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Title:Methods metadata: curating scientific research data for reuse
Author(s):Chao, Tiffany C.
Director of Research:Palmer, Carole L.
Doctoral Committee Chair(s):Palmer, Carole L.
Doctoral Committee Member(s):Blake, Catherine L; Greenberg, Jane; Wander, Michelle M.
Department / Program:Library & Information Science
Discipline:Library & Information Science
Degree Granting Institution:University of Illinois at Urbana-Champaign
Data curation
Data reuse
Data sharing
Abstract:The sharing and reuse of research data relies on the provision of metadata and documentation. At present, scientists are not prepared to invest in the kind of rich description that will offer high functionality and interoperability in large-scale networked data systems. The absence of metadata not only makes data difficult to share and use but also increases the likelihood that these data will be lost, thereby diminishing the validity of the research data are associated with and leaving the potential value of the data for reuse unfulfilled and wasted. Further exacerbating this problem is the growing amount and heterogeneity of research data being generated and increased expectations from the federal government and publishers for public access to data. Current efforts of data curators and managers to procure metadata from these data producers are highly time-intensive and an alternative approach is needed. This study investigates how research practices for data production conducted in the Earth Sciences can provide information about data that can be used for metadata description. The research methods implemented by scientists are an essential part of the data generation process and are important for metadata inclusion. Using a case study approach, I address what metadata for methods, or methods metadata, can be derived from two different sources of evidence: qualitative interviews conducted with data producers and content analysis of journal articles collected across three subdisciplines of Earth Science. Research areas such as the Earth Sciences already have scientists producing and working with a variety of data in need of curation support. Having a better understanding of how description for data can be systematically generated from both direct engagement with scientists and from use of the unobtrusive approach of analyzing research publications provides insight into ways to improve and support metadata development for data curators in research library, data repository, and archive environments and enhance data for sharing and reuse.
Issue Date:2015-07-14
Rights Information:Copyright 2015 Tiffany C. Chao
Date Available in IDEALS:2015-09-29
Date Deposited:August 201

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