Multidimensional Data Model and Query Language for Informetrics
Article first published online: 20 MAY 2003
Published 2003 Wiley Periodicals, Inc.
Journal of the American Society for Information Science and Technology
Volume 54, Issue 10, pages 939–951, August 2003
How to Cite
Niemi, T., Hirvonen, L. and Järvelin, K. (2003), Multidimensional Data Model and Query Language for Informetrics. J. Am. Soc. Inf. Sci., 54: 939–951. doi: 10.1002/asi.10290
- Issue published online: 25 JUN 2003
- Article first published online: 20 MAY 2003
- Manuscript Revised: 11 FEB 2003
- Manuscript Accepted: 11 FEB 2003
- Manuscript Received: 5 SEP 2002
- Academy of Finland. Grant Number: 52894
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.