Modeling and querying sensor networks using temporal graph databases

"Transportation networks (e.g., river systems or road net works) equipped with sensors that collect data for several different pur poses can be naturally modeled using graph databases. However, since networks can change over time, to represent these changes appropriately, a temporal graph data...

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Detalles Bibliográficos
Autores principales: Kuijpers, Bart, Soliani, Valeria, Vaisman, Alejandro Ariel
Formato: Ponencia en Congreso acceptedVersion
Lenguaje:Inglés
Publicado: 2023
Materias:
BASES DE DATOS ORIENTADAS A GRAFOS
Acceso en línea:https://ri.itba.edu.ar/handle/123456789/4152
Aporte de:
Repositorio Institucional Instituto Tecnológico de Buenos Aires (ITBA) de Instituto Tecnológico de Buenos Aires (ITBA)
id I32-R138-123456789-4152
record_format dspace
spelling I32-R138-123456789-41522023-01-14T03:01:41Z Modeling and querying sensor networks using temporal graph databases Kuijpers, Bart Soliani, Valeria Vaisman, Alejandro Ariel BASES DE DATOS ORIENTADAS A GRAFOS "Transportation networks (e.g., river systems or road net works) equipped with sensors that collect data for several different pur poses can be naturally modeled using graph databases. However, since networks can change over time, to represent these changes appropriately, a temporal graph data model is required. In this paper, we show that sensor-equipped transportation networks can be represented and queried using temporal graph databases and query languages. For this, we extend a recently introduced temporal graph data model and its high-level query language T-GQL to support time series in the nodes of the graph. We redefine temporal paths and study and implement a new kind of path, called Flow path. We take the Flanders’ river system as a use case." 2023-01-13T15:29:49Z 2023-01-13T15:29:49Z 2022 Ponencia en Congreso info:eu-repo/semantics/acceptedVersion https://ri.itba.edu.ar/handle/123456789/4152 en info:eu-repo/semantics/altIdentifier/doi/10.1007/978-3-031-15743-1_21 application/pdf
institution Instituto Tecnológico de Buenos Aires (ITBA)
institution_str I-32
repository_str R-138
collection Repositorio Institucional Instituto Tecnológico de Buenos Aires (ITBA)
language Inglés
topic BASES DE DATOS ORIENTADAS A GRAFOS
spellingShingle BASES DE DATOS ORIENTADAS A GRAFOS
Kuijpers, Bart
Soliani, Valeria
Vaisman, Alejandro Ariel
Modeling and querying sensor networks using temporal graph databases
topic_facet BASES DE DATOS ORIENTADAS A GRAFOS
description "Transportation networks (e.g., river systems or road net works) equipped with sensors that collect data for several different pur poses can be naturally modeled using graph databases. However, since networks can change over time, to represent these changes appropriately, a temporal graph data model is required. In this paper, we show that sensor-equipped transportation networks can be represented and queried using temporal graph databases and query languages. For this, we extend a recently introduced temporal graph data model and its high-level query language T-GQL to support time series in the nodes of the graph. We redefine temporal paths and study and implement a new kind of path, called Flow path. We take the Flanders’ river system as a use case."
format Ponencia en Congreso
acceptedVersion
author Kuijpers, Bart
Soliani, Valeria
Vaisman, Alejandro Ariel
author_facet Kuijpers, Bart
Soliani, Valeria
Vaisman, Alejandro Ariel
author_sort Kuijpers, Bart
title Modeling and querying sensor networks using temporal graph databases
title_short Modeling and querying sensor networks using temporal graph databases
title_full Modeling and querying sensor networks using temporal graph databases
title_fullStr Modeling and querying sensor networks using temporal graph databases
title_full_unstemmed Modeling and querying sensor networks using temporal graph databases
title_sort modeling and querying sensor networks using temporal graph databases
publishDate 2023
url https://ri.itba.edu.ar/handle/123456789/4152
work_keys_str_mv AT kuijpersbart modelingandqueryingsensornetworksusingtemporalgraphdatabases
AT solianivaleria modelingandqueryingsensornetworksusingtemporalgraphdatabases
AT vaismanalejandroariel modelingandqueryingsensornetworksusingtemporalgraphdatabases
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