Storage and Querying of E-Commerce Data
Proceedings of the 27th International Conference on Very Large Data Bases
Sesame: A Generic Architecture for Storing and Querying RDF and RDF Schema
ISWC '02 Proceedings of the First International Semantic Web Conference on The Semantic Web
RStar: an RDF storage and query system for enterprise resource management
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Efficient management of very large ontologies
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Benchmarking database representations of RDF/S stores
ISWC'05 Proceedings of the 4th international conference on The Semantic Web
OntoDB2: support of multiple ontology models within ontology based database
Ph.D. '08 Proceedings of the 2008 EDBT Ph.D. workshop
Semantic Exploitation of Engineering Models: An Application to Oilfield Models
BNCOD 26 Proceedings of the 26th British National Conference on Databases: Dataspace: The Final Frontier
A semantic handling of geological modeling workflows
Proceedings of the International Conference on Management of Emergent Digital EcoSystems
An object-oriented based algebra for ontologies and their instances
ADBIS'07 Proceedings of the 11th East European conference on Advances in databases and information systems
OntoDB: it is time to embed your domain ontology in your database
DASFAA'07 Proceedings of the 12th international conference on Database systems for advanced applications
Context representation in domain ontologies and its use for semantic integration of data
Journal on data semantics X
Reasoning with large ontologies stored in relational databases: The OntoMinD approach
Data & Knowledge Engineering
A methodology and tool for conceptual designing a data warehouse from ontology-based sources
DOLAP '10 Proceedings of the ACM 13th international workshop on Data warehousing and OLAP
A language for ontology-based metamodeling systems
ADBIS'10 Proceedings of the 14th east European conference on Advances in databases and information systems
Ontologies and functional dependencies for data integration and reconciliation
ER'11 Proceedings of the 30th international conference on Advances in conceptual modeling: recent developments and new directions
Embedding user's requirements in data warehouse repositories
OTM'11 Proceedings of the 2011th Confederated international conference on On the move to meaningful internet systems
The role of class dependencies in designing ontology-based databases
OTM'11 Proceedings of the 2011th Confederated international conference on On the move to meaningful internet systems
Ontologies versus relational databases: are they so different? A comparison
Artificial Intelligence Review
Towards performance evaluation of semantic databases management systems
BNCOD'13 Proceedings of the 29th British National conference on Big Data
View-OD: a view model for ontology-based databases
International Journal of Intelligent Information and Database Systems
| Hi-index | 0.00 |
Recently, several approaches and systems were proposed to store in the same database data and the ontologies describing their meanings. We call these databases, ontology-based databases (OBDBs). Ontology-based data denotes those data that represent ontology individuals (i.e., instance of ontology classes). To speed up query execution on the top of these OBDBs, efficient representations of ontology-based data become a new challenge. Two main representation schemes have been proposed for ontology-based data: vertical and binary representations with a variant called hybrid. In these schemes, each instance is split into a number of tuples. In this paper, we propose a new representation of ontology-based data, called table per class. It consists in associating a table to each ontology class, where all property values of a class instance are represented in a same row. Columns of this table represent those properties of the ontology class that are associated with a value for at least one instance of this class. We present the architecture of our ontology-based databases and a comparison of the effectiveness of our representation scheme with the existing ones used in Semantic Web applications. Our benchmark involves three categories of queries: (1) targeted class queries, where users know the classes they are querying, (2) no targeted class queries, where users do not know the class(es) they are querying, and (3) update queries.