Artículos de publicaciones periódicas
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Browsing Artículos de publicaciones periódicas by Subject "BASES DE DATOS ORIENTADAS A GRAFOS"
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artículo de publicación periódica.listelement.badge Analytical queries on semantic trajectories using graph databases(2019-10) Gómez, Leticia Irene; Kuijpers, Bart; Vaisman, Alejandro Ariel"This article studies the analysis of moving object data collected by location-aware devices, such as GPS, using graph databases. Such raw trajectories can be transformed into so-called semantic trajectories, which are sequences of stops that occur at “places of interest.” Trajectory data analysis can be enriched if spatial and non-spatial contextual data associated with the moving objects are taken into account, and aggregation of trajectory data can reveal hidden patterns within such data. When trajectory data are stored in relational databases, there is an “impedance mismatch” between the representation and storage models. Graphs in which the nodes and edges are annotated with properties are gaining increasing interest to model a variety of networks. Therefore, this article proposes the use of graph databases (Neo4j in this case) to represent and store trajectory data, which can thus be analyzed at different aggregation levels using graph query languages (Cypher, for Neo4j). Through a real-world public data case study, the article shows that trajectory queries are expressed more naturally on the graph-based representation than over the relational alternative, and perform better in many typical cases."artículo de publicación periódica.listelement.badge A model and query language for temporal graph databases(2021-09) Debrouvier, Ariel; Parodi, Eliseo; Perazzo, Matías; Soliani, Valeria; Vaisman, Alejandro Ariel"Graph databases are becoming increasingly popular for modeling different kinds of networks for data analysis. They are built over the property graph data model, where nodes and edges are annotated with property-value pairs. Most existing work in the field is based on graphs were the temporal dimension is not considered. However, time is present in most real world problems. Many different kinds of changes may occur in a graph as the world it represents evolves across time. For instance, edges, nodes, and properties can be added and/or deleted, and property values can be updated. This paper addresses the problem of modeling, storing, and querying temporal property graphs, allowing keeping the history of a graph database. This paper introduces a temporal graph data model, where nodes and relationships contain attributes (properties) timestamped with a validity interval. Graphs in this model can be heterogeneous, that is, relationships may be of different kinds. Associated with the model, a high-level graph query language, denoted T-GQL, is presented, together with a collection of algorithms for computing different kinds of temporal paths in a graph, capturing different temporal path semantics. T-GQL can express queries like “Give me the friends of the friends of Mary, who lived in Brussels at the same time than her, and also give me the periods when this happened”. As a proof-of-concept, a Neo4j-based implementation of the above is also presented, and a client-side interface allows submitting queries in T-GQL to a Neo4j server. Finally, experiments were carried out over synthetic and real-world data sets, with a twofold goal: on the one hand, to show the plausibility of the approach; on the other hand, to analyze the factors that affect performance, like the length of the paths mentioned in the query, and the size of the graph."artículo de publicación periódica.listelement.badge Towards the Internet of water: Using graph databases for hydrological analysis on the Flemish river system(2021-07) Bollen, Erik; Hendrix, Rik; Kuijpers, Bart; Vaisman, Alejandro Ariel"The “Internet of Water” project will deploy 2,500 sensors along the Flemish river system, in Belgium. These sensors will be part of a monitoring system. This will produce anenormous amount of data, on which prediction and analysis tasks can be performed. To represent, store, and query river data, relational databases are normally used. However, this choice introduces an “impedance mismatch” between the conceptual representation (typically a graph) and the storage model (relational tables). To solve this problem, this article proposes to use graph databases. The Flemish river system is presented as a use case and the Neo4j graph database and its high-level query language, Cypher, are used for storing and querying the data, respectively. A relational alternative is implemented over the PostgreSQL database. A collection of representative queries of interest for hydrologists is defined over both database implementations."