Object-relational data modelling for informetric databases

Hairong Yu, Mari Davis, Concepción S. Wilson and Fletcher T.H. Cole

Journal of Informetrics, 2008, vol. 2, issue 3, 240-251

Abstract: Informetric researchers have long chafed at the limitations of bibliographic databases for their analyses, without being able to visualize or develop real solutions to the problem. This paper describes a solution developed to provide for the specialist needs of informetric researchers. In a collaborative exercise between the fields of computer science and informetrics, data modelling was used in order to address the requirements of complex and dynamic informetric data. This paper reports on this modelling experience with its aim of building an object-relational database (ORDB) for informetric research purposes. The paper argues that ORM (object-relational model) is particularly suitable because it allows for the modelling of complex data and accommodates the various data source formats and standards used by a variety of bibliographic databases. Further, ORM captures the dynamic nature of informetric data by allowing user-defined data types and by embedding basic statistical calculating tools as object functions in these user-defined data types. The main ideas of the paper are implemented in an Oracle database management system.

Keywords: Object-relational database systems (ORDB); Complex data modelling; Bibliometrics; Informetrics; Scientometrics; Interdisciplinary application (search for similar items in EconPapers)
Date: 2008
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:2:y:2008:i:3:p:240-251

DOI: 10.1016/j.joi.2008.06.001

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