RDF models and SPARQL queries for decoupled analytics demonstration

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This directory contains the following: - Two sets of RDF triples using different ontologies, modeling the same "MZVAV-2" air handling unit from the data inventory by Granderson et al. [1]. - SPARQL queries for retrieving inputs to APAR [2] rules. - SPARQL queries for discovering "data links" from the models, connecting data points to time series providers. The models were created by manually writing the triples. For details, see included README.md   [1] J. Granderson, G. Lin, A. Harding, P. Im, Y. Chen, Building fault detection data to aid diagnostic algorithm creation and performance testing, Scientific Data. 7 (2020) 65. https://doi.org/10.1038/s41597-020-0398-6. [2] J.M. House, H. Vaezi-Nejad, J.M. Whitcomb, An expert rule set for fault detection in air-handling units, ASHRAE Transactions. 107 (2001) 858–871.
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Julkaisuvuosi

2022

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Department of Electrical Engineering and Automation

Ville Kukkonen Orcid -palvelun logo - Tekijä

Zenodo - Julkaisija

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Muut tiedot

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Tietojenkäsittely ja informaatiotieteet

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Avoin

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Creative Commons Nimeä 4.0 Kansainvälinen (CC BY 4.0)

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