Time-series based simulations of industrial processes are instrumental to optimizing a variety of industrial settings. In this paper, we describe a use case, developed together with Infineon Technologies Austria AG. Monitoring data stored in relational databases was used to build process models of industrial chillers. Optimization algorithms were then applied to find optimal strategies for operating the chillers. Even though the results from this approach were convincing, the access to the necessary data was a labor-intensive and error-prone task. Therefore, in this paper, we investigate how Semantic Web technologies can help to improve data access for time-series data and under which circumstances they would be helpful for the domain experts performing the simulation.
|Title of host publication||Posters&Demos at SEMANTiCS 2018|
|Subtitle of host publication||Proceedings of the Posters and Demos Track of the 14th International Conference on Semantic Systems co-located with the 14th International Conference on Semantic Systems (SEMPDS 2018)|
|Editors||Ali Khalili, Maria Koutraki|
|Place of Publication||Aachen|
|Publication status||Published - 2018|
|Event||Posters and Demos Track of the 14th International Conference on Semantic Systems, SEMPDS 2018 - Vienna, Austria|
Duration: 10 Sept 2018 → 13 Sept 2018
|Series||CEUR Workshop Proceedings|
|Conference||Posters and Demos Track of the 14th International Conference on Semantic Systems, SEMPDS 2018|
|Period||10/09/18 → 13/09/18|
Bibliographical notePublisher Copyright:
© 2018 CEUR-WS. All Rights Reserved.
- Ontology-based data access