Semantic Sensor Network Ontology (SSN)

published as Linked Open Data (LOD). The data schema is based on the new version of the Semantic Sensor Network ontology. This ontology version integrates the Sensor, Observation, Sample, and Actuator pattern. We first present the network of ontologies used to organize the data. Then, the transformation process for publishing the dataset is detailed. To conclude we present some use cases of queries related to Irstea research projects.

ontology provide a way to represent sensor data semantically, but how to transform sensor data into the instance of SSN ontology conveniently is still an issue to be considered. This paper proposed a solution to map sensor data to SSN ontology automatically based on a predefined XML-based document. We design a mapping language SASML (Sensors Annotation and Semantic Mapping Language) which provide a schema to annotate sensors and sources so as to generate a XML document for mapping. Then, an algorithm (namely SDRM) is designed to automatically transform sensor data, which described by SASML, to RDF conforming to SSN ontology, according to the mapping document and the element correspondences between the SASML and SSN ontology. Further, a case study about sensor data from greenhouse is presented to illustrate our method, and a prototype is also developed to demonstrate the feasibility and effectiveness.

response to natural disasters such as floods for the lack of semantics. In this paper, a hydrological sensor web ontology based on SSN ontology is proposed to describe the heterogeneous hydrological sensor web resources by importing the time and space ontology, instantiating the hydrological classes, and establishing reasoning rules. This work has been validated by semantic querying and knowledge acquiring experiments. The results demonstrate the feasibility and effectiveness of the proposed ontology and its potential to grow into a more comprehensive ontology for hydrological monitoring collaboratively. In addition, this method of ontology modeling is generally applicable to other applications and domains.

 In this WIP paper, we assume a situation where the edge side and the cloud side hold a common SSN ontology instance and transmit tagged data according to its structure, and a method of reducing the amount of communication data there The basic idea is shown below. Specifically, on the edge side, a pruning process is performed to harvest a part of the data structure including data that does not require transmission, and on the cloud side, by reconstructing the data structure reconstructed against the structure of the ontology, aim for the amount of data reduction.

The ontologies have been published bot h as a W3C recommendation and as an OGC implementation standard. The set includes a lightweight core module called SOSA (Sensor, Observation, Sampler, and Actuator) available at: http://www.w3.org/ns/sosa/, and a more expressive extension module called SSN (Semantic Sensor Network) available at: http://www.w3.org/ns/ssn/. Together they describe systems of sensors and actuators, observations, the used procedures, the subjects and their properties being observed or acted upon, samples and the process of sampling, and so forth. The set of ontologies adopts a modular architecture with SOSA as a self-contained core that is extended by SSN and other modules to add expressivity and breadth. The SOSA/SSN ontologies are able to support a wide range of applications and use cases, including satellite imagery, large-scale scientific monitoring, industrial and household infrastructures, social sensing, citizen science, observation-driven ontology engineering, and the Internet of Things. In this paper we give an overview of the ontologies and discuss the rationale behind key design decisions, reporting on the differences between the new SSN ontology presented here and its predecessor [Web Semantics: Science, Services and Agents on the World Wide Web 17 (2012), 25–32] developed by the W3C Semantic Sensor Network Incubator group (the SSN-XG). We present usage examples and describe alignment modules that foster interoperability with other ontologies.

context of the ITEA2 SEAS (Smart Energy Aware Systems) project. This paper provides an overview of these choices and their rationale. In particular, we describe contributions regarding: (i) the design of the ontology as a set of simple core ontology patterns , that can then be instantiated for multiple engineering-related verticals; (ii) the design and publication of the SEAS modular and versioned ontology in conformance with the publication and meta-data best practices, with the additional constraint that every term is deened under a single namespace. These planned additions to SAREF will ease its adoption and extension by industrial stake-holder, while ensuring easy maintenance of its quality, coherence, and modularity. Finally, because the SEAS ontology generalizes the future W3C&OGC SOSA/SSN (Sensor, Observation, Sensing, Actuation / Semantic Sensor Network) ontology, these work items contribute to the convergence of the diierent reference ontologies relevant for the IoT domain.

context and WSN characteristics are based on ontologies. Based upon a critical analysis of existing ontologies which formalize the WSN domain, we determine that the Semantic Sensor Network (SSN) ontology is the most suitable to represent the WSN issues. However, as the communication data policy is not characterized either by SSN or by other ontologies, we propose to enrich the SSN ontology with a new pattern describing communication.\nIn this paper, we will first integrate the different concepts related to WSN in the SSN ontology and then we will use the resulting ontology, called Wireless Semantic Sensor Network ontology, in an agri-environmental scenario to illustrate the interest of our approach.

SWE), achieve syntactic interoperability, they do not provide facilities for computer logic and reasoning. We argue that ontologies are an adequate methodology to model sensors and their capabilities. Ontologies enable reasoning, classification and other types of automation to extend the SWE standards of the OGC. A semantic sensor network would allow the network and its components to be organised, queried, and controlled through high-level specifications. The ontology proposed here is not an ontology that organises all the facets and concepts of sensing, but rather one that provides a language to describe sensors in terms of their capabilities and operations. This paper introduces an initial version.

foundational ontology to improve semantic interoperability and clarify the underlying ontological commitments. The pattern also forms the top-level of the the Semantic Sensor Network ontology developed by the W3C Semantic Sensor Network Incubator Group. The integration of both ontologies is discussed and directions of further work are pointed out. 1

measurement processes, observations and deployments. This article describes the SSN ontology. It further gives an example and describes the use of the ontology in recent research projects.