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![Page 1: Towards a hybrid approach to context modelling, reasoning and interoperation Karen Henricksen CRC for Enterprise Distributed Systems Technology (DSTC)](https://reader036.fdocuments.us/reader036/viewer/2022072005/56649ce65503460f949b3b9e/html5/thumbnails/1.jpg)
Towards a hybrid approach to Towards a hybrid approach to context modelling, reasoning and context modelling, reasoning and
interoperationinteroperation
Karen Henricksen
CRC for Enterprise Distributed Systems Technology
(DSTC)
Steven Livingstone and Jadwiga Indulska
School of Information Technology and Electrical
Engineering, The University of
Queensland
![Page 2: Towards a hybrid approach to context modelling, reasoning and interoperation Karen Henricksen CRC for Enterprise Distributed Systems Technology (DSTC)](https://reader036.fdocuments.us/reader036/viewer/2022072005/56649ce65503460f949b3b9e/html5/thumbnails/2.jpg)
MotivationMotivation
Context modelling requirements:
Formality
Support for efficient reasoning
Support for imperfect context information (imprecise, ambiguous, incomplete information)
Appropriate abstractions to support requirements analysis, design and programming tasks
Support for interoperability
![Page 3: Towards a hybrid approach to context modelling, reasoning and interoperation Karen Henricksen CRC for Enterprise Distributed Systems Technology (DSTC)](https://reader036.fdocuments.us/reader036/viewer/2022072005/56649ce65503460f949b3b9e/html5/thumbnails/3.jpg)
BackgroundBackground
We have been building context-aware applications and infrastructure for several years using our own layered modelling approach
Our approach: leverages proven information modelling techniques developed by
the IS community provides two levels of abstraction:
facts situations
To evaluate possible extensions to our modelling approach, we: performed a comparison with recently proposed ontology
approaches investigated the potential benefits of a hybrid approach
![Page 4: Towards a hybrid approach to context modelling, reasoning and interoperation Karen Henricksen CRC for Enterprise Distributed Systems Technology (DSTC)](https://reader036.fdocuments.us/reader036/viewer/2022072005/56649ce65503460f949b3b9e/html5/thumbnails/4.jpg)
A comparison of context modelling A comparison of context modelling approachesapproaches
Requirements Our approach Ontology-based approaches
Formality
Support for efficient reasoning (but potential exists
to extend supported types of reasoning)
Possible but tools for new standards
are still limited
Support for imperfect
information
Possible but difficult (especially reasoning)
Abstractions for design/programmi
ng
Interoperability
![Page 5: Towards a hybrid approach to context modelling, reasoning and interoperation Karen Henricksen CRC for Enterprise Distributed Systems Technology (DSTC)](https://reader036.fdocuments.us/reader036/viewer/2022072005/56649ce65503460f949b3b9e/html5/thumbnails/5.jpg)
Overview of our modelling approachOverview of our modelling approach
We model context as follows: fact types (and constraints) are modelled graphically using
CML
situations are defined in terms of logical expressions over fact types and variables
CML provides a natural graphical notation to support design and requirements analysis tasks
Situations and context-dependent preferences (expressed in terms of situations) are used as a basis for our programming models
![Page 6: Towards a hybrid approach to context modelling, reasoning and interoperation Karen Henricksen CRC for Enterprise Distributed Systems Technology (DSTC)](https://reader036.fdocuments.us/reader036/viewer/2022072005/56649ce65503460f949b3b9e/html5/thumbnails/6.jpg)
CML modelling conceptsCML modelling concepts
Special fact types: Static, sensed, derived, profiled
Historical
Alternative/ambiguous
Quality-annotated
![Page 7: Towards a hybrid approach to context modelling, reasoning and interoperation Karen Henricksen CRC for Enterprise Distributed Systems Technology (DSTC)](https://reader036.fdocuments.us/reader036/viewer/2022072005/56649ce65503460f949b3b9e/html5/thumbnails/7.jpg)
CML exampleCML example
Person(name)
Device(id)
located near
permitted to use
Activity(name)
engaged in
[ ]
Comm.channel(id)
has channel
Location(name)
located ata
*
requires device
Comm.mode(name)
has mode
s
s
located at
a
synchronous
Certainty
Probability(nr)+
Legend
Object type
Fact type
Static fact type
Sensed fact type
Derived fact type
Profiled fact type
Alternative fact type
Historical fact type
Uniqueness (key)Constraints
Dependency
*
a
[ ]
s
