FinalSWT Presentation.ppt
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Transcript of FinalSWT Presentation.ppt
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User-driven Ontology Evolution
Management
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Introduction
Ontology evolution is the timely adaptation of an ontology to
changed business requirements, to trends in ontology instances
and patterns of usage .
A modification in one part of the ontology may generate subtleinconsistencies in other parts of the same ontology, in the
ontology based instances as well as in depending ontologies and
applications.
We specifically focus on the problem that ontology has to remain
consistent under complex changes during evolution.
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Ontology Evolution Requirements
ontology evolution require following set of design requirements
The first requirement is the essential one for any ontology evolutionapproach after applying a change to a consistent ontology, the ontologyshould remain in consistent state. It has to enable resolving the givenontology changes and ensure the consistency of the underlying ontology and
all dependent artifacts.
The second requirement complements the first one by presenting the userwith information needed to control changes and make appropriate decisionsIt should be supervised allowing the user to manage changes more easily.
The last one states that potential changes improving the ontology may bediscovered semi automatically from ontology-based data and throughanalysis of users behavior It should offer advice to user for continualontology refinement.
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Ontology evolution process
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Ontology evolution process
It consist of Six Phases as follows
(1) Change Capturing
(2) Change Representation
(3) Semantics of Change
(4) Change Implmentation
(5) Change Propagation
(6) Change Validation.
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Change Capturing
The process of ontology evolution starts with capturing changes
either from explicit requirements or from the result of change
discovery methods, which induce changes from patterns in data
and usage.
It has two types of change Discovery usage-driven and data-
driven change discovery.
Usage-driven changes result from the usage patterns created over
a period of time
Data-driven change discovery as the problem of deriving
ontological changes from the ontology instances by applyingtechniques such as data-mining, Formal Concept Analysis (FCA)
or various heuristics.
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Consistency requirement states that after applying and resolving
changes in an ontology already in a consistent state, the ontology,
its instances and dependent ontologies/applications must remain
in the consistent state.
Data-driven change discovery can be defined as the task of
deriving ontology changes from modifications to the knowledge
from which the ontology has been constructed.
Change Capturing
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To resolve changes, they have to be identified and represented in
a suitable format which means that the change representation
needs to be defined for a given ontology model.
The set of ontology change operations depends heavily on the
underlying ontology model
A lot of unnecessary changes may be performed if each change isapplied alone.
There is an impedance mismatch between the intent of the
request and the way the intent is achieved.
To avoid these drawbacks, it should be possible to expresschanges on a more coarse level, with the intent of change directly
visible.
Change Representation
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Semantics of Change
Application of an elementary change in the ontology can induce
inconsistencies in other parts of the ontology.
Syntax inconsistency arises when undefined entities at the
ontology or instance level are used or ontology model constraints
are invalidated.
Semantic inconsistency arises when meaning of an ontologyentity is changed due to changes performed in the ontology
If an ontology is large, it may be difficult to fully comprehend
the extent and meaning of each induced change.
The task of semantics of change phase is to enable resolution ofinduced changes in a systematic manner, ensuring consistency of
the whole ontology.
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Semantics of Change The authors describe the semantics of change for the consistent
evolution of OWL ontologies, considering the structural, logical,
and user-defined consistency conditions
Structural Consistency ensures that the ontology obeys the
constraints of the ontology language with respect to how the
constructs of the ontology language are used. consistent.
Logical Consistency regards the formal semantics of the
ontology: viewing the ontology as a logical theory, an ontology
as logically consistent if it is satisfiable, meaning that it does not
contain contradicting information.
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Semantics of Change
User-defined Consistency: Finally, there may be definitions of
consistency that are not captured by the underlying ontology
language itself, but rather given by some application or usage
context. The conditions are explicitly defined by the user andthey must be met in order for the ontology to be considered
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Semantics of Change
Author describes and compares two approaches to verify
ontology consistency:
1) A posteriori verification, where first the changes are executed,
and then the updated ontology is checked to determine whether it
satisfies the consistency constraints.
2) A priori verification, which defines a respective set of
preconditions for each change. It must be proven that, for each
change, the consistency will be maintained if an ontology isconsistent prior to an update and the preconditions are satisfied.
Ch I l i
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Change Implementation
The role of the change implementation phase of the ontology
evolution process is
(i) to inform an ontology engineer about all consequences of a
change request
(ii) to apply all the (required and derived) changes and
(iii) to keep track of performed changes
Change Notification: In order to avoid performing undesired
changes, a list of all implications for the ontology and dependent
artefacts should be generated and presented to the ontology
engineer, who should then be able to accept or abort these
changes.
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Change Implementation
Change Application: The application of a change should have
transactional properties, that is (A) Atomicity, (C) Consistency,
(I) Isolation, and (D) Durability. This approach realizes the
requirement by strict separation between the request specification
and the change implementation
Change Logging: There are various ways to keep track of the
performed changes The evolution ontology covers the various
types of changes, dependencies between changes as well as the
decision-making process.
Ch P ti
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Change Propagation
When the ontology is modified, ontology instances need to be
changed to preserve consistency with the ontology.
This can be performed in three steps
The instances are on the Web, collected from the knowledge base
In the second step, modification of instances is performed
according to the changes in the ontology
In the last step out-of-date instances on the Web are replaced
with corresponding up-to-date instances.
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Change Propagation
So when an ontology is changed, applications based on the
changed ontology may not work correctly
An ontology evolution approach has to recognize which change
in the ontology can affect the functionality of dependent
applications and to react correspondingly
Ch V lid ti
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Change Validation
There are numerous circumstances where it can be desirable to
reverse the effects of the ontology evolution
It is the task of the change validation phase to recover from these
situations
Change validation enables justification of performed changes
or undoing them at users request
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Ontology Evolution Process
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Ontology Evolution Process The overall ontology evolution process derived from our
discussion of ontology evolution requirements is presented in
Figure 3.
It has a cyclic structure, since validation of realized changes may(automatically) induce new changes in order to obtain model
consistency or to satisfy users expectations.
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Conclusion
In this way we have studied the approach of Ontologyevolution which is based on a six-phase evolution
process.
Which systematically analyses the causes and the
consequences of the changes and ensures the
consistency of the ontology and depending artifacts
after resolving these changes
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Thank You