Doc# 533571745
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I NPUT C ONTRIB UTION
Meeting ID*
TP#16
Title:*
Modeling aspects for mash-up
Source:*
<Junling Mao> , <China Unicom> , <maojl11@chinaunicom.cn>
<Changwei Hu>, <China Unicom>, <hucw5@chinaunicom.cn>
<Peng Wang>, <China Unicom>, <wangpeng@chinaunicom.cn>
Uploaded Date:*
2015-03-10
Document(s)
oneM2M-TR-0007-Study_on_Abstraction_and_Semantics_Enablement
Impacted*
Intended purpose of
Decision
document:*
Discussion
Information
Other <specify>
Decision requested or
recommendation:*
For discussions and adoption in the Abstraction and Semantics Technical
Report.
Template Version:23 February 2015 (Dot not modify)
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oneM2M Notice
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The document to which this cover statement is attached is submitted to oneM2M. Participation in, or attendance at, any
activity of oneM2M, constitutes acceptance of and agreement to be bound by terms of the Working Procedures and the
Partnership Agreement, including the Intellectual Property Rights (IPR) Principles Governing oneM2M Work found in
Annex 1 of the Partnership Agreement.
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© 2015 oneM2M Partners
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1. Introduction
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The mash-up capability is considered to be required in oneM2M systems, since it can facilitate the
access of complicated parameters which cannot be directly measured by physical sensors and
support cooperative working of multiple devices. In this contribution, we give some considerations
on the modelling aspects supporting mash-up.
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2. Discussion
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According to the current device and things aspect association model in TR 0007, the mash-up relationships
can be modelled in three categories.
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1) Things category
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In this category, the mash-up relationship will be described from the perspective of things aspect. There
will be a semantic rule or ontology to state the natural relationship between the mash-up things aspect
and other related things aspects, e.g. the relationship between the air aspect Air quality index (AQI) and
other air aspects such as PM2.5, PM10, SO2 and NO2. This is highly related to the domain ontology of
air environment.
2) Devices category
In this category, the mash-up relationship will be described from the perspective of devices. There will
be a semantic rule or ontology to state the relationship between the operation of the mash-up devices and
the operations of other devices involved in the mash-up. Fig.1 gives an example for the mash-up
modelling in device category.
Cooling device
Mash-up device
hasOperation
hasOperation
cooling
hasOut
Set
Temperature
compositedBy
Mash-up
hasParameter
hasIn
Target Temperature
hasLogic
Mash-up logic
Temperature
Sensor
hasOperation
monitoring
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Fig.1 an example for mash-up modelling in device category
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3) Association category
In this category, the mash-up relationship will be described from the perspective of association. There
will be a semantic rule or ontology to state the association between the mash-up aspect and related
devices, e.g. the association between AQI and air quality related monitoring devices such as PM2.5,
PM10, SO2 and NO2 monitoring devices. This type of association is more complex than the current
association in TR 0007, since it will associate with multiple devices and a mash-up logic. Fig. 2 gives an
example for mash-up modelling in association category.
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SO2 monitoring
device
ROOM
hasOperation
hasSubAssociation
Operation
hasAspect
Air quality
index
hasAssociationA
spect
Mash-up
Measure
Association
Measure
SO2
hasLogic
Mash-up
Logic
PM2.5 monitoring
device
hasOperation
hasSubAssociation
Operation
Measure PM2.5
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Fig.2 an example for mash-up modelling in association category
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In Table I, we give the comparisons of above modelling methods. It can be observed that modelling in
devices category is preferred for the cooperative working case, and modelling in association category is
more suitable for the complicated parameter sensing case.
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Table I. comparisons of mash-up relationship modelling
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Advantages
Things
category
Weakness
• Natural expressions for the mash-up • hardly reflect the measured or
relationship
impact quality
• Independent from the type of devices • may need
associated with thing aspects
ontology
to
extend
domain
Devices
category
• easy for modelling the cooperative • not easy for reflecting the
working of multiple devices
measured quality for the mash-up
aspects impacted by the devices
• flexible for reconstructing the mashinvolved in mash-up.
up of devices
Association
category
• facilitate reflecting the measured or • not easy for modelling the
impact quality
cooperative working of multiple
devices
• flexible for reconstructing the mashup of devices
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In table II, we show the relationship between above modelling categories and the works in oneM2M.
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Table II. relationship between above modelling categories and works in oneM2M
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Related modelling
aspects
Things category
Devices category
Association category
Related to things
domain ontology
modelling
Highly related to the
modelling of virtual
devices created by the
mash-up of devices
Related to the
modelling of
association between the
reources involved in
mash-up and the target
things apsect;
(e.g. direct mash-up
association between the
data involved in mashup and the target things
aspect)
Relationship with
oneM2M
Out of scope of
oneM2M
In the scope of TR0007
For future evaluation
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In summary, modelling in devices category needs to be considered first, since the virtual devices created by
mash-up is already discussed in TR 0007 and we need to model this. In addition, considering the
compatibility of simultaneous modelling in above three categories and the benefits of modelling in
association category, in future if necessary we can discuss whether to adopt the modelling in association
category as supplement.
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3. Proposal
It is proposed to model the mash-up relationship in devices category and add the following
content to TR 0007.
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8.2.2.6 Modelling of mash-up devices
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The basic structure for modelling Devices is described in Fig. 27 of section 8.2.2.1.In that structure, specific
Device Types and successively Operation and Parameter Types are involved. The structure for modelling
mash-up device (i.e. the virtual device created by mash-up) should inherit the basic structure for modelling
devices, but may extend the basic structure for describing the mash-up relationship between mash-up devices
and other devices involved in mash-up. A concept named Mash-up is introduced for representing the mashup relationship.
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As shown in Fig. x, the Operation of mash-up device will be linked to the Mash-up concept. Besides
Operation of mash-up device, the Mash-up concept is also associated with Operations of other devices
involved in mash-up and a Mash-up logic concept.
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DeviceA
Mash-up Device
hasOperation
hasOperation
OperationA
hasParameter
ParameterA
hasOut
Operation1
compositedBy
Mash-up
hasLogic
Mash-up logic
DeviceB
hasParameter
hasIn
hasOperation
Parameter1
OperationB
hasParameter
ParameterB
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Fig.x Structure for modelling mash-up devices
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There are two types of relations between the Mash-up concept and Operations of other devices involved in
mash-up. One type indicates that the Operation plays an input role in the mash-up, i.e. the Parameter of the
Operation will be an input parameter in the mash-up. The other type indicates that the Operation plays an
output role in the mash-up, i.e. the Parameter of the Operation will be an output parameter in the mash-up..
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The Mash-up logic concept is used to describe the service logic used in the mash-up. It will have a data type
property (e.g. xsd: string) for logic expression to indicate the mapping relationship among the Parameters of
Operations of other devices involved in the mash-up and the Parameters of Operation of Mash-up Devices.
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Based on the logic expression of Mash-up logic, the input parameters of Operation of Mash-up Device will
be mapped to set the input Parameters of Operation involved in mash-up, and the output Parameters of
Operation involved in mash-up can be mapped to the set of output parameters of Operation of Mash-up
Device. The Parameters of Operation that plays input role in mash-up can also be mapped to set the
parameters of Operation that plays output role in mash-up.
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© 2015 oneM2M Partners
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