a context ontology for service provisioning and consumption
DESCRIPTION
Nowadays services as those provided by smart cities, health smart services, as well as common services (e.g., telephonic services, e-mail services), have a great economic impact for organisations and represent an important mean to deliver value to their consumers. The malfunctions of both the services themselves as well as the entities responsible for their execution and consumption might cause economic losses, consumers’ dissatisfaction and even shorten the service life cycle, among other risks. To avoid malfunctions beyond maintaining quality levels desired, it is important to take into account the widest possible context information that cause either positive or negative effects around services and entities involved in their provisioning and consumption. In this paper, we propose an upper ontology for service provisioning and consumption from a service-centric perspective. Specifically, we focus on software services, although we could argue for more generic applications. The contribution is the analysis, evaluation and reuse of existing proposals on context models to identify the strengths and weaknesses of its current status as well as to identify contexts not yet considered, and consolidate an integrated view of these proposals. The ultimate intention is to provide a well-defined and consolidated infrastructure of context information as a common body of knowledge, that could be instantiated on variety of use cases, for example, to be instantiated by monitors as context information useful to be monitored, or to be used as context information that allows knowing which contexts affect a service when a user consumes it, among others.TRANSCRIPT
A Context Ontology for Service Provisioning and Consumption
AuthorsM.C.C. Oscar Jair Cabrera Bejar
Dr. Xavier FranchDr. Jordi Marco
Research Challenges in Information Science (RCIS)May 28-30 2014, Marrakesh, Morocco
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Outline
Overview
Paper contribution
Ontology development process
• Specification
• Knowledge acquisition
• Conceptualization
Use case scenario
Conclusions & future workRC
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Overview
Services
Companies
Customers
Economic impact
Mean to deliver value
Malfunctions
Economic losses, consumers’ dissatisfaction,
shorten the service life cycle, …
Context
To avoid
K. Anind
“Context is any information that can be used to characterise the situation of an entity”
Service-centric perspective
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Seen from
Service provisioning and consumption
“An entity is a person, place, or object that is considered relevant to the interactionbetween a user and an application, including the user and applications themselves”
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Outline
Overview
Paper contribution
Ontology development process
• Specification
• Knowledge acquisition
• Conceptualization
Use case scenario
Conclusions & future workRC
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Paper contribution
Time
Location
Activity
Individuality
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Time
...
Service
…
Object
User
Place
Produce
Context Information
Service provisioning & consumption
Entities
Ontology
Paper contribution
State of the art Consolidate
context information
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Outline
Overview
Paper contribution
Ontology development process
• Specification
• Knowledge acquisition
• Conceptualization
Use case scenario
Conclusions & future workRC
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Documentation
Ontology development processR
CIS
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Methontology
Specification Knowledge acquisition Conceptualization
Integration Implementation Evaluation
Evolving prototype
DomainScope
Purpose
Sources of knowledge
State of theart
Conceptual model
Conceptualize the acquired knowledge
Integratedefinitions
Reusing
Ontologycodified
Avoidingwrong
definitions
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Outline
Overview
Paper contribution
Ontology development process
• Specification
• Knowledge acquisition
• Conceptualization
Use case scenario
Conclusions & future workRC
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SpecificationR
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DomainContext information causing either positive or negative effects on entities involved in service provisioning and consumption.
Scope
Delimited by relevant entities surrounding the domain specified.
Purpose Providing structured context knowledge from a service-centric perspective.
Specification overview
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Outline
Overview
Paper contribution
Ontology development process
• Specification
• Knowledge acquisition
• Conceptualization
Use case scenario
Conclusions & future workRC
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Knowledge acquisitionR
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Size5
Size4
Size3
Size2
Size1
3-6 7-10 11-14 15-183-6 7-10 11-14 15-18 19-22 23-26 27-30 +30
Nodes
Depth
level
Correlation map between nodes and depth levels Definition completeness
30 Papers were evaluated
Ontology-based
Categorization-based
UML-based
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Knowledge acquisitionR
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Category Context grouped Category Context grouped
Environment Physical
environment, User
environment,
Environmental parameters,
Environmental,
Pollution
Preferences Individual
dimension,
Individuality,
Personal, Interest-topic, interest,
Thing, Cognitive
pattern
Location Space, Place, Spatial, Living
conditions, Physical,
Indoor, Outdoor
Time Timestamp, Physical, temporal,
sporadic, periodic
Infrastructure Technical,
Technological,
Energy, Functional, Non-functional,
Quality of service,
QoWS
Activity Attention, State,
Goals, Tasks,
Object, Schedule, User history,
Action, Agenda
User action,
Event
Human
Factors
Relations, Medical
Social dimension,
Relationship, Agent, Community, contact,
Peers, Auxiliary,
Role Division of
Labour,
Holder, User role
Policy Rules,
Legal entity
Entity User, Person,
Service, Provider, third-party services
Profiles Information, characteristics, ability, education, profession,
expertise. Domain, Subscription information, identity
Resource Interaction means, Resource management, Resource specification, Informational, Tools, Service, Economic,
Device, Platform, Network, Application, System, Computing,
physical object, sensor, interface, connectivity, Computational, verbal, Value-added
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Outline
Overview
Paper contribution
Ontology development process
• Specification
• Knowledge acquisition
• Conceptualization
Use case scenario
Conclusions & future workRC
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ConceptualizationR
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Outline
Overview
Paper contribution
Ontology development process
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• Knowledge acquisition
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Use case scenario
Conclusions & future workRC
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Use case scenarioR
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Outline
Overview
Paper contribution
Ontology development process
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Use case scenario
Conclusions & future workRC
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Conclusions & future workR
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Presented the state of the art of context model proposals for software
services providing an overview on the field;
Made available a unified and consolidated upper ontology-based context
information;
To extend the state of the art addressed in this work in a form of
systematic mapping considering an extended panoramic view of context
model proposals;
To provide different resources from an ontological point of view, such as
the instantiation method, inference, reasoning and implementation, etc.;
Thanks for your attention
Comments and Questions
Xavier Franch, [email protected]
Oscar Cabrera, [email protected]
Jordi Marco, [email protected]