Ld make sensorssing_slideshare

Semantic-Service Provisioning for theInternet of Things using Future Internet Research by Experimentation www.spitfire-project.eu

Linked Data make sensors sing
Myriam Leggieri
DERI, NUI Galway

myriam.leggieri@deri.org

Sensors matter

Bridge between the real and the digital world

enhanced by

What we do not see

What happened where we couldn’t be

A thief in our house

Not working equipment

Product going to waste

On a small scale...

What we do not see
How healthy was your walk?

Temperature
Radiation

Noise

Diseases
Location Air quality

Distance from Home

What we do not see

What happened where we couldn’t be

On a large scale

What we can not see

Radiation level? Air quality?

What we can not see

Limited human capabilities need to be enhanced by
devices

Democratic awareness

Sensors for people

Conclusion: Sensors matter.

How to get a sensor?

Sensors are all around
and cheap

Sensors for people

Conclusion: Sensors are everywhere.

This matters.

...

For who?

Sensor for people

Few users of sensor-based mobile apps.

Why?

Sensors for people - Issues

Different information / sources need integration

Temperature
Radiation

Noise

Diseases

Distance from Home


1. Integrate different information

Temperature
Radiation

Noise

Diseases

Distance from Home


2. Integrate different domains

Temperature
Radiation

Noise

Diseases

Environmental

Distance from Home Life Science

Geography

3. Integrate different sources Government

Sensors for people – Solution

Linked Data

Linked Data representation

1. HTTP Unique Names for Things

Color

? Dereferencable URI
http://www.example.com/color


2. semantic description
Temperature

Identifiable single data

Unambiguous
Hierarchical Knowledge



Unambiguous for machine -> no ad-hoc schema

Ad-hoc Schema Natural Language
Web Page
XML
subjverbobjsubjve
rbobjsubjverbobjs
ubjverbobj..
subjverbobjsubjve
rbobj......




Tables

Trees
Graphs
Easy merging
source: http://www.w3.org/2006/Talks/0216-semweb-em/




RD
F
source: http://www.w3.org/2006/Talks/0216-semweb-em/



SPARQL query

SPARQL query language to extract and/or merge data



SPARQL query

+
graph name

SPARQL query run against “Named Graphs”



SPARQL query

External triples/named graphs imported


Federated query: remotely queried datasets

Source: http://www.slideshare.net/LeeFeigenbaum/sparql-cheat-sheet

Federated Query example

UK legislation
+
QR-Code based digital zoom images

Source:http://www.delicious.com/kidehen/sparql_fed_demo


3. meaningful linkage

http://../Braunschweig Germany
http://.../isPartOf

motivation assigned to the link


LOD cloud: publicly available datasets

2007

2008
2010


LOD cloud: publicly available datasets
2011

<div itemscope itemtype="http://data-vocabulary.org/Person"> My name is <span itemprop="name">Bob Smith</span> but people call me <span itemprop="nickna

Adding semantics in other ways than RDF

Source: http://manu.sporny.org/2011/uber-
comparison-rdfa-md-uf/


support Microformats, Microdata, RDFa

Google’s Rich Snippet (2009)

Facebook’s Open Graph (2010)

Schema.org (2011)


Microformats, Microdata -> RDF

Sindice indexes semantics from anywhere

Radiation Temperature

Noise
Diseases Location Air quality

Distance from Home

Not all of these data are yet available but
support from

Linked Data vocabularies

IEEE standards to allow seamless device interaction

Bluetooth standard

Standards

Rigid approach

Standards

Rigid approach

Resource expensive

Standards

Rigid approach

Resource expensive

A full agreement is never reached


Semantic ontologies have a democratic approach
Agreement

Meanwhile...

People Opinions

ontology reusage + link with abstratc concepts
=
constant reciprocal undertanding


Vocabularies are indexed and ranked

Easy finding ontology concepts to reuse

source: http://labs.mondeca.com/dataset/lov/search

Sensor ontologies

CESN Ontology
A3M3 Ontology
MMI Device Ontology SWAMO Ontology

W3C SSN-XG Ontology

SSN cross-domain sensor ontology easily pluggable with
other domain-specific ones

Outcomes: SPITFIRE ontology

Bringing sensors in the LOD and abstract on top of them

Outdoor Place Sensing Context
W3C SSN-XG Ontology +
Event Model F ontology Historical Archive
W3C SSN-XG plugged with other concepts

Available at: http://spitfire-project.eu/cc/spitfireCC_n3.owl

Outcomes

Smart Service Proxy (SSP)
Henning Hasemann, Oliver Kleine, Alexander Kroeller
RDF4Sensors
myself

live sensor data published online as Linked Data

dynamically aggregatable according to higher concepts

Outcomes – RDF4Sensors

Try it yourself at
http://spitfire-project.eu/
incontextsensing/rdf4sensors.php
and SSP at
http://spitfire.ibr.cs.tu-bs.de:8080/

Outcomes – inContext-Sensing

External links searched through Sindice by customizable
criteria

Personal Outcomes

SPITFIRE ontology

inContext Sensing: customizable external linkage

RDF4Sensors: REST API + HTML form to provide
semantic sensor description

Investigate on usefulness / meaningfulness
of Linked Sensor Data

LD make sensors sing

Temperature
Radiation

Noise

Diseases

Distance from Home

LD make sensors sing

Radiation Temperature

Diseases
Location
Noise

Distance from Home Air quality

DERI – Sensors and Semantics
part of the DERI people working on Sensors and Semantics

http://sensormasher.deri.org
RDF Storage and Query Processor for Android phones

Data Stream querying

Prof. Manfred Hauswirth

M. Hausenblas M. Karnstedt D. Le Phuoc J.X. Parreira myself
http://www.deri.ie/about/team/

DERI, NUIG, Ireland

DERI

DERI, NUIG, Ireland

National Univ. of Ireland, Galway
Galway
DERI

Thanks to such additional context
now you will not forget about DERI


Ld make sensorssing_slideshare

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