{"title":"社会科学研究数据管理:再利用问题","authors":"Guangyuan Sun, Christopher S. G. Khoo","doi":"10.15291/LIBELLARIUM.V9I2.291","DOIUrl":null,"url":null,"abstract":"Data curation is attracting a growing interest in the library and information science community. The main purpose of data curation is to support data reuse. This paper discusses the issues of reusing quantitative social science data from three perspectives of searching and browsing for datasets, evaluating the reusability of datasets (including evaluating topical relevance, utility and data quality), and integrating datasets, by comparing dataset searching with online database searching. The paper also discusses using knowledge representation techniques of metadata and ontology, and a graphical visualization interface to support users in browsing, assessing and integrating datasets.","PeriodicalId":30549,"journal":{"name":"Libellarium Journal for the Research of Writing Books and Cultural Heritage Institutions","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Social science research data curation: issues of reuse\",\"authors\":\"Guangyuan Sun, Christopher S. G. Khoo\",\"doi\":\"10.15291/LIBELLARIUM.V9I2.291\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Data curation is attracting a growing interest in the library and information science community. The main purpose of data curation is to support data reuse. This paper discusses the issues of reusing quantitative social science data from three perspectives of searching and browsing for datasets, evaluating the reusability of datasets (including evaluating topical relevance, utility and data quality), and integrating datasets, by comparing dataset searching with online database searching. The paper also discusses using knowledge representation techniques of metadata and ontology, and a graphical visualization interface to support users in browsing, assessing and integrating datasets.\",\"PeriodicalId\":30549,\"journal\":{\"name\":\"Libellarium Journal for the Research of Writing Books and Cultural Heritage Institutions\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-03-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Libellarium Journal for the Research of Writing Books and Cultural Heritage Institutions\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15291/LIBELLARIUM.V9I2.291\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Libellarium Journal for the Research of Writing Books and Cultural Heritage Institutions","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15291/LIBELLARIUM.V9I2.291","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Social science research data curation: issues of reuse
Data curation is attracting a growing interest in the library and information science community. The main purpose of data curation is to support data reuse. This paper discusses the issues of reusing quantitative social science data from three perspectives of searching and browsing for datasets, evaluating the reusability of datasets (including evaluating topical relevance, utility and data quality), and integrating datasets, by comparing dataset searching with online database searching. The paper also discusses using knowledge representation techniques of metadata and ontology, and a graphical visualization interface to support users in browsing, assessing and integrating datasets.