Abstract

While satellite-based positioning systems are mainly used in outdoor environments, various other positioning techniques exist for different domains and use cases, including indoor or underground settings. The representation of spatial data via semantic linked data is well addressed by existing spatial ontologies. However, there is a primary focus on location data with its specific geographical context, but a lack of solutions for describing the different types of data generated by a positioning system and the used sampling techniques to obtain the data. In this paper we introduce a new generic Positioning System Ontology (POSO) that is built on top of the Semantic Sensor Network (SSN) and Sensor, Observation, Sample, and Actuator (SOSA) ontologies. With POSO, we provide missing concepts needed for describing a positioning system and its output with known positioning algorithms and techniques in mind. Thereby, we enable the improvement of hybrid positioning systems making use of multiple platforms and sensors that are described via the presented POSO ontology.

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Methodology

The POSO ontology has been designed with the common data requirements of various positioning system technologies, datasets and frame- works in mind to cover all types of systems without overcomplicating the modelling of the data. An initial validation has further been conducted based on the OpenHPS framework using the @openhps/rdf module.