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Transcript of The role of semantics in eGovernment service model verification and evolution AAAI Spring Symposium...
The role of semantics in eGovernment service model verification and evolution
AAAI Spring Symposium 2006
Ljiljana Stojanovic, FZI
Andreas Abecker, FZI
Dimitris Apostolou, University of Pieraus
Gregoris Mentzas, ICCS,
Rudi Studer, AIFB
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Politicians define the law
Programmers write the code
Experts decide how to implement the law Process1 Process2 Process3Start End
End-users use a portal
How to cope with the changes?
X
The goal of the OntoGov project is to improve back-office processes by taking into account the whole lifecycle!!!
suppliers
customers
back-office
Semantic Web Service
ID
Name
Time
Date
City
OutputsInputs
Get Birthday
Information
Web ServiceWeb Service Description
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I1I2
O1O2O3
WS1I1I2
O1O2O3
WS2
I1I2
O1O2O3
WS
I1I2
O1O2O3
WS3
Monitor a document version
Analyse which activity to change
Plan how to achieve the consistency
Execute the required changes
Document X is changed
Activity Y has to be changedResource Z is not needed
Ontology Evolution generates additional changes and propagates
Effector (programmer modifies a code)
X
X
Sensor (add entry in a log)
XX
X
Change Management Framework
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Modelling e-Government services
Meta Ontologies define the schema i.e. the language for modelling the e-Government services
Domain-oriented Ontologies model the concrete e-Government services and all data relevant for these services
Administration Ontologies enable better management of e-Government services
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OntoGov model
LegalOntology
OrganisationalOntology
LifecycleOntology
DomainOntology
OntoGov ProcessOntology
OntoGovProfileOntology
Life-EventOntology
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Meta-ontology cluster
Legal Ontology defines the structure of the legal documents, which includes paragraphs, sections, amendments, etc.
Organisational Ontology models an organisation by defining its organisational units, roles, persons, resources etc.
Domain Ontology contains domain specific knowledge LifeEvent Ontology models the categorisation of the e-
Government services Process Ontology describes the elements for modelling the
process flow Profile Ontology contains metadata about e-Government
services and includes all previously mentioned ontologies Lifecycle Ontology describes the information flow and the
decision making process in the public administration
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Process Ontology
It is based on the OWL-S Process Ontology We distinguish between the services and the control
constructs Services can be either atomic or composite services We define a standard set of attributes such as name,
description, version, status etc. There are specific requirements concerning
retraceability, realisation, security, costs, etc. each service can be associated to the laws it is based upon each service can be associated to several software
components that implement it (i.e. dynamic binding) it is possible to assign security levels to each service information about cost and time restrictions can be also
specified Consistency conditions are formally defined
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Life-Event ontology
It is used for the classification of the e-government services
It includes concepts such as residential affairs, residential permissions, identification certifications, naturalization citizenship, moving, education etc.
It has been developed based on the existing standards for modelling lifeevents For example, the Swiss Standard eCH-001 (Best Practice
Structure Process Inventory - http://www.ech.ch) aims: to give an overview over all relevant e-government services
in Switzerland and to provide a consistent and standardized classification of the
services. The inventory comprises 1.200 e-government services
that are all services initialized by a citizen or internal administration processes
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Legal ontology
It models the structure of the legal documents, which includes paragraphs, sections, amendments We have analyzed the structure of legal documents in
Switzerland, Greece and Spain We concluded that the legal documents have very similar
structure independently of the country they are defined for Even though different countries use different terminology to organize
their legal documents, all of them use three levels of abstractions However, each country can extend (i.e. specialise or instantiate) it
as needed It is very important to document the laws and regulations the
process is based upon: not only for the whole process but also for specific activities
By associating legislation to these services, it is possible to trace and propagate the effects that a change in the legislation (or administrative regulations) produces on the models of the administrative services
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Organisational ontology
It describes the roles and areas of responsibility and capabilities within an organisation with respect to the activities of a process model
It models the structure of an organisation, its resources, know-how, etc. For example, we distinguish two types of resources:
human resources who perform an activity equipment (i.e. hardware, software etc.) that is occupied
by the activity
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Lifecycle ontology
It describes the decision-making process in the public administration
It bridges the gap between decision making and realisation by providing means: for describing these decisions and formally stating reasons that motivate the design
decisions
It provides answers on the following questions: “How have the process design (e.g. regarding atomic
activities) and flow (e.g. regarding control constructs) been realized?”
“Why has a design decision been taken?”
