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|Title:||Knowledge representation of social science quantitative research data for data curation and reuse||Authors:||Sun, Guangyuan||Keywords:||Library and information science::Knowledge management||Issue Date:||2019||Source:||Sun, G. (2019). Knowledge representation of social science quantitative research data for data curation and reuse. Doctoral thesis, Nanyang Technological University, Singapore.||Abstract:||Data curation refers to the management of data sets (usually research data) to make them available for use by other researchers beyond the lifespan and purpose of the project for which the data was collected. The value of data curation lies in value-addition to existing data to support data reuse. The scope of the study is the curation of quantitative social science research data, particularly publicly available data sets collected using survey questionnaires. The assumed context of the study is a data repository system (such as the Inter-university Consortium for Political and Social Research, and the UK Data Archive) that provides user access to curated research data and supports researchers in searching, browsing, assessing and manipulating the curated data. The objectives of this study were: 1) to identify the user requirements for a data repository system to support the reuse of curated quantitative social science research data; 2) to develop a knowledge representation system for data repository systems to support the reuse of quantitative social science research data.||URI:||https://hdl.handle.net/10356/107575
|Fulltext Permission:||embargo_20211201||Fulltext Availability:||With Fulltext|
|Appears in Collections:||WKWSCI Theses|
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