Karel Hynek, Jan Luxemburk, Jaroslav Pešek, Tomáš Čejka, Pavel Šiška
{"title":"Author Correction: CESNET-TLS-Year22: A year-spanning TLS network traffic dataset from backbone lines.","authors":"Karel Hynek, Jan Luxemburk, Jaroslav Pešek, Tomáš Čejka, Pavel Šiška","doi":"10.1038/s41597-024-04055-9","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":21597,"journal":{"name":"Scientific Data","volume":"11 1","pages":"1199"},"PeriodicalIF":5.8000,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11538410/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Data","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41597-024-04055-9","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
期刊介绍：
Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data.
The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
