By: M.Gillespie , H.Holmani, D. Kotowski, and D.A.Stacey

hesitantdoubtfulAI and Robotics

Oct 29, 2013 (3 years and 5 months ago)

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By:
M.Gillespie

,
H.Holmani
, D. Kotowski, and
D.A.Stacey

Presented By: Daniel
Kotowski

dkotowsk
@
uoguelph.ca

Who are we?


Guelph Ontology Team (GOT)


Website:
http://jaws.socs.uoguelph.ca



Soon to be:
http://ontology.socs.uoguelph.ca



We have been recently established


Our
Research Focus:


Semantic Web & Compositional Systems


Semantic Web & Workflow Planning


Semantic Web & Ontology Discovery and Reuse

2

Goal of this Presentation



This paper is a position paper and preliminary work


We would like to start a dialog on the framework
presented


To introduce aspects of an ODCS that needs to be
considered when designing
ontolgoies


Explore possible usage of the framework


We
have done case study using this framework which will be
presented at
KEOD 2011 in Paris

3

Outline


Introduction


Ontology Driven Compositional Systems (ODCS)


Current Implementations


Knowledge Identification Framework for ODCS


Categories of Knowledge Entities


Applications of
Framework


Summary

4

The Semantic Web &

Compositional Systems



System Composition

is the process of composing two or more
previously

implemented software and/or services to create a
more functional system.


Note: We do not consider code “generation”


Compositional Systems
are expert systems that automatically
or semi
-
automatically perform
system composition

5

The Semantic Web &

Compositional Systems



Compositional Systems required a
knowledge base

to reason
which software/services are required to create the desired
resultant system






Enter
Ontologies
!

6

Ontology Driven Compositional
System (ODCS)



An
Ontology Driven Compositional System

is reasons with
ontological representations to construct a
resultant system

composed of
compositional units


7

Source
Giliepse

et. al. (2011)

ODCS Examples:

Semantic Web Services



Automatic Composition
of Web Services


Ex.
Arpinar

et al. (2005)


WebService.owl


Process.owl


Domain.owl

8


Source:
Arpinar

et al. (2005)

ODCS Examples:

BioSTORM Agent Composition



Automatic composition
of
syndromic

surveillance
software agents


DataSource.owl


SurveillanceMethods.owl


SurveillanceEvaluation.owl

9


Source:
Nyulas

et.al
. (2008)

ODCS Examples:

Algorithm Composition



Semi
-
automatic
composition of
Algorithms


Hlomani

& Stacey (2009)


Algorithm.owl

-

Timeline.owl


Gillespie et al. (2011)


StatisticalModelling.owl


PopulationModelling.owl

10

Kotowski
et.al

(2011)

Let’s Not Reinvent the Wheel


Each system defines there own way to share knowledge


Often this method is unique to each system


However all these systems are trying to accomplish the
same thing (even though they may be named different
things)


Define Data architecture


Compositional Units


Workflow

11

Wouldn’t it be Nice


Method for understanding what knowledge we needed
to
capture


To have a basis for evaluating our knowledge bases


There are elements systems do not capture but will be
important as they evolve

12

Knowledge Identification

Framework


Purpose
:


Generalize knowledge
entities within any type of
ODCS


Propose collaborative
vocabulary


Assist with Merging and
Mapping between ODCS's
ontologies


Enhance adaptability of
future ontologies for
ODCSs

13

Knowledge Identification

Framework


Five Categories of


Knowledge
:


Compositional Units


Work
-
flow


Data Architecture


Human Actors


Physical Resources

14

Knowledge Identification

Framework


Internal vs.



External
:


Compositional Units


Work
-
flow


Data Architecture


Human Actors


Physical Resources

15

Knowledge Identification

Framework


Internal vs.



External
:


Compositional Units


Work
-
flow


Data Architecture


Human Actors


Physical Resources

16

Knowledge Identification

Framework


Syntactic vs Semantic


Knowledge Entities
:



Syntactic entities
represent
actual

objects


Semantic entities
represent the
realization

of those
actual objects

17

Knowledge Identification

Framework


Syntactic vs Semantic


Knowledge Entities
:


Like “Information
Realization” ontology
design pattern
(Gangemi &
Prescutti, 2009)


18

Knowledge Identification

Framework


Semantic Knowledge


Entity Sub
-
Types
:


Function


Data


Execution


Quality


Trust

19

Examples of

Knowledge Entities


Compositional Unit Examples

Syntactic:


