Model Eco-systems Decision Systems Lab University of Wollongong.

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Model Eco-systems Model Eco-systems Decision Systems Lab University of Wollongong
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Transcript of Model Eco-systems Decision Systems Lab University of Wollongong.

Page 1: Model Eco-systems Decision Systems Lab University of Wollongong.

Model Eco-systems Model Eco-systems

Decision Systems Lab

University of Wollongong

Page 2: Model Eco-systems Decision Systems Lab University of Wollongong.

DecisionSystemsLab

U of Wollongong Related referencesRelated references

Ghose, Koliadis and Cheung. Rapid Ghose, Koliadis and Cheung. Rapid process discovery. ER-2007process discovery. ER-2007

Ghose and Koliadis. Auditing Ghose and Koliadis. Auditing business process compliance. business process compliance. ICSOC-2007ICSOC-2007

Koliadis and Ghose. Conistency in Koliadis and Ghose. Conistency in process inter-operation. SCC-2007process inter-operation. SCC-2007

Page 3: Model Eco-systems Decision Systems Lab University of Wollongong.

DecisionSystemsLab

U of Wollongong

OutlineOutline The challenges of model The challenges of model

managementmanagement The eco-systems metaphorThe eco-systems metaphor The model life-cycleThe model life-cycle The key technical challengesThe key technical challenges Consistency equilibriaConsistency equilibria Completeness equilibriaCompleteness equilibria

Page 4: Model Eco-systems Decision Systems Lab University of Wollongong.

DecisionSystemsLab

U of Wollongong

The challenges of model The challenges of model managementmanagement

Large numbers of modelsLarge numbers of models Large numbers of stakeholdersLarge numbers of stakeholders Diversity of modeling notationsDiversity of modeling notations Models specified at varying levels of Models specified at varying levels of

abstractionabstraction Distributed asynchronous model updatesDistributed asynchronous model updates Changes in a given model impact several Changes in a given model impact several

othersothers Collections of models are often inconsistentCollections of models are often inconsistent Collections of models are often incompleteCollections of models are often incomplete

Page 5: Model Eco-systems Decision Systems Lab University of Wollongong.

DecisionSystemsLab

U of Wollongong Why eco-systems (1/3)Why eco-systems (1/3)

The (biological) eco-systems metaphor The (biological) eco-systems metaphor provides useful conceptual (and formal) provides useful conceptual (and formal) tools to understand and instrument tools to understand and instrument model management systemsmodel management systems

A biologically-inspired account of the A biologically-inspired account of the model life-cycle:model life-cycle:– Models are created (or discovered)Models are created (or discovered)– Models co-exist/co-evolve/inter-operate with Models co-exist/co-evolve/inter-operate with

other models during their lifetimesother models during their lifetimes– Existing models lead to the creation of new Existing models lead to the creation of new

modelsmodels– Models are discarded/superannuated. Models are discarded/superannuated.

Page 6: Model Eco-systems Decision Systems Lab University of Wollongong.

DecisionSystemsLab

U of Wollongong Why eco-systems (2/3)Why eco-systems (2/3)

Like biological eco-systems, models in a Like biological eco-systems, models in a model eco-system undergo constant changemodel eco-system undergo constant change– Requirements models change frequently because Requirements models change frequently because

of of » changing stakeholder perceptions,changing stakeholder perceptions,» evolving needs and evolving needs and » changing usage contexts. changing usage contexts.

– Design models, process models, goal models, Design models, process models, goal models, rule models and others also change for these (or rule models and others also change for these (or similar) reasons similar) reasons

Like biological eco-systems, perturbations in a Like biological eco-systems, perturbations in a model eco-system propagate across models, driven model eco-system propagate across models, driven by the need to maintain a variety of by the need to maintain a variety of inter-modelinter-model constraints. constraints.

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DecisionSystemsLab

U of Wollongong Why eco-systems (3/3)Why eco-systems (3/3)

Like biological eco-systems, model eco-Like biological eco-systems, model eco-systems are characterized by systems are characterized by competing forces, such as:competing forces, such as:– a pair of inconsistent models driving a a pair of inconsistent models driving a

specification in competing directions, or specification in competing directions, or – the competing pulls of alternative ways to the competing pulls of alternative ways to

completing a specificationcompleting a specification Like biological eco-systems, model eco-Like biological eco-systems, model eco-

systems settle into systems settle into equilibriaequilibria after being after being perturbedperturbed

Page 8: Model Eco-systems Decision Systems Lab University of Wollongong.