![Page 8: Towards a hybrid approach to context modelling, reasoning and interoperation Karen Henricksen CRC for Enterprise Distributed Systems Technology (DSTC)](https://reader036.fdocuments.us/reader036/viewer/2022072005/56649ce65503460f949b3b9e/html5/thumbnails/8.jpg)
Modelling situationsModelling situations
Defined using a novel form of predicate logic Contain variables (application context) and fact types
(shared context) Examples:
CanUseChannel(person, channel) :forall device ● RequiresDevice[channel, device] ● LocatedNear[person, device] and PermittedToUse[person,
device]
![Page 9: Towards a hybrid approach to context modelling, reasoning and interoperation Karen Henricksen CRC for Enterprise Distributed Systems Technology (DSTC)](https://reader036.fdocuments.us/reader036/viewer/2022072005/56649ce65503460f949b3b9e/html5/thumbnails/9.jpg)
Related work: ontology-based Related work: ontology-based approachesapproaches
Many context ontologies have recently appeared based on new standards such as OWL
These support reasoning for: Derivation of new types of context information Detection and correction of inconsistencies Evaluation of privacy policies (e.g., eWallet, CoBrA)
Shortcomings: Reasoning is being held back by immature standards/tools Good potential for interoperability, but not yet realised Focus is on modelling and reasoning, not on provision of
software engineering abstractions
![Page 10: Towards a hybrid approach to context modelling, reasoning and interoperation Karen Henricksen CRC for Enterprise Distributed Systems Technology (DSTC)](https://reader036.fdocuments.us/reader036/viewer/2022072005/56649ce65503460f949b3b9e/html5/thumbnails/10.jpg)
Towards a hybrid approachTowards a hybrid approach
We have evaluated extending our approach to use ontology concepts for: modelling additional concepts that are not well supported
by CML reasoning for:
deriving additional context information model checking interoperation
Our evaluation focused on: OWL: The new W3C standard and currently most popular
ontology language SWRL: Extends OWL with rules by merging OWL and RuleML
![Page 11: Towards a hybrid approach to context modelling, reasoning and interoperation Karen Henricksen CRC for Enterprise Distributed Systems Technology (DSTC)](https://reader036.fdocuments.us/reader036/viewer/2022072005/56649ce65503460f949b3b9e/html5/thumbnails/11.jpg)
Using ontology concepts for Using ontology concepts for context representationcontext representation
To compare our current representation with an ontology-based representation, we: Mapped our current modelling concepts into an OWL
representation Evaluated the potential to extend this to capture
additional concepts Results:
Positives of ontology representation: Reuse of concepts is straightforward Meta-modelling: can model the modelling concepts
themselves (and reason about them) Can model some additional properties such as transitivity
![Page 12: Towards a hybrid approach to context modelling, reasoning and interoperation Karen Henricksen CRC for Enterprise Distributed Systems Technology (DSTC)](https://reader036.fdocuments.us/reader036/viewer/2022072005/56649ce65503460f949b3b9e/html5/thumbnails/12.jpg)
Using ontology concepts for Using ontology concepts for context representation (continued)context representation (continued)
Negatives:
Unnatural to model complex relationships in OWL (must be represented as objects rather than properties)
OWL provides no built-in support for expressing uncertainty
Verbose (in contrast to CML’s user-friendly graphical notation)
![Page 13: Towards a hybrid approach to context modelling, reasoning and interoperation Karen Henricksen CRC for Enterprise Distributed Systems Technology (DSTC)](https://reader036.fdocuments.us/reader036/viewer/2022072005/56649ce65503460f949b3b9e/html5/thumbnails/13.jpg)
Using reasoning to derive additional Using reasoning to derive additional context informationcontext information
OWL can support reasoning based on relations such as transitivity and commutativity
OWL does not currently support axiomatic rules (but these can be expressed in SWRL)
We compared our situation-based reasoning approach with an SWRL rules approach by attempting to map situations to rules
![Page 14: Towards a hybrid approach to context modelling, reasoning and interoperation Karen Henricksen CRC for Enterprise Distributed Systems Technology (DSTC)](https://reader036.fdocuments.us/reader036/viewer/2022072005/56649ce65503460f949b3b9e/html5/thumbnails/14.jpg)
Example mappingExample mapping
Situation: CanUseChannel(person, channel) :
forall device ● RequiresDevice[channel, device] ● LocatedNear[person, device] and PermittedToUse[person, device]
