Social science research data curation
Author(s) -
Guangyuan Sun,
Christopher S. G. Khoo
Publication year - 2017
Publication title -
libellarium journal for research in the field of information and related sciences
Language(s) - English
Resource type - Journals
eISSN - 1846-9213
pISSN - 1846-8527
DOI - 10.15291/libellarium.v9i2.291
Subject(s) - computer science , data curation , metadata , data science , reuse , relevance (law) , information retrieval , ontology , visualization , interface (matter) , world wide web , data mining , ecology , philosophy , epistemology , bubble , maximum bubble pressure method , parallel computing , political science , law , biology
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.
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