A semantics-enabled approach for personalised Data Lake exploration

Bianchini, Devis; De Antonellis, Valeria; Garda, Massimiliano

doi:10.1007/s10115-023-02014-1

Cited by 1 publication

(1 citation statement)

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“…This model adds a contextual layer to the data, elucidating the meaning of the data and establishing their interconnections with other datasets. An example of a semantic data lake tailored for a Smart City was described in [34], where the authors included a semantic metadata catalog on top of the data lake, leveraging tools and metrics to ease the annotation of the data lake metadata, as well as modeling indicators and analysis dimensions and exploiting a multi-dimensional ontology to check their conformance. Finally, they applied an enrichment of the indicators based on a customization of the profiles and preferences of the users, further facilitating the exploration of data.…”

Section: Related Workmentioning

confidence: 99%

An Urban Intelligence Architecture for Heterogeneous Data and Application Integration, Deployment and Orchestration

Silvestri,

Tricomi,

Bassolillo

et al. 2024

Sensors

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This paper describes a novel architecture that aims to create a template for the implementation of an IT platform, supporting the deployment and integration of the different digital twin subsystems that compose a complex urban intelligence system. In more detail, the proposed Smart City IT architecture has the following main purposes: (i) facilitating the deployment of the subsystems in a cloud environment; (ii) effectively storing, integrating, managing, and sharing the huge amount of heterogeneous data acquired and produced by each subsystem, using a data lake; (iii) supporting data exchange and sharing; (iv) managing and executing workflows, to automatically coordinate and run processes; and (v) to provide and visualize the required information. A prototype of the proposed IT solution was implemented leveraging open-source frameworks and technologies, to test its functionalities and performance. The results of the tests performed in real-world settings confirmed that the proposed architecture could efficiently and easily support the deployment and integration of heterogeneous subsystems, allowing them to share and integrate their data and to select, extract, and visualize the information required by a user, as well as promoting the integration with other external systems, and defining and executing workflows to orchestrate the various subsystems involved in complex analyses and processes.

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Section: Related Workmentioning

confidence: 99%