{"title":"获取他们的“第一个”数据集:一门研究生课程,带领博士生完成论文数据的管理","authors":"Megan Sapp Nelson, N. Kong","doi":"10.29173/iq971","DOIUrl":null,"url":null,"abstract":"The data set accompanying theses is a valuable intellectual property asset, both from the viewpoint of the PhD student, who can procure employment and build publications and research grants from the work for years to come, and the university, which owns the data and has invested in the work. However, the data set has generally not been captured as a finished product in a similar manner to the published thesis. A course has been developed which walks PhD students through the process of identifying an archival data set, selecting a repository or long term storage location, creating metadata and documentation for the data package, and the deposit process. A pre- and post assessment has been designed to ascertain the level of data literacy the students gain through curating their own dataset. PIs for the projects have input into the repositories and metadata standards selected. The university thesis office was consulted as the course was developed, so that accurate procedures and practices are reflected throughout the course. This first of a kind class is open to students of any discipline at a Research-1 university. The resulting mixture of data types creates a unique course every time it is offered.","PeriodicalId":84870,"journal":{"name":"IASSIST quarterly","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Capturing their “first” dataset: A graduate course to walk PhD students through the curation of their dissertation data\",\"authors\":\"Megan Sapp Nelson, N. Kong\",\"doi\":\"10.29173/iq971\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The data set accompanying theses is a valuable intellectual property asset, both from the viewpoint of the PhD student, who can procure employment and build publications and research grants from the work for years to come, and the university, which owns the data and has invested in the work. However, the data set has generally not been captured as a finished product in a similar manner to the published thesis. A course has been developed which walks PhD students through the process of identifying an archival data set, selecting a repository or long term storage location, creating metadata and documentation for the data package, and the deposit process. A pre- and post assessment has been designed to ascertain the level of data literacy the students gain through curating their own dataset. PIs for the projects have input into the repositories and metadata standards selected. The university thesis office was consulted as the course was developed, so that accurate procedures and practices are reflected throughout the course. This first of a kind class is open to students of any discipline at a Research-1 university. The resulting mixture of data types creates a unique course every time it is offered.\",\"PeriodicalId\":84870,\"journal\":{\"name\":\"IASSIST quarterly\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IASSIST quarterly\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.29173/iq971\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IASSIST quarterly","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.29173/iq971","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Capturing their “first” dataset: A graduate course to walk PhD students through the curation of their dissertation data
The data set accompanying theses is a valuable intellectual property asset, both from the viewpoint of the PhD student, who can procure employment and build publications and research grants from the work for years to come, and the university, which owns the data and has invested in the work. However, the data set has generally not been captured as a finished product in a similar manner to the published thesis. A course has been developed which walks PhD students through the process of identifying an archival data set, selecting a repository or long term storage location, creating metadata and documentation for the data package, and the deposit process. A pre- and post assessment has been designed to ascertain the level of data literacy the students gain through curating their own dataset. PIs for the projects have input into the repositories and metadata standards selected. The university thesis office was consulted as the course was developed, so that accurate procedures and practices are reflected throughout the course. This first of a kind class is open to students of any discipline at a Research-1 university. The resulting mixture of data types creates a unique course every time it is offered.