IERC AC4 SEMANTIC INTEROPERABILITY WORKSHOP

farmpaintlickInternet and Web Development

Oct 21, 2013 (4 years and 22 days ago)

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Generic Adaptive Middleware for

Behavior
-
driven Autonomous Services

Universität

Duisburg
-
Essen


ETRA
Investigación

y
Desarrollo
, S. A.

National University of Ireland, Galway

The Open University

SpeechConcepts

GmbH & Co. KG


Empresa

Municipal de
Transportes

de Madrid, S. A.

IERC AC4 SEMANTIC INTEROPERABILITY WORKSHOP

IoT

Week 2012

Josiane Parreira

Generic Adaptive Middleware for

Behavior
-
driven Autonomous Services

GAMBAS


Objectives


Development
of a
generic adaptive middleware
for behavior
-
driven autonomous services that encompasses:


Models and infrastructures to support the
interoperable representation
and scalable processing of context
.


Frameworks and methods to support the
generic yet resource
-
efficient
multi
-
modal recognition of context
.


Protocols and tools to
derive
, generalize,
and enforce
user
-
specific
privacy
-
policies
.


Techniques and concepts to optimize the interaction

with behavior
-
driven services.


Validation of the middleware

using
lab tests and a prototype
application
in the public transportation domain
.

2

Generic Adaptive Middleware for

Behavior
-
driven Autonomous Services

GAMBAS Scenario

3


Generic Adaptive Middleware for

Behavior
-
driven Autonomous Services

Interoperability issues


Heterogeneous devices


Heterogeneous data representations


Heterogeneous APIs


Lack of data semantics describing data meaning


Resource constrained devices


Sensors, mobile devices


Dynamic, frequently changing information


e.g., stream data from sensors


Large
-
scale, distributed networks


Data needs to be discoverable

Generic Adaptive Middleware for

Behavior
-
driven Autonomous Services

GAMBAS approach t
owards interoperability


Linked Data paradigm to describe sensors and data streams


Associate meaning to raw data (e.g.
feature of interest, accuracy,
measuring condition, time point, location, etc. )


Unified, yet flexible data representation


Integration with other existing Linked Data infrastructures.


Analysis of current sensor semantic descriptions


Semantic Sensors Networks ontology


Semantic annotations for
OGC’s

SWE Sensor Model Language


Development of required formalisms and ontologies to support
semantic descriptions at sensor level

Generic Adaptive Middleware for

Behavior
-
driven Autonomous Services

GAMBAS approach t
owards interoperability


Infrastructure to explore data storage and processing capabilities
of mobile devices


SPARQL
-
like access down to the sensor level (lightweight)


Allow RDF Stream processing


Support generation of query execution plans that

not only consider
network and physical costs but also adapt to the dynamics of the data


Means of exchanging the descriptions of the data and devices


Allow devices to find relevant data, without knowing a priori the data’s
particular location.


Develop infrastructures to support the discovery of dynamic data





Generic Adaptive Middleware for

Behavior
-
driven Autonomous Services

References


D.
Bimschas
,

H.
Hasemann
,

M.
Hauswirth
,

M.
Karnstedt
,

O.
Kleine
,

A.
Kröller
,
M.
Leggieri
,

R.
Mietz
,

A. Passant,

D.

Pfisterer
,

K.
Römer
,

C. Truong: Semantic
-
Service Provisioning for the Internet of Things. ECEASST 37: (2011)



A. P.
Sheth
, C. A. Henson, and S. S.
Sahoo
. Semantic Sensor Web. IEEE
Internet Computing, 12(4):78
-
83, 2008.


E.
Bouillet
, M.
Feblowitz
, Z. Liu, A.
Ranganathan
, A.
Riabov
, F. Ye, A
semantics
-
based middleware for utilizing heterogeneous sensor networks, in:
DCOSS, 2007.


Whitehouse, K., Zhao, F., Liu, J.: Semantic streams: A framework for
composable

semantic interpretation of sensor data. In: EWSN’06. (2006)


Christian
Bizer
,

Tom Heath,

Tim Berners
-
Lee: Linked Data
-

The Story So
Far.

Int. J. Semantic Web Inf. Syst. 5(3): 1
-
22 (2009)



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