{"title":"材料数据平台——数据驱动材料科学的公平系统","authors":"M. Tanifuji, Asahiko Matsuda, Hideki Yoshikawa","doi":"10.1109/IIAI-AAI.2019.00206","DOIUrl":null,"url":null,"abstract":"We have identified five important approaches as requirements for a FAIR (findable, accessible, interoperable, reusable) materials data platform. To realize these, we are designing a data platform that consists of about ten interconnected subsystems. We aim to incorporate next generation repository (NGR) concepts into our platform; the subsystems share features such as persistent identifier (PID) based resource management, a common metadata model, and vocabulary control. Another vital requirement is that all datasets must be machine-readable and translatable. These features are highly important in developing a platform as a research pipeline capable of handling various materials data – from data creation and efficient collection, to advanced data usage, secure storage, and open publishing.","PeriodicalId":136474,"journal":{"name":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Materials Data Platform - a FAIR System for Data-Driven Materials Science\",\"authors\":\"M. Tanifuji, Asahiko Matsuda, Hideki Yoshikawa\",\"doi\":\"10.1109/IIAI-AAI.2019.00206\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We have identified five important approaches as requirements for a FAIR (findable, accessible, interoperable, reusable) materials data platform. To realize these, we are designing a data platform that consists of about ten interconnected subsystems. We aim to incorporate next generation repository (NGR) concepts into our platform; the subsystems share features such as persistent identifier (PID) based resource management, a common metadata model, and vocabulary control. Another vital requirement is that all datasets must be machine-readable and translatable. These features are highly important in developing a platform as a research pipeline capable of handling various materials data – from data creation and efficient collection, to advanced data usage, secure storage, and open publishing.\",\"PeriodicalId\":136474,\"journal\":{\"name\":\"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IIAI-AAI.2019.00206\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IIAI-AAI.2019.00206","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Materials Data Platform - a FAIR System for Data-Driven Materials Science
We have identified five important approaches as requirements for a FAIR (findable, accessible, interoperable, reusable) materials data platform. To realize these, we are designing a data platform that consists of about ten interconnected subsystems. We aim to incorporate next generation repository (NGR) concepts into our platform; the subsystems share features such as persistent identifier (PID) based resource management, a common metadata model, and vocabulary control. Another vital requirement is that all datasets must be machine-readable and translatable. These features are highly important in developing a platform as a research pipeline capable of handling various materials data – from data creation and efficient collection, to advanced data usage, secure storage, and open publishing.