A user-oriented interface for informetrics

A User-oriented interface for generalized informetric analysis based on applying advanced data modelling techniques

Järvelin, Kalervo
Departments of Computer Science and Information Studies
University of Tampere
P.O.Box 607
FIN-33101 TAMPERE, Finland

Ingwersen, Peter
Royal School of Library and Information Science
Birketinget 6
DK-2300 COPENHAGEN S, Denmark

Niemi, Timo
Departments of Computer Science and Information Studies
University of Tampere
P.O.Box 607
FIN-33101 TAMPERE, Finland

Järvelin, K. & Ingwersen, P. & Niemi, T. (2000). A User-oriented interface for generalized informetric analysis based on applying advanced data modelling techniques. Accepted for publication.

Abstract

This article presents a novel user-oriented interface for generalized informetric analysis and demonstrates how informetric calculations can easily and declaratively be specified through advanced data modeling techniques. The interface is declarative and at a high level. Therefore it is easy to use, flexible, and extensible. It enables end-users to perform basic informetric ad hoc calculations easily and often with much less effort than in the contemporary online retrieval systems. It also provides several fruitful generalizations of typical informetric measurements like impact factors. These are based on substituting traditional foci of analysis, for instance journals, by other object types, such as authors, organizations, or countries. In the interface, bibliographic data are modeled as complex objects (non-first normal form relations) and terminological and citation networks involving transitive relationships are modeled as binary relations for deductive processing. The interface is flexible, because it makes it trivial to switch focus between various object types for informetric calculations, e.g. from authors to institutions. Moreover, it is demonstrated that all informetric data can easily be broken down by criteria that foster advanced analysis, e.g., by years or content-bearing attributes. Such modeling allows flexible data aggregation along many dimensions. These salient features emerge from the query interfaceÕs general data restructuring and aggregation capabilities combined with transitive processing capabilities. The features are illustrated by means of sample queries and results in the article.

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