RDF models and SPARQL queries for decoupled analytics demonstration

RDF models and SPARQL queries for decoupled analytics demonstration

Description

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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Year of publication

2022

Authors

Department of Electrical Engineering and Automation

Ville Kukkonen Orcid -palvelun logo - Creator

Zenodo - Publisher

Other information

Fields of science

Computer and information sciences

Open access

Open

License

Creative Commons Attribution 4.0 International (CC BY 4.0)

RDF models and SPARQL queries for decoupled analytics demonstration - Research.fi