Linked Data for Smart Homes: Comparing RDF and Labeled Property Graphs

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Abstract

The need to integrate siloed data in the built environment led to a gaining interest in semantic web technologies in the Architecture, Engineering and Construction (AEC) sector. Especially for smart home developments, the integration of information about the building, users and Internet of Things (IoT) devices could be valuable. The Resource Description Framework (RDF) is the standard model for the semantic web, however, labeled property graphs (LPG) also proved to be effective in linking data. This research used the Open Smart Home Dataset and a dataset representing a kitchen to compare the two graph models both qualitatively and quantitatively. The comparison shows that native labeled property graphs are less complex and outperform the atomic RDF in complex graph traversals. However, RDF shows qualitative advantages for multi-domain and multi-stakeholder environments, such as the use of ontologies and HTTP URIs, making it a more stable interoperability format.

Original languageEnglish
Title of host publicationLDAC 2020 Linked Data in Architecture and Construction
Subtitle of host publicationProceedings of the 8th Linked Data in Architecture and Construction Workshop Dublin, Ireland, June 17-19, 2020
EditorsMaría Poveda-Villalón, Ana Roxin, Kris McGlinn, Pieter Pauwels
PublisherCEUR-WS.org
Pages23-36
Number of pages14
Publication statusPublished - 2020
Event8th Linked Data in Architecture and Construction Workshop - Virtually Hosted, Dublin, Ireland
Duration: 17 Jun 202019 Jun 2020
http://linkedbuildingdata.net/ldac2020/

Publication series

NameCEUR Workshop Proceedings
PublisherCEUR-WS.org
Volume2636

Workshop

Workshop8th Linked Data in Architecture and Construction Workshop
Abbreviated titleLDAC2020
CountryIreland
CityDublin
Period17/06/2019/06/20
Internet address

Keywords

  • LPG
  • Neo4j
  • RDF
  • Smart Home

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