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  • × author_ss:"Sbaffi, L."
  • × year_i:[2020 TO 2030}
  1. Huang, Y.; Cox, A.M.; Sbaffi, L.: Research data management policy and practice in Chinese university libraries (2021) 0.00 
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    Abstract
    On April 2, 2018, the State Council of China formally released a national Research Data Management (RDM) policy "Measures for Managing Scientific Data". In this context and given that university libraries have played an important role in supporting RDM at an institutional level in North America, Europe, and Australasia, the aim of this article is to explore the current status of RDM in Chinese universities, in particular how university libraries have been involved in taking the agenda forward. This article uses a mixed-methods data collection approach and draws on a website analysis of university policies and services; a questionnaire for university librarians; and semi-structured interviews. Findings indicate that Research Data Service at a local level in Chinese Universities are in their infancy. There is more evidence of activity in developing data repositories than support services. There is little development of local policy. Among the explanations of this may be the existence of a national-level infrastructure for some subject disciplines, the lack of professionalization of librarianship, and the relatively weak resonance of openness as an idea in the Chinese context.
    Type
    a
  2. Sbaffi, L.; Zhao, C.: Modeling the online health information seeking process : information channel selection among university students (2020) 0.00 
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    Abstract
    This study investigates the influence of individual and information characteristics on university students' information channel selection (that is, search engines, social question & answer sites, online health websites, and social networking sites) of online health information (OHI) for three different types of search tasks (factual, exploratory, and personal experience). Quantitative data were collected via an online questionnaire distributed to students on various postgraduate programs at a large UK university. In total, 291 responses were processed for descriptive statistics, Principal Component Analysis, and Poisson regression. Search engines are the most frequently used among the four channels of information discussed in this study. Credibility, ease of use, style, usefulness, and recommendation are the key factors influencing users' judgments of information characteristics (explaining over 62% of the variance). Poisson regression indicated that individuals' channel experience, age, student status, health status, and triangulation (comparing sources) as well as style, credibility, usefulness, and recommendation are substantive predictors for channel selection of OHI.
    Type
    a

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