DecisionSystemsLab

U of WollongongMore on equilibriaMore on equilibria

An equilibrium is a “steady state”, An equilibrium is a “steady state”, where the competing forces within a where the competing forces within a system balance each other outsystem balance each other out

Changes to the system perturb these Changes to the system perturb these equilibria, but the system eventually equilibria, but the system eventually settles into a new equilibrium that settles into a new equilibrium that accommodates these changesaccommodates these changes

Common concept in:Common concept in:– Physics (physical equilibria)Physics (physical equilibria)– ChemistryChemistry– Economics (market equilibria)Economics (market equilibria)– Decision theory (Pareto-equilibria etc..)Decision theory (Pareto-equilibria etc..)

Page 9: Model Eco-systems Decision Systems Lab University of Wollongong.

DecisionSystemsLab

U of Wollongong Inter-model constraintsInter-model constraints

What is a minimal way of What is a minimal way of characterizing the constraints a characterizing the constraints a given model imposes on others that given model imposes on others that co-exist with it?co-exist with it?– ConsistencyConsistency– CompletenessCompleteness

Formally, these are complementary Formally, these are complementary notionsnotions– Inconsistency resolved via Inconsistency resolved via removalremoval– Incompleteness resolved via Incompleteness resolved via additionaddition

Page 10: Model Eco-systems Decision Systems Lab University of Wollongong.

DecisionSystemsLab

U of Wollongong The hard questionsThe hard questions How do we tell whether a set of models is How do we tell whether a set of models is

consistentconsistent?? How do we tell whether a set of models is How do we tell whether a set of models is

completecomplete?? How do we detect similarity between a pair of How do we detect similarity between a pair of

models?models? How do we establish How do we establish model co-referencemodel co-reference

(distinct models that describe the same real-(distinct models that describe the same real-world artefact)?world artefact)?

How do we detect How do we detect model inclusionmodel inclusion?? How do we determine How do we determine model entailmentmodel entailment?? What does it mean to minimally change a What does it mean to minimally change a

model or set of models?model or set of models?

Page 11: Model Eco-systems Decision Systems Lab University of Wollongong.

DecisionSystemsLab

U of Wollongong

Dealing with abstraction Dealing with abstraction heterogeneityheterogeneity

Models in an eco-system might be Models in an eco-system might be specified at varying levels of abstractionspecified at varying levels of abstraction

Comparisons Comparisons (consistency/completeness) possible (consistency/completeness) possible only with models specified at the same only with models specified at the same level of abstractionlevel of abstraction

Current solution: Use enterprise Current solution: Use enterprise ontologies to map more abstract models ontologies to map more abstract models to more refined modelsto more refined models

Page 12: Model Eco-systems Decision Systems Lab University of Wollongong.

DecisionSystemsLab

U of Wollongong Model consistencyModel consistency

Informally, a set of models is Informally, a set of models is consistent if it can be consistent if it can be realizedrealized

Semantic: The existence of a Semantic: The existence of a specificandspecificand in the semantic domain in the semantic domain

Syntactic: The satisfaction of a set Syntactic: The satisfaction of a set of of consistency rulesconsistency rules

Also, hybrid notionsAlso, hybrid notions

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DecisionSystemsLab

U of Wollongong Checking consistencyChecking consistency

Alternative (classes of) techniques:Alternative (classes of) techniques: Mapping models to a (common) Mapping models to a (common)

semantic domainsemantic domain Semantic markup of modelsSemantic markup of models Metamodel-based approachesMetamodel-based approaches Rule-based approachesRule-based approaches HybridsHybrids

Page 14: Model Eco-systems Decision Systems Lab University of Wollongong.

DecisionSystemsLab

U of Wollongong

Consistency in model eco-Consistency in model eco-systemssystems

Two types:Two types:– Intra-notation consistencyIntra-notation consistency– Inter-notation consistencyInter-notation consistency

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DecisionSystemsLab

U of Wollongong

Example: Intra-notation Example: Intra-notation inconsistency (1/4)inconsistency (1/4)

Page 16: Model Eco-systems Decision Systems Lab University of Wollongong.

