An ontology-driven case study for the knowledge representation of management information systems

1

on o

f M

IS An Ontology-Driven Case Study forthe Knowledge Representation of

e R

epre

sen

tati

o the Knowledge Representation ofManagement Information Systems

the

Kn

owle

dge

José A. Asensio, Nicolás Padilla, Luis Iribarne

Cas

e St

ud

y fo

r

1Applied Computing Group, University of Almería, SPAIN{jacortes, npadilla, [email protected]

tolo

gy-D

rive

n C

WSKS, Mykonos, GREECE

An

On

t

21-23th September, 2011

Applied Computing GroupUniversity of Almería, SPAIN

4th World Summit on the Knowledge SocietyMykonos (GREECE), 21-23th September, 2011

2

Indexon

of

MIS

• Context

e R

epre

sen

tati

o

• ODA: Data Ontologies

the

Kn

owle

dge ODA: Data Ontologies

• ODA: Process Ontologies

Cas

e St

ud

y fo

r • ODA: Process Ontologies

• Planning

tolo

gy-D

rive

n C • Planning

C l i

An

On

t • Conclusions



3

Contexton

of

MIS

• WMIS facilitate information retrieval and

e R

epre

sen

tati

o

decision-making, allowing cooperative work.

the

Kn

owle

dge

work.

WMIS d i d d l t i

Cas

e St

ud

y fo

r • WMIS design and development require standard methods and techniques:

tolo

gy-D

rive

n C

– Model-Driven Architectures (MDA), and– Ontology-Driven Architectures (ODA).

An

On

t gy ( )



4

Contexton

of

MIS

SOLERES

e R

epre

sen

tati

o

Environmental Management Information System

▼

the

Kn

owle

dge ▼

SOLERES-KRS

Cas

e St

ud

y fo

r

Knowledge Representation Subsystem▼

tolo

gy-D

rive

n C ▼

Ontology-Driven Architectures

An

On

t



5

Contexton

of

MIS

SOLERES

e R

epre

sen

tati

o


▼

the

Kn

owle

dge ▼

SOLERES-KRS

Cas

e St

ud

y fo

r


tolo

gy-D

rive

n C ▼


An

On

t



6

Contexton

of

MIS

SOLERES

e R

epre

sen

tati

o


▼

the

Kn

owle

dge ▼

SOLERES-KRS

Cas

e St

ud

y fo

r


tolo

gy-D

rive

n C ▼


An

On

t



7

Contexton

of

MIS

• Ontologies have been used for:

e R

epre

sen

tati

o

g

– describing the information domain knowledge

the

Kn

owle

dge describing the information domain knowledge

in the system, and

Cas

e St

ud

y fo

r

– modeling the processes and communicationsbetween system components.

tolo

gy-D

rive

n C between system components.

An

On

t



8

Contexton

of

MIS

e R

epre

sen

tati

o

User InterfaceProcesses

User InterfaceProcesses HCI

the

Kn

owle

dge Processes Processes

Cas

e St

ud

y fo

r

Middleware

tolo

gy-D

rive

n C

An

On

t

KRSEPU EPU



9

Contexton

of

MIS

e R

epre

sen

tati

o



the

Kn

owle


Cas

e St

ud

y fo

r

Middleware

tolo

gy-D

rive

n C

EIM

An

On

t

KRSEPU EPU

EID



10

Contexton

of

MIS

e R

epre

sen

tati

o



the

Kn

owle


Cas

e St

ud

y fo

r

Middleware

tolo

gy-D

rive

n C

EIM

An

On

t

KRSEPU EPU

EID



11

Contexton

of

MIS

e R

epre

sen

tati

o



the

Kn

owle


Cas

e St

ud

y fo

r

Middleware

tolo

gy-D

rive

n C

EIM

An

On

t

KRSEPU EPU

EID



12

ODA: Data Ontologies. EIM Ontology (I)on

of

MIS

SOLERES_concept

111

cartography id

1

ecological classification id

e R

epre

sen

tati

o

-id-observations-...

Cartography-id-name-description-...

Ecological_classification

11..*1 ** *

*

1 cartography_ecological_classification_id

ecological_classification_cartography_id

*g p y_

1

*g _ _

the

Kn

owle

dge

1

classification_hierarchycal_id

*time_id

1grid_id

1

geography_id

1

start_date_id

1..*

classification_technician_id

1

end_date_id1

hierarchycal_hierarchycal_id

*technician_id

1..*

layer_id

Cas

e St

ud

y fo

r

-id-hierarchycal_level-...

Classification_hierarchycal-id-name-area-perimeter-utm_x-utm_y-town

Geography-id-name-...

Layer-id-first_name-last_name-e-mail-telephone-organization-...

Technician-id-day-month-year-hour-minute-second

Time-id-square_side_size-number_columns-number_rows-utm_x-utm_y-...

Grid

*1 *hierarchycal_layer_id

1*

*

*

tolo

gy-D

rive

n C -locality

-scale-...

