Interlinking Heterogeneous Data for Smart Energy Systems Article Swipe

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Fabrizio Orlandi , Alan Meehan , Murhaf Hossari , Soumyabrata Dev , Declan O’Sullivan , Tarek AlSkaif ·

YOU? · · 2021 · Open Access · · DOI: https://doi.org/10.1109/sest.2019.8849055

Smart energy systems in general, and solar energy analysis in particular, have recently gained increasing interest. This is mainly due to stronger focus on smart energy saving solutions and recent developments in photovoltaic (PV) cells. Various data-driven and machine-learning frameworks are being proposed by the research community. However, these frameworks perform their analysis - and are designed on - specific, heterogeneous and isolated datasets, distributed across different sites and sources, making it hard to compare results and reproduce the analysis on similar data. We propose an approach based on Web (W3C) standards and Linked Data technologies for representing and converting PV and weather records into an Resource Description Framework (RDF) graph-based data format. This format, and the presented approach, is ideal in a data integration scenario where data needs to be converted into homogeneous form and different datasets could be interlinked for distributed analysis.

Related Topics

Theoretical Computer Science

Engineering

Electrical Engineering

Optics

Physics

Concepts

Computer science RDF Data science Graph Homogeneous Linked data Resource (disambiguation) Focus (optics) Photovoltaic system Distributed computing Semantic Web Data modeling Database Data mining World Wide Web Theoretical computer science Computer network Engineering Electrical engineering Optics Physics Thermodynamics

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Type: article
Language: en
Landing Page: https://arxiv.org/abs/1907.02790
PDF: https://www.tara.tcd.ie/bitstream/2262/95723/1/1907.02790.pdf
OA Status: green
Cited By: 12
References: 19
Related Works: 10
OpenAlex ID: https://openalex.org/W2977215071

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OpenAlex ID: https://openalex.org/W2977215071

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DOI: https://doi.org/10.1109/sest.2019.8849055

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Title: Interlinking Heterogeneous Data for Smart Energy Systems

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Type: article

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Language: en

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Publication year: 2021

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Publication date: 2021-03-17

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Authors: Fabrizio Orlandi, Alan Meehan, Murhaf Hossari, Soumyabrata Dev, Declan O’Sullivan, Tarek AlSkaif

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Landing page: https://arxiv.org/abs/1907.02790

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PDF URL: https://www.tara.tcd.ie/bitstream/2262/95723/1/1907.02790.pdf

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Concepts: Computer science, RDF, Data science, Graph, Homogeneous, Linked data, Resource (disambiguation), Focus (optics), Photovoltaic system, Distributed computing, Semantic Web, Data modeling, Database, Data mining, World Wide Web, Theoretical computer science, Computer network, Engineering, Electrical engineering, Optics, Physics, Thermodynamics

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Cited by: 12

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Citations by year (recent): 2025: 1, 2024: 1, 2023: 1, 2021: 8, 2019: 1

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References (count): 19

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Related works (count): 10

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publication_year	2021
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