Multidimensional Data Model and Query Language for Informetrics

Abstract

Multidimensional data analysis or On-line analytical processing (OLAP) offers a single subject-oriented source for analyzing summary data based on various dimensions. We demonstrate that the OLAP approach gives a promising starting point for advanced analysis and comparison among summary data in informetrics applications. At the moment there is no single precise, commonly accepted logical/conceptual model for multidimensional analysis. This is because the requirements of applications vary considerably. We develop a conceptual/logical multidimensional model for supporting the complex and unpredictable needs of informetrics. Summary data are considered with respect of some dimensions. By changing dimensions the user may construct other views on the same summary data. We develop a multidimensional query language whose basic idea is to support the definition of views in a way, which is natural and intuitive for lay users in the informetrics area. We show that this view-oriented query language has a great expressive power and its degree of declarativity is greater than in contemporary operation-oriented or SQL (Structured Query Language)-like OLAP query languages.

Object-relational data modelling for informetric databases

“…In a subsequent paper, Niemi, Hirvonen, and Järvelin (2003) describe a logical/conceptual model for a multi-dimensional database that they have developed for informetric analyses. In this project, they use online analytical processing (OLAP) to focus on the end user's requirements for summary data related to specific aspects of informetric attributes.…”

Graphical Querying of Multidimensional Databases

“…Dimensions are composed of hierarchically ordered attributes which model the different detail levels of the axisdata granularity. Notice that, in spite of a decade of research in OLAP systems, concepts and systems exist without uniform theoretical basis [17,20].…”

Applications of SQL for Informetric Data Processing

“…Their representation of bibliographic references as complex objects permits the study of author, journal, article, citation, and co-citation-based analyses using a specially developed querying approach. Querying of data sets is expanded in Niemi, Hirvonen, and Järvelin (2003), where the authors outline how an online analytic processing (OLAP) approach may be used to model multidimensional data. The authors develop a declarative query language to manipulate the data.…”