{"title":"生物数据可持续性悖论","authors":"Terence R. Johnson, Philip E. Bourne","doi":"arxiv-2311.05668","DOIUrl":null,"url":null,"abstract":"Biological data in digital form has become a, if not the, driving force\nbehind innovations in biology, medicine, and the environment. No study and no\nmodel would be complete without access to digital data (including text)\ncollected by others and available in public repositories. With this ascent in\nthe fundamental importance of data for reproducible scientific progress has\ncome a troubling paradox.","PeriodicalId":501219,"journal":{"name":"arXiv - QuanBio - Other Quantitative Biology","volume":"4 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Biological Data Sustainability Paradox\",\"authors\":\"Terence R. Johnson, Philip E. Bourne\",\"doi\":\"arxiv-2311.05668\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Biological data in digital form has become a, if not the, driving force\\nbehind innovations in biology, medicine, and the environment. No study and no\\nmodel would be complete without access to digital data (including text)\\ncollected by others and available in public repositories. With this ascent in\\nthe fundamental importance of data for reproducible scientific progress has\\ncome a troubling paradox.\",\"PeriodicalId\":501219,\"journal\":{\"name\":\"arXiv - QuanBio - Other Quantitative Biology\",\"volume\":\"4 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-11-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - QuanBio - Other Quantitative Biology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2311.05668\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuanBio - Other Quantitative Biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2311.05668","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Biological data in digital form has become a, if not the, driving force
behind innovations in biology, medicine, and the environment. No study and no
model would be complete without access to digital data (including text)
collected by others and available in public repositories. With this ascent in
the fundamental importance of data for reproducible scientific progress has
come a troubling paradox.