Ten challenges in modeling bibliographic data for bibliometric analysis

Alfio Ferrara () and Silvia Salini ()
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Alfio Ferrara: Università degli Studi di Milano

Scientometrics, 2012, vol. 93, issue 3, No 12, 765-785

Abstract: Abstract The complexity and variety of bibliographic data is growing, and efforts to define new methodologies and techniques for bibliometric analysis are intensifying. In this complex scenario, one of the most crucial issues is the quality of data and the capability of bibliometric analysis to cope with multiple data dimensions. Although the problem of enforcing a multidimensional approach to the analysis and management of bibliographic data is not new, a reference design pattern and a specific conceptual model for multidimensional analysis of bibliographic data are still missing. In this paper, we discuss ten of the most relevant challenges for bibliometric analysis when dealing with multidimensional data, and we propose a reference data model that, according to different goals, can help analysis designers and bibliographic experts in working with large collections of bibliographic data.

Keywords: Dimensional data modeling; Multivariate statistics; Multidimensional data analysis; Topics models (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (9)

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DOI: 10.1007/s11192-012-0810-x

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