{"title":"数据科学及其在大型神经科学合作中的未来。","authors":"Manuel Schottdorf, Guoqiang Yu, Edgar Y Walker","doi":"10.1016/j.neuron.2024.08.017","DOIUrl":null,"url":null,"abstract":"<p><p>Collaborative neuroscience requires systematic data management and analysis. How this is best done in practice remains unclear. Based on a survey across collaborative neuroscience projects, we document the current state of the art focusing on data integration, sharing, and researcher training. We propose best practices and list actions and policies to attain these goals.</p>","PeriodicalId":19313,"journal":{"name":"Neuron","volume":"112 18","pages":"3007-3012"},"PeriodicalIF":14.7000,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Data science and its future in large neuroscience collaborations.\",\"authors\":\"Manuel Schottdorf, Guoqiang Yu, Edgar Y Walker\",\"doi\":\"10.1016/j.neuron.2024.08.017\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Collaborative neuroscience requires systematic data management and analysis. How this is best done in practice remains unclear. Based on a survey across collaborative neuroscience projects, we document the current state of the art focusing on data integration, sharing, and researcher training. We propose best practices and list actions and policies to attain these goals.</p>\",\"PeriodicalId\":19313,\"journal\":{\"name\":\"Neuron\",\"volume\":\"112 18\",\"pages\":\"3007-3012\"},\"PeriodicalIF\":14.7000,\"publicationDate\":\"2024-09-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Neuron\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1016/j.neuron.2024.08.017\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neuron","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.neuron.2024.08.017","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
Data science and its future in large neuroscience collaborations.
Collaborative neuroscience requires systematic data management and analysis. How this is best done in practice remains unclear. Based on a survey across collaborative neuroscience projects, we document the current state of the art focusing on data integration, sharing, and researcher training. We propose best practices and list actions and policies to attain these goals.
期刊介绍：
Established as a highly influential journal in neuroscience, Neuron is widely relied upon in the field. The editors adopt interdisciplinary strategies, integrating biophysical, cellular, developmental, and molecular approaches alongside a systems approach to sensory, motor, and higher-order cognitive functions. Serving as a premier intellectual forum, Neuron holds a prominent position in the entire neuroscience community.
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