Algorithm, Web Service, System Library Function,
Input/Output Specification

Semantic:


subType::
Function

(i.e. Domain
-
specific actions)


Data aggregation/conversion/plotting/analysis,
Statistical model, Aberrancy detection, etc.



subType::
Execution

subType::
Quality


Operating system






Average Runtime

20

Examples of

Knowledge Entities


Data Architecture Examples

Syntactic:


Single Datum, Structured Data, Data Source, Data Set

Semantic:


subType:
Data


Data Context, Data Context Component


DataSource Structure, DataSource FileFormat


Data Structure
(i.e., Matrix, Vector, Variable)


Data Type


Units of Measure

21

Examples of

Knowledge Entities


Human Actor Examples

Syntactic:


Person, Organization, Recommendation

Semantic:

subType:
Trust


Role
(i.e., software developer, domain
-
expert, novice
-
user)


Recommendation Context


Organization Type


Organization Governance

22

Knowledge Identification

Framework



Relationships between

Knowledge Categories



Syntactic Relationships


Semantic Relationships

23

Relationships between
Knowledge Categories


Syntactic Relationship Example

Algorithm

Input

Specification

has_input

Compositional Unit

Data Architecture

Compositional Unit

Data Architecture

Human Actor

----

Input

Specification

Data

Source

Data

Source

Datum

requires

sameAs

contains

contains

Person

owns

can_use

----

24

Relationships between
Knowledge Categories


Semantic Relationship Example
(Function & Trust)

Algorithm

Input

Specification

has_feature

Compositional Unit

Human Actor

SpaceTime

Dimension

Person

Person

works_in

trusts_


using

----

Organizational

Role

trusts

recommends

25

Applications of

Framework


Ontology Evaluation using Software Quality Assurance Checklist


With “SQA
-
like” Checklist,
evaluated the adaptability

of the
BioSTORM

ontologies

26

Applications of

Framework


Ontology Capture & Integration


SystemComposition.owl

DataArchitecture.owl

HumanActors.owl

PhysicalResources.owl

CompositionalUnits.owl

Workflow.owl

FOAF.owl

Time.owl


(W3C)

DataSource.owl


(BioSTORM)

Process.owl


(ISO)

Algorithm.owl


(Hlomani)

imported_by


Adapting current knowledge representations to improve
ontologies for Algorithm construction:



Hlomani

& Stacey (2009) Gillespie et al (2011)

27

Summary


Knowledge Identification Framework assists:


With the capture of knowledge about components of an
ODCS


Detailing relationships between the categories of
knowledge


Both syntactic and semantic


Merging and mapping between ODCS’ ontologies


Enhance adaptability of future ontologies for ODCS’




28

Thank You!!

29

References


Arpinar
, I. B., Zhang, R., Aleman
-
Meza, B., &
Maduko
, A. (2005). Ontology
-
driven Web services
composition platform. I nformation Systems and e
-
Business Management, 3(2), 175
-
199.
doi:10.1007/s10257
-
005
-
0055
-
9


Gillespie, M. G., Stacey, D. A., & Crawford, S. S. (2011). Designing Ontology
-
Driven System Composition
Knowledge and Processes to Satisfy User Expectations (in publication). Communications in Computer and
I nformation Science (CCI S). Springer
-
Verlag
.


Hlomani
, H., & Stacey, D. A. (2009). An ontology driven approach to software systems composition.
I nternational Conference of Knowledge Engineering and Ontology Development (pp. 254
-
260). I NSTICC.


Nyulas
, C. I., O’Connor, M. J.,
Tu
, S. W.,
Buckeridge
, D. L.,
Okhmat ovskaia
, A., &
Musen
, M. a. ( 2008). An
Ont ology
-
Driven Framework for Deploying JADE Agent Syst ems. 2008 I EEE/WI C/ACM I nternational
Conference on Web I nt elligence and I nt elligent Agent Technology, 573
-
577.
I eee
.
doi:10.1109/WIIAT.2008.25


Kotowski, D,
Heriques
, G.,
Gillespie,M
.,
Hlomani,H
., &
Stacey,D

(2011). Leveraging User Knowledge: Design
Principles for an Intuitive User Interface for Building Workflows. KEOD 2011.


Holmani
, H., Gillespie, M., Kotowski, D.,
Stacey,D
.(2011). Utilizing a Compositional System Knowledge
Framework for Ontology Evaluation: A Case Study on
BioSTORM


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