-id-name

Resource-id-name

Variable

1 *

1..*variable_id

1layer_resource_id

An

On

t -uri-size-...

-sinonymous-measure-category-type-accuracy-min_value-max_value-...

1..

hierarchycal_variable...

1..*

new_variable_id

*



1variable_variable_id

13


of

MIS

SOLERES_concept

111

cartography id

1


e R

epre

sen

tati

o




11..*1 ** *

*



*g p y_

1

*g _ _

the

Kn

owle

dge

1


*time_id

1grid_id

1

geography_id

1

start_date_id

1..*


1

end_date_id1


*technician_id

1..*

layer_id

Cas

e St

ud

y fo

r







Grid


1*

*

*

tolo

gy-D

rive

n C -locality

-scale-...

-id-name

Resource-id-name

Variable

1 *

1..*variable_id

1layer_resource_id

An

On

t -uri-size-...


1..


1..*

new_variable_id

*




14


of

MIS

SOLERES_concept

111

cartography id

1


e R

epre

sen

tati

o




11..*1 ** *

*



*g p y_

1

*g _ _

the

Kn

owle

dge

1


*time_id

1grid_id

1

geography_id

1

start_date_id

1..*


1

end_date_id1


*technician_id

1..*

layer_id

Cas

e St

ud

y fo

r







Grid


1*

*

*

tolo

gy-D

rive

n C -locality

-scale-...

-id-name

Resource-id-name

Variable

1 *

1..*variable_id

1layer_resource_id

An

On

t -uri-size-...


1..


1..*

new_variable_id

*




15

ODA: Data Ontologies. EIM Ontology (II)on

of

MIS SOLERES_concept

1 1111

e R

epre

sen

tati

o

-id-name-size-...

Satellite_image-id-name-description-training_type-classificator_type-...

Image_classification*

satellite_image

*1..*

sat_image_image_classifimage_classif_sat_image

* *

*image_classification

1..**

the

Kn

owle

dge

-id-name-agency_name

Satellite

-idTechnician

-idTime

-idTraining_set

-idPerformance_indicator

-idClasses

-idClassified_image

1..*

*

image_classif_tech

tech_image_classif

1

*

start_date

1

1

classified_image*

1..*

training_set1

*

end_date1..*

1..*

classes*

technician1..*

sat_image_sat

1

1..*

perform_indicator

1..*

satellite

Cas

e St

ud

y fo

r -...

-idname

Instrument

-first_name-last_name-email-telephone-organization-...

-day-month-hour-minute-second

-... -separability-quality-confiability

-name-value-observations

-...

1..*

1..*

training_set_classesclasses_training_set

1 1

1..*

1

instrument

tolo

gy-D

rive

n C -name

-...

-id-name-uri-size-...

Resource

<<enumeration>>Classificator type

<<enumeration>>Training type1..*

1..*

instrument_band

1

resource

1

resolution

1..*

satellite_image_band

1..*

resource

1

*

resolution* band

1

resource

An

On

t

-id-spectral-radiometric-temporal-spatial-observations

Resolution-id-name-description-min_bandwidth-max_bandwidth-...

Band-Isodata-K_medias-Min_distance-Mahalanobis-Max_probability-Paralelepipedes-Feature_Space-Fuzzy

-Supervised-Unsupervised

1 1



16


of

MIS SOLERES_concept

1 1111

e R

epre

sen

tati

o

-id-name-size-...



satellite_image

*1..*


* *


1..**

the

Kn

owle

dge


Satellite

-idTechnician

-idTime

-idTraining_set


-idClasses

-idClassified_image

1..*

*

image_classif_tech

tech_image_classif

1

*

start_date

1

1

classified_image*

1..*

training_set1

*

end_date1..*

1..*

classes*

technician1..*

sat_image_sat

1

1..*

perform_indicator

1..*

satellite

Cas

e St

ud

y fo

r -...

-idname

Instrument





-...

1..*

1..*


1 1

1..*

1

instrument

tolo

gy-D

rive

n C -name

-...


Resource



1..*

instrument_band

1

resource

1

resolution

1..*


1..*

resource

1

*

resolution* band

1

resource

An

On

t





1 1



17


of

MIS SOLERES_concept

1 1111

e R

epre

sen

tati

o

-id-name-size-...



satellite_image

*1..*


* *


1..**

the

Kn

owle

dge


Satellite

-idTechnician

-idTime

-idTraining_set


-idClasses

-idClassified_image

1..*

*

image_classif_tech

tech_image_classif

1

*

start_date

1

1

classified_image*

1..*

training_set1

*

end_date1..*

1..*

classes*

technician1..*

sat_image_sat

1

1..*

perform_indicator

1..*

satellite

Cas

e St

ud

y fo

r -...

-idname

Instrument





-...

1..*

1..*


1 1

1..*

1

instrument

tolo

gy-D

rive

n C -name

-...