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Domain ontology
It encodes concepts of the public administration domain such as the “terminology” used in the e-government domain For example, it defines the type and structure of
documents such as passport
Input and output of an activity are represented using entities defined in this ontology
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“Announcement of moving” e-government service modelled using the OntoGov model
Lifecycle aspects
Design Decision 1:Eligibility handling
Reason I:Citizen must have Swiss domicile in order to perform automatic registration/deregistration
Related Instance(s):SR 101
SR 210 Art. 22A – 26A
Legal aspects
Organisational aspects
Domain InformationDomain Information
Domain InformationDomain Information
Domain InformationDomain Information
Domain InformationDomain Information
Domain InformationDomain Information
Domain InformationDomain Information
Domain InformationDomain Information
Domain aspects
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Role of ontologies Ontologies are used to model (formally and explicitly) e-
government services OntoGov Profile Ontology:
Used for advertising and discoveing e-government services Based on OWL-S Profile Ontology Extends it with e-government specific metadata
LifeEvent Ontology is used for the classification of the e-government services
OntoGov Process Ontology: Gives a detailed description of a process flow Based on OWL-S Process Ontology Extends it with:
e-government specific metadata (e.g. Legal Ontology) in order to enable better and easier management of services
set of rules: for defining consistency of a service description for resolving inconsistencies
Set of ontologies (i.e. Legal, Organisational, Domain, Lifecycle and LifeEvent) used for annotation of a service description
Are e-government specific Model different part of reality Contain only the top-level entities
Each public organisation can extend it e.g. by specializing concepts or by creating instances
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Ontologies are used to model aspects relevant for change management: Service Evolution ontology
It models what changes, why, when, by whom and how are performed in a service description, e.g.
Hierarchy of possible changes is developed based on the OntoGov model
They build the backbone of the change management system They correspond to the “conceptual” operation that someone wants to
apply without understanding the details (i.e. a set of ontology changes) that the management system has to perform
To enable reversibility as well as the synchronisation between different version of an ontology, this ontology includes:
the “cause-effects” dependency between changes a change may cause new changes in order to keep the service
model consistent the order in which the changes are requested
groups of changes of one request (requested or induced) are maintained in a linked list using the
Role of ontologies (cont.)
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Change Management Framework
OntologyEvolution
ChangeDetection
MM
AAPP EE
Evolution Ontology
Process1 Process2 Process3Start End
Law
Code
AA
E-GovernmentPortal
MM
Serviceontologies
Usage OntologyLifecycle Ontology
Evolution Log
Usage Log
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Change management
It has to enable the resolution of a given change in a systematic manner by ensuring the consistency of the whole ontology
InconsistencyDetection
ChangeGeneration
ChangeApplication
Change Resolution
Inconsistency Detection: It is responsible for checking of the consistency of an ontology with the respect to the ontology consistency definition. Its goal is to find ”parts” in the ontology that do not meet consistency conditions
Change Generation: It ensures the consistency of the ontology by generating additional changes that resolve detected inconsistencies
The approach requires: explicit specification of changes that can be applied the consistency definition
Changes have to preserve the consistency
18
Service consistency
Ontology consistency in general is defined as a set of conditions that must hold for every ontology
An e-Government service ontology is consistent: if it is ontology consistent and if it satisfies a set of consistency constraints defined for
the service model Consistency constraints have been defined in order to take
into account specificities of the Meta Ontologies Meta Ontologies represent the language for describing
services and therefore they define consistency of e-Government services
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Inconsistency detection
Two approaches are possible: The procedural approach - semantics is given by
a procedural mechanism that is capable of providing answer to wide class of consistency problems It traverses the process model and checks every entity
within on its consistency Difficult to cover all options, since models may be very
complex The declarative approach is based on the sound
and complete set of consistency rules (provided with an inference mechanism) that formalises the model It applies reasoning based on a set of consistency rules
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Incosistency detection
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Changes
Ontology changes include changes such “AddAxiom” and “RemoveAxiom”
To make a service s1 a predecessor of a service s2, a domain expert needs to apply a list of ontology changes that connects s1 to s2
Domain experts require a method for expressing their needs in an exacter, easier and more declarative manner
For a domain expert it would be more useful to know that he can connect two services rather than to know how to do that
Intent of changes has to be expressed on a more coarse level
22
Semantics of changes is specified It guarantees that a required change is correctly
propagated and that no inconsistency is left in the system Each change is described in a form:
Precondition - a set of assertions that must be true to be able to apply a change
Postcondition - a set of assertions that must be true after applying a change and it describes the result of a change
Actions are additional changes that have to be generated
E.g. RemoveAtomicService X Precondition – AtomicService X has been defined Postcondition – AtomicService X doesn‘t exist anymore Actions:
Remove all input links of AtomicService X; Remove all output links of AtomicService X; Remove all metadata defined for AtomicService X that includes:
the attributes such as name, description, fist and last service; the relations to the legal, organisational and domain ontology; the pre- and post-conditionsX
Changes
23
Change propagation
Two types of change propagation are supported: From the associated ontologies to the service description From the included composite services to the service description
