Statistical and Scientific Database Issues
IEEE Transactions on Software Engineering
Efficient organization and access of multi-dimensional datasets on tertiary storage systems
Information Systems - Special issue: scientific databases
Implementing data cubes efficiently
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
CROSS-DB: a feature-extended multidimensional data model for statistical and scientific databases
CIKM '96 Proceedings of the fifth international conference on Information and knowledge management
OLAP and statistical databases: similarities and differences
PODS '97 Proceedings of the sixteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
The pyramid-technique: towards breaking the curse of dimensionality
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Clustering techniques for large data sets—from the past to the future
KDD '99 Tutorial notes of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
The Grid File: An Adaptable, Symmetric Multikey File Structure
ACM Transactions on Database Systems (TODS)
ACM Computing Surveys (CSUR)
Extending OLAP querying to external object databases
Proceedings of the ninth international conference on Information and knowledge management
The Quadtree and Related Hierarchical Data Structures
ACM Computing Surveys (CSUR)
A performance comparison of bitmap indexes
Proceedings of the tenth international conference on Information and knowledge management
ACM Computing Surveys (CSUR)
Survey of Spatio-Temporal Databases
Geoinformatica
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
An introduction to spatial database systems
The VLDB Journal — The International Journal on Very Large Data Bases - Spatial Database Systems
Visualization Techniques for Mining Large Databases: A Comparison
IEEE Transactions on Knowledge and Data Engineering
A Logical Approach to Multidimensional Databases
EDBT '98 Proceedings of the 6th International Conference on Extending Database Technology: Advances in Database Technology
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
Characteristics of Scientific Databases
VLDB '84 Proceedings of the 10th International Conference on Very Large Data Bases
Extending Practical Pre-Aggregation in On-Line Analytical Processing
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Optimal Grid-Clustering: Towards Breaking the Curse of Dimensionality in High-Dimensional Clustering
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
The R+-Tree: A Dynamic Index for Multi-Dimensional Objects
VLDB '87 Proceedings of the 13th International Conference on Very Large Data Bases
Statistical Databases: Characteristics, Problems, and some Solutions
VLDB '82 Proceedings of the 8th International Conference on Very Large Data Bases
Summarizability in OLAP and Statistical Data Bases
SSDBM '97 Proceedings of the Ninth International Conference on Scientific and Statistical Database Management
The Cube-Query-Languages (CQL) for Multidimensional Statistical and Scientific Database Systems
Proceedings of the Fifth International Conference on Database Systems for Advanced Applications (DASFAA)
Querying Multidimensional Databases
DBLP-6 Proceedings of the 6th International Workshop on Database Programming Languages
Multidimensional Indexing and Query Coordination for Tertiary Storage Management
SSDBM '99 Proceedings of the 11th International Conference on Scientific and Statistical Database Management
Clustering High Dimensional Massive Scientific Datasets
SSDBM '01 Proceedings of the 13th International Conference on Scientific and Statistical Database Management
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The term "multidimensional databses" refers to data that can be viewed conceptually in a multidimensional space, where each dimension represents some attributes of the data. Viewing data in this form is natural for many applications, yet the concepts are not treated in a uniform way in the database literature. In this chapter, we show the commonality of concepts between three database areas: statistical, OLAP, and scientific databases. We show that these domains have two main structural concepts: the cross-product space of the dimensions, and the classification hierarchy structure associated with each dimension. In the first part of this chapter we describe how these structures are sed to represent data in statistical and OLAP databases and how summarization operators can be applied to them. Further, we discuss how these structures can be extended to represent related information using federated database concepts. In the second part of the chapter we show that these concepts are common to many scientific database application. In particular, we discuss the importance of supporting classification structures and the difficulty in representing them as tables in relational databases. We also discuss data structures to support multidimensional databases, emphasizing space-time representation, clustering in multidimensional space, indexing in multidimensional space, and supporting classification structures. We conclude by arguing that the concepts of multidimensionality and classification structures as well as the operation over them should be elevated to "first class" object types. These object types should be visible by the application user explicitly in the conceptual schemas as well as exposing them in the user interfaces.