Linked Sensor Data

Augment Sensor Data with additional contextual information from the Web of Data.

The SPITFIRE Ontology

The SPITFIRE Ontology (SPT) aligns already existing vocabularies to enable the semantic description of, not only sensor measurements and sensor metadata, but also of the context surrounding them (Figure 1). The ontology also extends them with support for energy-efficiency requirements (Figure 2 and Figure 3). In particular, the activities sensed by sensors, are modeled and related with social domain vocabularies and complex event descriptions (Figure 4).

The authoritative namespace is http://spitfire-project.eu/ontology/ns/ (OWL, last update: 30 April 2012) .
The SPITFIRE ontology is part of the Linked Open Vocabularies.
Browse it using an RDF browser (e.g. Marbles, Parrot, LODE).
The W3C Semantic Sensor Network ontology (SSN) constitutes the core of the SPITFIRE ontology.
View all the vocabularies referenced by SPT .

The SPT is composed by the modules showed in Figure 1 with a focus on
  • energy saving in building automation (the SPITFIRE consolidated use case) thus allowing to monitor and describe both the structure and the performances of sensor networks and their components.
  • modeling any kind of activity / event that has been sensed together enriched by descriptions of the surrounding environment. The SPITFIRE ontology enables a full and rich description of, not only sensor data but also the sensed event, its structure, what triggered it and its relation with other activities. An activity can be also a Presence somewhere or a Status (either online or offline).

Specific Context-related types and instances are defined in http://spitfire-project.eu/ontology/ns/ct/ .
Specific Sensor Network-related types and instances are defined in http://spitfire-project.eu/ontology/ns/sn/ .
Specific types and instances related to Places are defined in http://spitfire-project.eu/ontology/ns/p/ .

Figure 1: Modules in which the SPITFIRE vocabulary is divided. For each module the main concepts, predicates and its relation with other modules are depicted, too.

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Figure 2: Data Modeling of the sensor network components. Using these terms to profile the network components, is aimed at improving the flexibility of energy-efficient routing algorithm by the addition of semantics.

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Figure 3: Data Modeling of energy-related concepts. Using these terms to profile network components or Internet-Connected Objects (ICOs), is aimed at improving the flexibility of energy-efficient routing algorithm by the addition of semantics.

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Figure 4: Alignment of already existing ontologies from the social, sensor and provenance domain, aimed at further modeling the context surrounding sensors

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