Resource



1..*

instrument_band

1

resource

1

resolution

1..*


1..*

resource

1

*

resolution* band

1

resource

An

On

t





1 1



18

ODA: Data Ontologies. EID Ontologyon

of

MIS

“... A Cartographical map stores its information in Layers identified by a set of Variables while a Satellite image stores

e R

epre

sen

tati

o identified by a set of Variables, while a Satellite image stores its information in Bands. Both the Cartographical and Satellite

classification have Geographical information associated and

the

Kn

owle

dge are carried out at a given Time by some Technicians...”

Cas

e St

ud

y fo

r to

logy

-Dri

ven

CA

n O

nt



19

ODA: Process Ontologies. Admin Ontologyon

of

MIS

e R

epre

sen

tati

oth

e K

now

led

geC

ase

Stu

dy

for

tolo

gy-D

rive

n C

An

On

t



20


of

MIS

Concepts

e R

epre

sen

tati

o Concepts

the

Kn

owle

dge

Cas

e St

ud

y fo

r to

logy

-Dri

ven

CA

n O

nt



21


of

MIS

Concepts

e R

epre

sen

tati

o

Actions

Concepts

the

Kn

owle

dge Actions

Cas

e St

ud

y fo

r to

logy

-Dri

ven

CA

n O

nt



22


of

MIS

Concepts

e R

epre

sen

tati

o Concepts

Actions

the

Kn

owle

dge Actions

Cas

e St

ud

y fo

r

Predicates

tolo

gy-D

rive

n C

An

On

t



23


of

MIS

e R

epre

sen

tati

oth

e K

now

led

geC

ase

Stu

dy

for

tolo

gy-D

rive

n C

An

On

t



24

ODA: Process Ontologies. Register Ontologyon

of

MIS

e R

epre

sen

tati

oth

e K

now

led

geC

ase

Stu

dy

for

tolo

gy-D

rive

n C

An

On

t



25


of

MIS

e R

epre

sen

tati

oth

e K

now

led

ge Actions

Cas

e St

ud

y fo

r to

logy

-Dri

ven

CA

n O

nt



26


of

MIS

Concepts

e R

epre

sen

tati

oth

e K

now

led

geC

ase

Stu

dy

for

tolo

gy-D

rive

n C

An

On

t



27


of

MIS

e R

epre

sen

tati

oth

e K

now

led

geC

ase

Stu

dy

for

Predicates

tolo

gy-D

rive

n C

An

On

t



28

ODA: Process Ontologies. Lookup Ontologyon

of

MIS

e R

epre

sen

tati

oth

e K

now

led

ge

Actions

Cas

e St

ud

y fo

r Actions

tolo

gy-D

rive

n C

An

On

t



29

ODA: Process Ontologies. Lookup Ontologyon

of

MIS

Concepts

e R

epre

sen

tati

oth

e K

now

led

geC

ase

Stu

dy

for

tolo

gy-D

rive

n C

An

On

t



30

Planningon

of

MIS

e R

epre

sen

tati

oth

e K

now

led

geC

ase

Stu

dy

for

tolo

gy-D

rive

n C

An

On

t



31

Planningon

of

MIS

e R

epre

sen

tati

oth

e K

now

led

geC

ase

Stu

dy

for

tolo

gy-D

rive

n C

An

On

t



32

Planningon

of

MIS

e R

epre

sen

tati

oth

e K

now

led

geC

ase

Stu

dy

for

tolo

gy-D

rive

n C

An

On

t



33

Planningon

of

MIS

e R

epre

sen

tati

oth

e K

now

led

geC

ase

Stu

dy

for

tolo

gy-D

rive

n C

An

On

t



34

Conclusionson

of

MIS

• Ontology-Driven Architecture has been

e R

epre

sen

tati

o

gyused in SOLERES-KRS for:

the

Kn

owle

dge

– representing the domain information (EIM and EID Ontologies) and

Cas

e St

ud

y fo

r and EID Ontologies), and

defining the behaviour and interaction

tolo

gy-D

rive

n C – defining the behaviour and interaction

protocols (Admin, Register and Lookup Ontologies).

An

On

t Ontologies).



35 An Ontology-Driven Case Study forth K l d R t ti f

on o

f M

IS

the Knowledge Representation ofManagement Information Systems

e R

epre

sen

tati

o

Thank you for your attention!!

the

Kn

owle

dge

Contact: [email protected]

Cas

e St

ud

y fo

r

Applied Computing GroupUniversity of Almería, SPAINhttp://www.ual.es/acg

tolo

gy-D

rive

n C p // / g

A Methodology for the Recovery and Exploitation of Environmental Information (TIN2010-15588)

An

On

t Environmental Information (TIN2010 15588)

Development of an Intelligent Web Agent for Environmental Information (TIC-6114)



An ontology-driven case study for the knowledge representation of management information systems

Documents

id id

id hierarchycal

hierarchycal id

ontologydriven case

classification id

applied computing group

spain mykonos greece

id layer