DecisionSystemsLab

U of Wollongong

Example: Intra-notation Example: Intra-notation inconsistency (2/4)inconsistency (2/4)

Page 17: Model Eco-systems Decision Systems Lab University of Wollongong.

DecisionSystemsLab

U of Wollongong

Example: Intra-notation Example: Intra-notation inconsistency (3/4)inconsistency (3/4)

Define semantic correspondences Define semantic correspondences between conceptsbetween concepts

Page 18: Model Eco-systems Decision Systems Lab University of Wollongong.

DecisionSystemsLab

U of Wollongong

Example: Intra-notation Example: Intra-notation inconsistency (4/4)inconsistency (4/4)

How do we determine whether How do we determine whether these models are inconsistent?these models are inconsistent?– Use a graph encoding of BPMN modelsUse a graph encoding of BPMN models

» activities, events and gateways become nodesactivities, events and gateways become nodes» message and control flow links become edgesmessage and control flow links become edges

– Use consistency rules specific to this Use consistency rules specific to this encodingencoding» Isomorphism of sub-graphs (in graph Isomorphism of sub-graphs (in graph

encoding of proto-models) determined by encoding of proto-models) determined by node intersections.node intersections.

» No dangling pointersNo dangling pointers

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DecisionSystemsLab

U of Wollongong Model inclusionModel inclusion

Notions of equilibria (that we will Notions of equilibria (that we will discuss next) require reference to an discuss next) require reference to an evaluation of evaluation of model inclusionmodel inclusion

Informally, m1 is Informally, m1 is includedincluded in m2 if m1 in m2 if m1 can be consistently extended to obtain can be consistently extended to obtain m2m2

Structural encodings permit sub-graph Structural encodings permit sub-graph inclusion as a basis for model inclusioninclusion as a basis for model inclusion

Closely related to the notion of Closely related to the notion of model model entailmententailment

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DecisionSystemsLab

U of Wollongong Consistency equilibriumConsistency equilibrium

Resolution of consistency-perturbation of an Resolution of consistency-perturbation of an equilibrium involves identifying maximal equilibrium involves identifying maximal “subsets” (referring to a notion of model “subsets” (referring to a notion of model inclusion) of the eco-system that is inclusion) of the eco-system that is consistentconsistent

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DecisionSystemsLab

U of Wollongong

Minimal sources of Minimal sources of inconsistencyinconsistency

Forms basis for computing restored consistency equilibria by focusing analyst attention on specific portions of models in the eco-system that, if edited, would restore consistency

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DecisionSystemsLab

U of Wollongong Assessing completenessAssessing completeness

Informally: Completeness is an attribute of a Informally: Completeness is an attribute of a model that model that “says all the things it needs to say”“says all the things it needs to say”

Formally: A formal theory is complete with Formally: A formal theory is complete with respect to a background language if the theory respect to a background language if the theory entails either p or entails either p or p for every proposition p in p for every proposition p in the background languagethe background language

Completeness of a model in an eco-system can Completeness of a model in an eco-system can be assessed either via:be assessed either via:– Reference to a background ontologyReference to a background ontology– Reference to other models in the eco-systemReference to other models in the eco-system

Types of assessment:Types of assessment:– Intra-notationIntra-notation– Inter-notationInter-notation

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DecisionSystemsLab

U of WollongongIntra-notation completenessIntra-notation completeness

Intra-BPMN completeness rulesIntra-BPMN completeness rules

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DecisionSystemsLab

U of Wollongong Inter-notation completenessInter-notation completeness

Identify correspondences between meta-Identify correspondences between meta-model elements of the 2 notations. If model elements of the 2 notations. If element e1 in (the meta-model of) element e1 in (the meta-model of) notation n1 is related to element e2 in notation n1 is related to element e2 in notation n2, then every instance of e1 in notation n2, then every instance of e1 in an n1 model requires that there is a an n1 model requires that there is a corresponding instance of e2 in a (co-corresponding instance of e2 in a (co-existing) n2 modelexisting) n2 model

Example: If a UML sequence diagram Example: If a UML sequence diagram refers to a “customer” object, then a refers to a “customer” object, then a “customer” object must exist in the “customer” object must exist in the corresponding class diagramcorresponding class diagram

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DecisionSystemsLab

U of WollongongCompleteness EquilibriumCompleteness Equilibrium