IoTest project: Semantic interoperability
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This document discusses semantic interoperability challenges for Internet of Things (IoT) services and resources. It proposes using semantic models and metadata tagging to provide structured, machine-interpretable representations of IoT concepts like resources, entities, and services. This would allow automated processing and integration of diverse IoT data and services. However, challenges remain in aligning different models and achieving real interoperability across frameworks. Practical solutions may involve linking related models and proposing common abstract descriptions.
IoTest project: Semantic interoperability
- 1. Semantic Interoperability for IoT Services and Resources Klaus Moessner Centre for Communication Systems Research University of Surrey October 2011
- 2. Internet of Things • Internet of Things (IoT) vision: – large number of physical world objects interacting with each other and the ambient environment – data/services from these objects to provide ‘real world’ services • provide information • allow interaction
- 3. Requirements • structured representation of identified IoT concepts • homogeneous access mechanism to heterogeneous objects with diverse capabilities • automated machine interpretability of the possible interactions and horizontal integration with existing applications
- 4. How to model Things? • resource model – Gateway, sensors, processing resources • entity model – Physical world objects • Features of interest for each entity • service model – IoT services and interfaces
- 6. Data and services in IoT ‐ Challenges • large‐scale networks, huge volumes of data, dynamic and sometimes unreliable data sources • dynamicity, transient data and subject to quality changes • scalability of the solutions • express‐ability and extensibility of semantics and meta‐data • heterogeneity ‐ more devices are contented, more diversity • more autonomous processes (integration, aggregation, filtering, ...) are required • management of the resources
- 7. Role of metadata • semantic tagging • machine‐interpretable data annotation and resource descriptions • re‐usable ontologies • resource description framework(s) • structured data, structured query
- 8. In IoT semantic models are useful for: • description of various concepts and attributes in the IoT framework • providing machine interpretable and structured representation of resources/entities/services and domain knowledge • supporting automated processing and decision making over various interactions and integration with existing and new applications
- 9. Metadata and Semantics • to describe: – Content – Context – Resources – Entities and features of interest • to create: – Perception – Context and situation awareness • to support: – Automated processes for management of resources and decision making
- 10. Semantic interoperability for • resource description – SENSEI resource description, IoT‐A resource model, W3C SSN Ontology,… • entity description and domain knowledge – SENSEI entity description, IoT‐A entity model, linked data models and linked open data fro domain knowledge,… • IoT services – In IoT.est we plan to use semantic web services (extension to OWL‐S) that we have developed in the context of the IoT‐A project.
- 11. 11 W3C Incubator Group, SSN Ontology makes observations of this type where it is What it measures units SSN-XG ontologies SSN-XG annotations
- 12. Service model Entity Model Ontology W3C SSN OntologyResource Model Ontology OWL‐S Service Profile Ontology P(em:DomainAttribute) OWL‐S Service Grounding Ontology Service Model Ontology hasInput profile:Profile iot:ResourceAccessAtomicProcessGrounding em:DomainAttribute em:DomainAttribute P(em:DomainAttribute) hasEffect hasPrecondition hasOutput Service presents supports rm:AccessInterface hasAccessInterface ssn:Property ssn:Property ssn:Condition ssn:Condition hasInputType hasOutputType hasPreconditionTypehasEffectType iot:ObservationArea iot:ObservationSchedule hasObservationArea hasObservationSchedule hasServiceType ServiceType OWL‐S USDL WSML xxx <<instanceOf>>
- 14. What are the challenges? • the models provide the basic description frameworks, but alignment between different models and frameworks are required. • semantics are the starting point, reasoning and interpretation of data is required for automated processes. • real interoperability happens when data/services from different frameworks and providers can be interchanged and used with minimised intervention.
- 15. What are the practical steps? • linked data approach is a promising way for integrating data from different sources and interlinking semantic descriptions • alignment between different description models for IoT Services/Resources/Entities • proposing reference and abstract models for semantic descriptions in IoT (e.g. similar to the W3C SSN approach)
- 16. References and links • Suparna De, et al, Service modelling for the Internet of Things – http://www.iot‐a.eu/public/public‐documents/documents‐1/1/2/service‐ modelling‐for‐the‐internet‐of‐things/at_download/file • W3C SSN – http://www.w3.org/2005/Incubator/ssn/XGR‐ssn‐20110628/ • Claudia Villalonga, A Resource Model for the Real World Internet – http://www.springerlink.com/content/ejxm56331g8w7rk2/fulltext.pdf
- 17. Thank you!