Closing the Semantic Gaps in Topic Maps and OWL ontologies with Modelling Workflow Patterns

Institut für Informatik

Closing the Semantic Gaps in Topic Maps and OWL ontologies with Modelling Workflow Patterns

Lutz Maicher, Martin Böttcher

University of [email protected]

[email protected]

2Lutz Maicher, Martin Böttcher



Agenda

Idea- Examples- Definition „Semantic Gap“- Basic Solution

Realisation- Basic Realisation- Data- and Processing Model- Workflow example

Implementation- OWL Example

Outlook




Created in background: Model which represents in Dublin Core Terms, that Lutz Maicher is the creator of the content of www.tmra.de




Idea




OWL Example

Creation

Use Cases

User Roles

Use(Instantiation)

Comprehensive Ontologies

Need of a use case or role specific view

Only application dependent support

Creation of an Ontology for employees.

Roles: Secretary, Manager, HR

Use Cases: „new employee“, „getting information“, „changing salary“

Use of an Ontology for employees.

Roles: Secretary

Use Cases: „new employee“

Problems: What needs to be added?

Where to get the information?

How can this Information be

preserved?

How can these Problems be

solved?




(Autonomous) Topic Maps Example

dc:creator Lutz Maicher

dc:subject Topic Maps

www.tmra.de

dc:contributor L.M. Garshol


www.isotopicmaps.org



www.uni-leipzig.de/~maicher



www.tmra.de

dc:contributor L.M. Garshol

www.isotopicmaps.org

www.uni-leipzig.de/~maicher

Modelling method has to

be broadcasted.




Semantic Gap

The usage of one ontology allows the creation of various independent model types, due to the interpretation spaces left by providing only the vocabulary.




Workflows for Representing Modelling Methods

Closing the semantic gap means to define the intensions of each model type by the description of the modelling method to apply.

A modelling method is a workflow which describes how observation of subjects should be documented with the given ontology.




Realisation

10




Basic Realisation

Design rationales of Modelling Workflow Patterns:

Workflow based Grounding on Petri nets

Self containedness Generic representation

Proprietary workflow

representation

Petri net Data Model

Petri net Processing

Model

Generic Interpreter

Mapping

Topic Maps SyntaxOWL Syntax

11




Data- and Processing Model

Petri net Data Model

The Petri net data model (PNDM) is derived from

the formal specification of Petri nets.

Petri net Processing

Model

The constraints how the Interpreter has to process these Petri Nets are defined

by the Petri net Processing Model (PNPM).

The PNDM and PNPM allow to properly represent any kind of Petri Nets with these syntaxes, including MWPs.

Specification of PNDM and MWP PNPM available at: http://www.informatik.uni-leipzig.de/~maicher/mwp/mwp.htm

12




Example of a workflow

Roles: Secretary

Use Cases: „ add a new employee“

Operator: hum.quest.

Operand: „Ask for the name!“

Operator: ont.request

Operand:„Employee exists?“

Operator:hum.inf.

Operand:„Employee exists!“

Operator:ont.update

Operand: „Insert employee“

Operator: hum.bin.req.

Operand: „Is there a new employee?“

yes

yes

no

no

Operator: hum.bin.req.

Operand: „Add the employee?“

yes

no

13




Representation of the example workflow as Petri net

[id] id1[operator] s:human_string[operand] What is the

employee‘s name?

[id] id3[operator] s:human_binaryDecision[operand] Shall the employee

be added?

[id] id4[operator] s:human_information[operand] Employee already exist.

using s for http://psi.semports.org/MWP#

[id] id2[operator] s:SPARQL_binary[operand] SELECT ?person

WHERE {?person rdfs:type db:Person. ?person db:name %result.id1%}

[id] t3r42[characteristic] {([key] result.id1

[value] Smith)}

[id] t3r42[characteristic] {[key] result.id1

[value] Smith),([key]

result.id2[value]

s:TRUE)}]

co

nd

itio

ns

:n

ull

co

nd

itio

ns

:%

id2

.va

lue

%

= s

:TR

UE

co

nd

itio

ns

:%

id2

.va

lue

%

= s

:FA

LS

E

co

nd

itio

ns

:n

ull

14




Implementation

15




Implementation (MWP Factory)

modelling workflow pattern 1


PA

RS

ER

1P

AR

SE

R 2

Petri net data

model

INT

ER

PR

ET

ER

PLU

G-I

N

1P

LUG

-IN

2

PLU

G-I

N

n

console web endGUI

instance of model type 2(e.g. OWL)

instance of model type 3

(XTM Topic Maps)

ontology 2(e.g. XTM

Topic Maps)

ontology 1(e.g. OWL)


instance of model type 1(e.g. OWL)

Editor

(Protégé Plug-In)

16




OWL Example – Complexity of Ontologies

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OWL Example – Protégé plug-in for MWP

18




OWL Example – MWP Factory

19




Outlook

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Outlook

• Validation– validation of workflow definitions

– ex-ante validation of the models to be created (based on the workflow definition)

• Workflow Patterns– representing common tasks in plugable workflow patterns

• Interpreter for different usage contexts – small footprint, web-based, mobile environments

Closing the Semantic Gaps in Topic Maps and OWL ontologies with Modelling Workflow Patterns

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