The following procedure is realized: The definition of a process model is extended with the version of
each referenced ontology Changes in the referenced ontologies are logged in their logs
(which results in the new version of these ontologies) Push-based synchronisaton: On the explicit request all changes
between two synchronisatons are discovered Their impact on a service model is determined For each „link“ the corresponding Remove change is
recommended For new entities the LifeCycle aspects are taken into account The domain expert may accept recommendations or not
24
OMS
25
State-of-the-art
26
OntoGov achievements
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OntoGov SWS Activities
Ontology Management Publishing Discovery
28
Ontology Management
Within the OntoGov project, we have extended the standard approaches in two directions: Change Management – it is the timely adaptation of a
service description to the changes in business requirements, users’ needs, etc. as well as the consistent propagation of these changes to dependent artefacts The OntoGov approach enables agile response to frequent
and huge changes by ensuring the consistency preservation as well as the propagation of changes;
Lifecycle Management – even though knowledge is becoming recognised as one of the most important success factors of engaging policy makers, public administration managers, citizens and businesses in e-government, there is a lack of proven methods for the application of knowledge technologies The OntoGov lifecycle management bridges the gap
between decision making and realisation by providing means for describing these decisions and formally stating reasons that motivate the design decisions
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Publishing
Publishing OntoGov service is based on the OntoGov Profile Ontology
Our approach focuses on imprecise or redundant annotation
It contains guidelines for building well-formed service announcement that are easier to be understood and cheaper to be modified
The “quality” of the annotation can be assessed through the existence of redundancy, inaccurate or incomplete information
30
Discovery
A number of proposals for automating the discovery of services are available They do not consider the fact that a user’s query is just an
approximation of his information need OntoGov service discovery has been realized by combining
three different types of conditions: Query-by-example– it is used for specifying conditions on the
service definitions, supplying the constraints on various fields; Reasoning using class hierarchy – the user can specify the type
of services. Subsumption reasoning is used to locate services that are more specific than specified;
Conceptual Query Refinement – the user defines keywords specifying the relevant terms that the service description must contain. The refinement system takes as the input the results of keyword-based search; whereas results are service descriptions. The system calculates refinements and generates a set of possible extensions of the original query
31
Architecture The novelty of the OntoGov approach lies in the formal verification of the service description as well as in the using of formal methods for achieving consistency when a problem is discovered This has been realized through two components:
Verificator Verification of the OWL-S process model is extended in several
dimensions First, we model the not only control-flow and data flow consistency
constraints. We allow to the public administrators to specify arbitrary domain-dependent consistency constraints. In this way we are able to cover all perspectives of the business models, i.e. control flow, data flow, operational issues (e.g. interactions between systems) and resources (e.g. humans, machines etc.)
Second, we do not consider only the process model but also the profile of a service
Finally, we have realized the verification of the e-government service descriptions using rule-based inference process
Recommender We propose formal approach for suggesting fixes that directly point to
the source of the inconsistencies The recommender is based on the so-called change-dependency graph,
which is a common technique for the maintenance of the knowledge-based systems
32
Service Ontology The most similar approach to the OntoGov approach is the OWL-S, since other approaches do not include the ontologies for modeling processes The OntoGov model consists of two major parts –
the OntoGov Profile ontology and the OntoGov Process ontology, which are developed based on the OWL-S ontologies
However, both of them are extended / adapted in order to take into account unique characteristics of the e-government services as well as some aspects needed for the better management of changes
33
Conclusion
Ontology-based change management system enables: automatic identification of inconsistencies in the description of
the E-Government services (log) analysis of a problem (lifecycle ontology) generation of recommendations for resolving problems
Advantages: Faster and better service design by all stakeholders involved
in the service lifecycle (e.g. managers, software developers) Better control and propagation of changes (e.g. control of
changes in law and propagation of changes to the software that delivers the service online)
More and better information about each step of the service delivery process, for all stakeholders involved in the service lifecycle
34
Thanks!Any questions?
Back up slides
36
User-defined Consistency
The user-defined consistency constraints are user‘s requirements that need to be expressed “outside” of the ontology language itself
Two types of the user-defined consistency conditions are identified:
generic conditions that are applicable across domains and represent best design practice or modeling quality criteria
modeling quality conditions: redundancy, misplaced properties, missing properties, etc.
domain dependent conditions that take into account the semantics of a particular formalism of the domain
All entities in the model must be connected Inputs & outputs must be defined in the domain ontology If input of a service is output of another service, then it has to
be subsumed by this output
37
OMS – Service Modeller & Service Registry
http://wim.fzi.de:8080/ontogov/ontogov.jnlp
38
Change generation
39
Change propagation
Extracting Deltas Reading Evolution Log
Analysis of changes For a new amendment a corresponding law can be found For a law all services that realize it can be found
Making Recommendation Lifecycle Ontology describes design decisions and their
relationship to affected parts of the service as well as to the requirements that motivate the decisions
It is a description of the service design process, which clarifies which design decisions were taken for which reasons, proves to be valuable for further development and maintenance
Legal
Legal‘
Meta
OntoGov
Supplier