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Many large organizations have their data and processing spread across multiple independent database applications. These data sources, with their own schemas, need to inter-operate to meet new requirements, both within and across organizations. In this paper, we propose a vision of an ontology-enabled database management systems (called OeDBMS) so that the end users can co-relate and integrate ontologies associated with individual sources and extract, co-relate and integrate data from different sources. We propose the architecture and ontology model for OeDBMS. We propose many useful extensions to the RDF/S-based ontology models that are emerging as standards, and provide a graph-based abstraction for the model. This becomes a basis for defining many useful ontology operators and an ontology query language for browsing, searching, matching and maintaining ontologies. We also address the need for ontology evolution by providing temporal support for ontology.

Many large organizations have their data and processing spread across multiple independent database applications. These data sources, with their own schemas, need to inter-operate to meet new requirements, both within and across organizations. In this paper, we propose a vision of an ontology-enabled database management systems (called OeDBMS) so that the end users can co-relate and integrate ontologies associated with individual sources and extract, co-relate and integrate data from different sources. We propose the architecture and ontology model for OeDBMS. We propose many useful extensions to the RDF/S-based ontology models that are emerging as standards, and provide a graph-based abstraction for the model. This becomes a basis for defining many useful ontology operators and an ontology query language for browsing, searching, matching and maintaining ontologies. We also address the need for ontology evolution by providing temporal support for ontology.

Many large organizations have their data and processing spread across multiple independent database applications. These data sources, with their own schemas, need to inter-operate to meet new requirements, both within and across organizations. In this paper, we propose a vision of an ontology-enabled database management systems (called OeDBMS) so that the end users can co-relate and integrate ontologies associated with individual sources and extract, co-relate and integrate data from different sources. We propose the architecture and ontology model for OeDBMS. We propose many useful extensions to the RDF/S-based ontology models that are emerging as standards, and provide a graph-based abstraction for the model. This becomes a basis for defining many useful ontology operators and an ontology query language for browsing, searching, matching and maintaining ontologies. We also address the need for ontology evolution by providing temporal support for ontology.

Many large organizations have their data and processing spread across multiple independent database applications. These data sources, with their own schemas, need to inter-operate to meet new requirements, both within and across organizations. In this paper, we propose a vision of an ontology-enabled database management systems (called OeDBMS) so that the end users can co-relate and integrate ontologies associated with individual sources and extract, co-relate and integrate data from different sources. We propose the architecture and ontology model for OeDBMS. We propose many useful extensions to the RDF/S-based ontology models that are emerging as standards, and provide a graph-based abstraction for the model. This becomes a basis for defining many useful ontology operators and an ontology query language for browsing, searching, matching and maintaining ontologies. We also address the need for ontology evolution by providing temporal support for ontology.

Many large organizations have their data and processing spread across multiple independent database applications. These data sources, with their own schemas, need to inter-operate to meet new requirements, both within and across organizations. In this paper, we propose a vision of an ontology-enabled database management systems (called OeDBMS) so that the end users can co-relate and integrate ontologies associated with individual sources and extract, co-relate and integrate data from different sources. We propose the architecture and ontology model for OeDBMS. We propose many useful extensions to the RDF/S-based ontology models that are emerging as standards, and provide a graph-based abstraction for the model. This becomes a basis for defining many useful ontology operators and an ontology query language for browsing, searching, matching and maintaining ontologies. We also address the need for ontology evolution by providing temporal support for ontology.

Many large organizations have their data and processing spread across multiple independent database applications. These data sources, with their own schemas, need to inter-operate to meet new requirements, both within and across organizations. In this paper, we propose a vision of an ontology-enabled database management systems (called OeDBMS) so that the end users can co-relate and integrate ontologies associated with individual sources and extract, co-relate and integrate data from different sources. We propose the architecture and ontology model for OeDBMS. We propose many useful extensions to the RDF/S-based ontology models that are emerging as standards, and provide a graph-based abstraction for the model. This becomes a basis for defining many useful ontology operators and an ontology query language for browsing, searching, matching and maintaining ontologies. We also address the need for ontology evolution by providing temporal support for ontology.

Many large organizations have their data and processing spread across multiple independent database applications. These data sources, with their own schemas, need to inter-operate to meet new requirements, both within and across organizations. In this paper, we propose a vision of an ontology-enabled database management systems (called OeDBMS) so that the end users can co-relate and integrate ontologies associated with individual sources and extract, co-relate and integrate data from different sources. We propose the architecture and ontology model for OeDBMS. We propose many useful extensions to the RDF/S-based ontology models that are emerging as standards, and provide a graph-based abstraction for the model. This becomes a basis for defining many useful ontology operators and an ontology query language for browsing, searching, matching and maintaining ontologies. We also address the need for ontology evolution by providing temporal support for ontology.

Many large organizations have their data and processing spread across multiple independent database applications. These data sources, with their own schemas, need to inter-operate to meet new requirements, both within and across organizations. In this paper, we propose a vision of an ontology-enabled database management systems (called OeDBMS) so that the end users can co-relate and integrate ontologies associated with individual sources and extract, co-relate and integrate data from different sources. We propose the architecture and ontology model for OeDBMS. We propose many useful extensions to the RDF/S-based ontology models that are emerging as standards, and provide a graph-based abstraction for the model. This becomes a basis for defining many useful ontology operators and an ontology query language for browsing, searching, matching and maintaining ontologies. We also address the need for ontology evolution by providing temporal support for ontology.

Many large organizations have their data and processing spread across multiple independent database applications. These data sources, with their own schemas, need to inter-operate to meet new requirements, both within and across organizations. In this paper, we propose a vision of an ontology-enabled database management systems (called OeDBMS) so that the end users can co-relate and integrate ontologies associated with individual sources and extract, co-relate and integrate data from different sources. We propose the architecture and ontology model for OeDBMS. We propose many useful extensions to the RDF/S-based ontology models that are emerging as standards, and provide a graph-based abstraction for the model. This becomes a basis for defining many useful ontology operators and an ontology query language for browsing, searching, matching and maintaining ontologies. We also address the need for ontology evolution by providing temporal support for ontology.

Many large organizations have their data and processing spread across multiple independent database applications. These data sources, with their own schemas, need to inter-operate to meet new requirements, both within and across organizations. In this paper, we propose a vision of an ontology-enabled database management systems (called OeDBMS) so that the end users can co-relate and integrate ontologies associated with individual sources and extract, co-relate and integrate data from different sources. We propose the architecture and ontology model for OeDBMS. We propose many useful extensions to the RDF/S-based ontology models that are emerging as standards, and provide a graph-based abstraction for the model. This becomes a basis for defining many useful ontology operators and an ontology query language for browsing, searching, matching and maintaining ontologies. We also address the need for ontology evolution by providing temporal support for ontology.