SWRL rule:<ruleml:imp> <ruleml:_body> <swrlx:classAtom> <owlx:Class owlx:name="&cml;RequiresDevice"/> <ruleml:var>requiresDevice</ruleml:var> </swrlx:classAtom> <swrlx:individualPropertyAtom swrlx:property="&cml;RequiresDeviceChannel"> <ruleml:var>requiresDevice</ruleml:var> <ruleml:var>channel</ruleml:var> </swrlx:individualPropertyAtom>
![Page 15: Towards a hybrid approach to context modelling, reasoning and interoperation Karen Henricksen CRC for Enterprise Distributed Systems Technology (DSTC)](https://reader036.fdocuments.us/reader036/viewer/2022072005/56649ce65503460f949b3b9e/html5/thumbnails/15.jpg)
Example mapping (continued)Example mapping (continued)
<swrlx:individualPropertyAtom swrlx:property="&cml;RequiresDeviceDevice"> <ruleml:var>requiresDevice</ruleml:var> <ruleml:var>device</ruleml:var> </swrlx:individualPropertyAtom> <swrlx:classAtom> <owlx:Class owlx:name="&cml;LocatedNear"/> <ruleml:var>locatedNear</ruleml:var> </swrlx:classAtom> <swrlx:individualPropertyAtom swrlx:property="&cml;LocatedNearPerson"> <ruleml:var>locatedNear</ruleml:var> <ruleml:var>person</ruleml:var> </swrlx:individualPropertyAtom> <swrlx:individualPropertyAtom swrlx:property="&cml;LocatedNearDevice"> <ruleml:var>locatedNear</ruleml:var> <ruleml:var>device</ruleml:var> </swrlx:individualPropertyAtom>
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Example mapping (continued)Example mapping (continued)
<swrlx:classAtom> <owlx:Class owlx:name="&cml;PermittedToUse"/> <ruleml:var>permittedToUse</ruleml:var> </swrlx:classAtom> <swrlx:individualPropertyAtom swrlx:property="&cml;PermittedToUsePerson"> <ruleml:var>permittedToUse</ruleml:var> <ruleml:var>person</ruleml:var> </swrlx:individualPropertyAtom> <swrlx:individualPropertyAtom swrlx:property="&cml;PermittedToUseDevice"> <ruleml:var>permittedToUse</ruleml:var> <ruleml:var>device</ruleml:var> </swrlx:individualPropertyAtom> </ruleml:_body> <ruleml:_head> <swrlx:individualPropertyAtom swrlx:property="CanUseChannel"> <ruleml:var>person</ruleml:var> <ruleml:var>channel</ruleml:var> </swrlx:individualPropertyAtom> </ruleml:_head></ruleml:imp>
![Page 17: Towards a hybrid approach to context modelling, reasoning and interoperation Karen Henricksen CRC for Enterprise Distributed Systems Technology (DSTC)](https://reader036.fdocuments.us/reader036/viewer/2022072005/56649ce65503460f949b3b9e/html5/thumbnails/17.jpg)
Using reasoning to derive additional Using reasoning to derive additional context information (continued)context information (continued)
Evaluation:
SWRL does not offer a natural way to reason over uncertain context information (in contrast, we support ambiguous and incomplete information using a three-valued logic)
SWRL representation is verbose and unwieldy (but a more compact notation can be used)
Situation logic’s explicit quantification is more natural than SWRL’s implicit quantification
![Page 18: Towards a hybrid approach to context modelling, reasoning and interoperation Karen Henricksen CRC for Enterprise Distributed Systems Technology (DSTC)](https://reader036.fdocuments.us/reader036/viewer/2022072005/56649ce65503460f949b3b9e/html5/thumbnails/18.jpg)
Using reasoning for model checkingUsing reasoning for model checkingand interoperation and interoperation
In OWL, can capture: relationships between concepts (e.g., equivalence of
classes and properties) various constraints (e.g., restrictions on property values)
Can use these to reason about models (both for model checking and interoperation)
Model checking examples: can define static fact types in a way that precludes other
classifications such as temporal or sensed can check for valid uniqueness constraints on fact types,
cyclic dependencies, etc.
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Using reasoning for model checkingUsing reasoning for model checkingand interoperation (continued)and interoperation (continued)
Interoperation examples:
can define equivalence between classes or properties to transfer information between context models
can define (SWRL) rules for translating different representations
![Page 20: Towards a hybrid approach to context modelling, reasoning and interoperation Karen Henricksen CRC for Enterprise Distributed Systems Technology (DSTC)](https://reader036.fdocuments.us/reader036/viewer/2022072005/56649ce65503460f949b3b9e/html5/thumbnails/20.jpg)
ConclusionsConclusions
Ontology-based reasoning about context offers few benefits over situation-based reasoning
We are most interested in ontology-based reasoning over context models
Current ontology approaches do not fully explore the potential of this type of reasoning
We are exploring a hybrid approach in which we: model using our CML and situation abstractions incorporate ontology-based reasoning about the models
into our tools/infrastructure for model checking and interoperation