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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
Experts decide how to implement the law
Programmers write the code
End-users use a portal
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Change Management Framework
Sensor (add entry in a log)
Monitor a document version
X
Document X is changed
Analyse which activity to change
X
Activity Y has to be changed
Resource Z is not needed
X
X
Plan how to achieve the consistency
Ontology Evolution generates additional changes
and propagates
Execute the required changes
Effector (programmer modifies a code)
X
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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
OntoGovProfile Ontology
OntoGov Process Ontology
Life-Event Ontology
Lifecycle Ontology
Domain Ontology
Legal Ontology
Organisational Ontology
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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
Domain aspects
Legal aspects
Organisational aspects
Lifecycle 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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Role of ontologies (cont.)

• 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

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Change Management Framework
Law
M
M
Evolution
Log
A
A
Evolution Ontology
P
E
P
E
Ontology
Change
Evolution
Detection
Lifecycle Ontology
Usage Ontology
Usage
A
A
Log
M
M
E
-
Government
Portal
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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

• 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

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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

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Changes

• 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 doesnt 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-conditions

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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

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OMS
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State-of-the-art
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OntoGov achievements
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OntoGov SWS Activities

• Ontology Management
• Publishing
• Discovery

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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

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Discovery

• A number of proposals for automating the
  discovery of services are available
• They do not consider the fact that a users 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

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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

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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

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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

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Thanks! Any questions?
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Back up slides
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User-defined Consistency

• The user-defined consistency constraints are
  users 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

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OMS Service Modeller Service Registry
http//wim.fzi.de8080/ontogov/ontogov.jnlp
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Change generation
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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

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