LOV4IoT: A second life for ontology-based domain knowledge to build

Semantic Web of Things applications

FiCloud 22-24 August 2016,Vienna, Austria

Amelie Gyrard, Insight, Ireland Christian Bonnet, Eurecom, France Karima Boudaoud, University of Nice Sophia Antipolis France Martin Serrano, Insight, Ireland

Agenda

• Introduction & Motivation Semantic Web Technologies Linked Open Vocabularies (LOV)

• Contribution: LOV4IoT: Linked Open Vocabularies for Internet of Things

• Use Case: Machine-to-Machine Measurement (M3) framework FIESTA-IoT ontology

• Conclusion & Future work

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How to interpret Internet of Things (IoT) data?

Thermometer

Sensor data

Applications to visualize data

Interpretation by humans

How machines can interpret data?

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Machine learning? Reusing domain knowledge?

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Reusing domain knowledge already designed in existing IoT applications

=> Our literature survey shows than more 300 projects are using semantic web technologies

Domain knowledge to build IoT applications is already designed and available on the Web.

Classify Interoperability

Collect

How to exploit the domain knowledge available on the Web

and make it interoperable?

Why using Semantic Web Technologies within IoT? • Share and reuse structured and already designed domain

knowledge (e.g., ontologies)

• Interconnecting datasets

• Machine-understandable data

• Describing data with common vocabularies

• Facilitating reasoning to interpret sensor data

Related Work: Ontology Catalogues & Semantic Search Engines

• Ontology Catalogues – Linked Open Vocabularies

(LOV) – Ready4SmartCities

• Semantic Search Engines

http://lov.okfn.org/dataset/lov/ http://www.ready4smartcities.eu/

=> Numerous ontologies relevant for IoT are not referenced yet due to a lack of unknown semantic web best practices

Contribution: LOV4IoT

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• Linked Open Vocabularies for Internet of Things (LOV4IoT) o Extension of Linked Open Vocabularies (LOV)

• A dataset of more than 300 ontology-based projects relevant for IoT – Ontologies, Datasets, Rules, Technologies, Sensors and

Domains

A second life for ontologies!

LOVIoT: http://www.sensormeasurement.appspot.com/?p=ontologies

LOV: http://lov.okfn.org/dataset/lov/

9 http://www.sensormeasurement.appspot.com/?p=ontologies

=> Classification by domains

=> Classification according semantic web best practices

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Extracting and Combining domain knowledge

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Improving domain knowledge

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Combining domain knowledge through rules

Interoperable semantic-based IoT applications

Unify IoT data and domain knowledge

Use case 1: The Machine-to-Machine Measurement (M3) Framework

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http://sensormeasurement.appspot.com/

Interoperable security

knowledge base

Dataset of domain knowledge for IoT

Dataset of interoperable rules

Use case 1: SWoT generator

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*

Interoperable semantic-based IoT

applications

* Domain where is deployed the sensor, not the applicative domain

=> Benefits: No need to learn semantic web technologies

Use case 1: SWoT template - interoperable domain knowledge

• Need to have the set of files generated in the template compatible with sensor data – Ontologies + datasets + rules + sensor data – Domain knowledge structured in the same way

Domain ontologies

Domain datasets

Rules

Interoperable IoT

Application

Provide sensor data

SWoT template Unified IoT data

Produce

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Demo

16 http://sensormeasurement.appspot.com/?p=m3api

• Generating a template to design a Semantic Web of Things application by reusing domain knowledge

Demo

17 http://sensormeasurement.appspot.com/?p=transport

• Template used to build this application:

=> Interoperable domain knowledge is used to interpret IoT data

Demo: Smart cars

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• FIESTA-IoT ontology reuses and aligns a set of IoT ontologies – IoT-lite, M3-lite Taxonomy, SSN and DUL.

• Analysis based on LOV4IoT referencing

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Use case 2: FIESTA-IoT ontology

https://mimove-apps.paris.inria.fr/ontology/fiestaIoT.html

=> 24 ontologies for sensor networks and 21 for Internet of Things

Conclusion & Future work

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• LOV4IoT encourages: – Reusing domain knowledge already designed and

available on the Web. – Designing interoperable semantic-based IoT applications

• Future Work:

– Automatically update LOV4IoT with: • User’s suggestions • Ontology catalogues • Semantic web search engines

– Extracting domain knowledge • Ontology matching, extraction of rules, etc.

Thank you!

• amelie.gyrard@insight-centre.org • http://sensormeasurement.appspot.com/ • Slideshare • Twitter

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