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Ontology for the Semantic Classification of Time Series Knowledge SemTS is an ontology to semantically structure insights gained from multivariate time series analyses combined with domain-specific information. The concept of SemTS constitutes a specification of informative data points or intervals within time series data, further referred to as segments. Any segment comprises characteristic knowledge associated with the covered time interval. Examples of such knowledge range from common time series features and structural particularities, such as anomalies or motifs, to a priori information provided by domain experts. A classification and semantic representation of this knowledge enables organized reusability and effective propagation. |
Diagram of version v1.2.0
Prefix: semts
Namespace: https://w3id.org/semts
Ontology IRI: https://w3id.org/semts/ontology#
https://w3id.org/semts/ontology/{version}Please cite as follows:
@inproceedings{grass2026semts,
title={SemTS: Ontology and Vocabularies for the Semantic Categorization of Time Series Knowledge},
author={Gra{\ss}, Alexander and Deshmukh, Rohit A and Lange, Christoph and Collarana, Diego and Beecks, Christian and Decker, Stefan},
booktitle={European Semantic Web Conference},
pages={172--190},
year={2026},
organization={Springer}
}
ontology.ttlOntology files and documentation:
Source code and other software components: