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.
- 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.
| Koska saatavilla | 2022 |
|---|---|
| Julkaisija | Zenodo |
Dataset Licences
- CC-BY-4.0