centers have implemented the fair principle for several years,understanding the fair implementation means and implementation maturity evaluation of foreign scientific data centers will help to deeply understand the concept of the fair principle,understand various indicators of the fair implementation maturity,and provide experience for China’s scientific data centers to implement the fair principle.The main body of this paper consists of five chapters: the first chapter is the introduction.The author describes the research background and significance of this paper in detail,focuses on the research status at home and abroad from the domestic and foreign literature,and expounds the research content,methods and innovation of this paper.The second chapter is the elaboration of related concepts.It mainly analyzes the four basic principles that constitute fair principles,namely,discoverable,obtainable,interoperable and reusable,and their 15 subdivision principles in detail.It also introduces the fair data maturity index and the fairs fair maturity index of research data alliance RDA.The third chapter mainly introduces the specific measures taken by WDCC to implement the fair principle.First,the general situation of WDCC is introduced.Secondly,the implementation status of WDCC management level is investigated.Then,the four aspects of implementing fair principles in WDCC data level are disassembled in detail through network research and literature research.The implementation means and methods of WDCC are introduced in detail in 15 rules.It is found that WDCC has corresponding implementation means in the four aspects of fair principles.Then,in order to measure the effect of fair implementation of WDCC,the evaluation method of fair implementation maturity is introduced in detail in Chapter 4.The fair data maturity model of research data alliance RDA is used to evaluate the fair maturity of WDCC manually.Then,the fairsfair dataset evaluation tool f-uji is introduced,and the tool is used to automatically evaluate the fair implementation maturity of WDCC.According to certain rules,sample datasets are selected from the WDCC database for testing.The fair maturity of datasets with different granularity is analyzed according to the granularity of sample data.It is found that datasets with larger granularity perform better in fair maturity.The results of the two evaluation methods show that the maturity of WDCC’s fair implementation is generally good.Compared with the inspection results and the implementation status of Chapter III,it is found that WDCC still has many problems in "discoverable" and "reusable" aspects that need to be further improved.The sixth chapter is the summary,enlightenment and outlook.It mainly summarizes this research,explains the enlightenment obtained from the research,points out the shortcomings of the analysis and research,and puts forward the thinking and outlook for the follow-up related research.