How to integrate the results of the Country Reports in the Semantic Wiki

Atrium – Forest Consulting Zvolen 2012

How to integrate the results of the Country Reports in the Semantic Wiki

Silvana R. NobreAtrium Forest Consulting, Brasil

[email protected]

Luiz Carlos E. RodriguezUniversity of São Paulo, Brasil

[email protected]


How to integrate the results of the Country Reports in the Semantic Wiki

1. Actual situation & objectives

2. Knowledge representation basic concepts

3. Models & Examples

4. Attribute Values

5. What is ahead?


What we have done until now

1. Actual situation & Objectives

a. We have collected data about the use of DSS on Forest Planning in each Country.

b. We have interpreted data and their relations

c. Those data make sense in compiled reports

d. We have similar reports for each Country

e. We have read and analyzed CR under some perspective26 reports!!

Understanding

Cont

ext

Data

Information

Knowledge

Wisdom

relations

patterns

Principles, explanations

We are here!!



Understanding

Cont

ext

Data

Information

Knowledge

Wisdom

relations

patterns

Principles, explanations

We want to get there!!!

What do we want?a. Guidelines to development

b. Guidelines to use of DSS

c. Lessons learned…

d. …


1. Understand patterns on Country Reports• We have already done a great effort to it!!• How far have we got on standardization?

2. Do knowledge model

3. Agree on a single “place” to store our knowledge base

4. Bring to the knowledge base what is already done.

5. Create a Knowledge base

6. Semantic wiki will make the knowledge base available

7. Look for explanations, principles, guidelines…

Knowledge

Technology

People

Value!!!




1. Objects & Class of Objects that participated the experiences we want to

transform in knowledge.

2. We must choose which objects from the real world we are going to represent

3. We must describe those objects

4. Describe an object means “say what are the attributes of each object”

5. Each attribute has his own set of possible values

Knowledge from experience

1. What are our relevant objects?

2. What are their common attributes?

3. What are the attributes possible value?

Answers are inside the CR



There will be an agent (a robot, or a semantic wiki ) ready and prepared to

read information and present as knowledge to humans.

The agent deals with (object, attribute, value) vectors.

Knowledge from experience

Structured &

InterpretedInformation

Semantic Wiki


3. Model & Examples

Objects of the real world

Level of object description can be:

• CR + Problem Type• DSS + Problem Type• CS + Problem Type

Important task: common classification for Problem Type

• Temporal scale: strategic; • Spatial context: spatial with no

neighborhood interrelation; • Spatial Scale: stand level;• Single Decision making• Single objective;• Function: wood productsProblem Type #1


Describing Objects

heritage:

• A DSS+PT can inherit an attribute from a CR+PT• CS + PT can inherit an attribute from a CR+PT

Examples on “Object, Attribute, Value” representation.

• (Austria Problem Type 1; Model; “Forest Species Conversion”)

• (Austria Problem Type 1; KM Technique; “Relational Database”)

• (Austria Problem Type 1; Volume estimation; “process -based”)

• (Austria Problem Type 1; Modeling Techniques; “Multi-criteria Analysis”)

Example on heritage:

• ClimChalp DSS inherits the attribute “Forest Species conversion” from Austria Problem Type 1

3. Model & Examples


General Model

3. Model & Examples


Model Application: Graph Examples

3. Model & Examples


4. Attribute Values

1. It is a potential problem

2. Some of them we already know the set of possible values

3. We must avoid replication: same meaning, different words

4. Suggestion: concentrate the job in a team (STSM)

5. Attach two attribute values of a same attribute class to an single object

6. Classical examples:

Modeling Techniques

• Linear programming• Goal Programing• Heuristics• Multi-criteria analysis• Dynamic Programing• …..

Models

• Harvest Scheduling• Species Conversion• Transportation• Daily truck dispatch• Road design optimization• Genetic Material Allocation• ….


6. What is ahead?

1. Understand patterns on Country Reports• We have already done a great effort to it!!• How far have we got on standardization?

2. Validate a knowledge model

3. Agree on a single “place” to store our knowledge base

4. Bring to the knowledge base what is already done.

5. Create a unique Knowledge base

6. Semantic wiki will make the knowledge base available

7. Look for explanations, principles, lessons learned, guidelines…


Thanks! Silvana Nobre

Atrium Forest Consulting, Brasil

[email protected]