Prolog-Based Meta-rules for Relational Database Representation and Manipulation
IEEE Transactions on Software Engineering
Building the data warehouse
Implementing data cubes efficiently
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
A data model for supporting on-line analytical processing
CIKM '96 Proceedings of the fifth international conference on Information and knowledge management
An overview of data warehousing and OLAP technology
ACM SIGMOD Record
Maintenance of data cubes and summary tables in a warehouse
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
An array-based algorithm for simultaneous multidimensional aggregates
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
OLAP solutions: building multidimensional information systems
OLAP solutions: building multidimensional information systems
Deductive database languages: problems and solutions
ACM Computing Surveys (CSUR)
A survey of logical models for OLAP databases
ACM SIGMOD Record
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Modeling Multidimensional Databases
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Total
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
Fast Computation of Sparse Datacubes
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Materialized Views Selection in a Multidimensional Database
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
nD-SQL: A Multi-Dimensional Language for Interoperability and OLAP
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Storage Estimation for Multidimensional Aggregates in the Presence of Hierarchies
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
On the Computation of Multidimensional Aggregates
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
A Foundation for Multi-dimensional Databases
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Modeling Multidimensional Databases, Cubes and Cube Operations
SSDBM '98 Proceedings of the 10th International Conference on Scientific and Statistical Database Management
Multidimensional Data Modeling for Complex Data
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
An Introduction to Database Systems
An Introduction to Database Systems
Model for organizational knowledge creation and strategic use of information: Research Articles
Journal of the American Society for Information Science and Technology
Graphical querying of multidimensional databases
ADBIS'07 Proceedings of the 11th East European conference on Advances in databases and information systems
Derived types in semantic association discovery
Journal of Intelligent Information Systems
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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.