Graph-driven federated data management
Modern data analysis applications, require the ability to provide on-demand integration of data sources while offering a flexible and user-friendly query interface. Traditional techniques for answering queries using views, focused on a rather static setting, fail to address such requirements. To ove...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2021 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/346074 |
| Acceso en línea: | https://hdl.handle.net/2117/346074 https://dx.doi.org/10.1109/TKDE.2021.3077044 |
| Access Level: | acceso abierto |
| Palabra clave: | Database management Ontologies (Information retrieval) Data integration (Computer science) Data wrangling GLAV mappings Bases de dades -- Gestió Ontologies (Informàtica) Àrees temàtiques de la UPC::Informàtica::Sistemes d'informació |
| Sumario: | Modern data analysis applications, require the ability to provide on-demand integration of data sources while offering a flexible and user-friendly query interface. Traditional techniques for answering queries using views, focused on a rather static setting, fail to address such requirements. To overcome these issues, we propose a fully-fledged data integration approach based on graph-based constructs. The extensibility of graphs allows us to extend the traditional framework for data integration with view definitions. Furthermore, we also propose a query language based on subgraphs. We tackle query answering via a query rewriting algorithm based on well-known algorithms for answering queries using views. We experimentally show that the proposed method yields good performance and does not introduce a significant overhead. |
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