Path constraints on semistructured and structured data
PODS '98 Proceedings of the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Regular path queries with constraints
Journal of Computer and System Sciences
A foundation for capturing and querying complex multidimensional data
Information Systems - Data warehousing
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Foundations of Databases: The Logical Level
Foundations of Databases: The Logical Level
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
Extending Practical Pre-Aggregation in On-Line Analytical Processing
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
What can Hierarchies do for Data Warehouses?
VLDB '99 Proceedings of the 25th 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
Summarizability in OLAP and Statistical Data Bases
SSDBM '97 Proceedings of the Ninth International Conference on Scientific and Statistical Database Management
Normal Forms for Multidimensional Databases
SSDBM '98 Proceedings of the 10th International Conference on Scientific and Statistical Database Management
Querying Multidimensional Databases
DBLP-6 Proceedings of the 6th International Workshop on Database Programming Languages
Maintaining Data Cubes under Dimension Updates
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Structurally heterogeneous olap dimensions
Structurally heterogeneous olap dimensions
Supporting OLAP operations over imperfectly integrated taxonomies
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Multidimensional content eXploration
Proceedings of the VLDB Endowment
Solving summarizability problems in fact-dimension relationships for multidimensional models
Proceedings of the ACM 11th international workshop on Data warehousing and OLAP
AlphaSum: size-constrained table summarization using value lattices
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
A survey on summarizability issues in multidimensional modeling
Data & Knowledge Engineering
Ontologies and summarizability in OLAP
Proceedings of the 2010 ACM Symposium on Applied Computing
Data warehouse design on the basis of Hierarchical Degenerate Snowflake (HDS)
International Journal of Business Intelligence and Data Mining
Combining objects with rules to represent aggregation knowledge in data warehouse and OLAP systems
Data & Knowledge Engineering
Incremental integration of data warehouses: the hetero-homogeneous approach
Proceedings of the ACM 14th international workshop on Data Warehousing and OLAP
Repairing dimension hierarchies under inconsistent reclassification
ER'11 Proceedings of the 30th international conference on Advances in conceptual modeling: recent developments and new directions
Analysing multi-dimensional data across autonomous data warehouses
DaWaK'06 Proceedings of the 8th international conference on Data Warehousing and Knowledge Discovery
Building data warehouses with semantic web data
Decision Support Systems
A unified object constraint model for designing and implementing multidimensional systems
Journal on Data Semantics XIII
Repair-oriented relational schemas for multidimensional databases
Proceedings of the 15th International Conference on Extending Database Technology
Enhancing OLAP analysis with web cubes
ESWC'12 Proceedings of the 9th international conference on The Semantic Web: research and applications
Repairing inconsistent dimensions in data warehouses
Data & Knowledge Engineering
Multidimensional models meet the semantic web: defining and reasoning on OWL-DL ontologies for OLAP
Proceedings of the fifteenth international workshop on Data warehousing and OLAP
Benchmarking summarizability processing in XML warehouses with complex hierarchies
Proceedings of the fifteenth international workshop on Data warehousing and OLAP
Scalable test data generation from multidimensional models
Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering
Spatial OLAP and Map Generalization: Model and Algebra
International Journal of Data Warehousing and Mining
A multidimensional data model with subcategories for flexibly capturing summarizability
Proceedings of the 25th International Conference on Scientific and Statistical Database Management
Extended dimensions for cleaning and querying inconsistent data warehouses
Proceedings of the sixteenth international workshop on Data warehousing and OLAP
Detecting summarizability in OLAP
Data & Knowledge Engineering
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In multidimensional data models intended for online analytic processing (OLAP), data are viewed as points in a multidimensional space. Each dimension has structure, described by a directed graph of categories, a set of members for each category, and a child/parent relation between members. An important application of this structure is to use it to infer summarizability, that is, whether an aggregate view defined for some category can be correctly derived from a set of precomputed views defined for other categories. A dimension is called structurally heterogeneous if two members in a given category are allowed to have ancestors in different categories. In this article, we propose a class of integrity constraints, dimension constraints, that allow us to reason about summarizability in heterogeneous dimensions. We introduce the notion of frozen dimensions which are minimal homogeneous dimension instances representing the different structures that are implicitly combined in a heterogeneous dimension. Frozen dimensions provide the basis for efficiently testing the implication of dimension constraints and are a useful aid to understanding heterogeneous dimensions. We give a sound and complete algorithm for solving the implication of dimension constraints that uses heuristics based on the structure of the dimension and the constraints to speed up its execution. We study the intrinsic complexity of the implication problem and the running time of our algorithm.