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RIONT-A MODERN RISK BASED ONTOLOGY


We have begun to develop an occupational risk based ontology- using as a main instrument for development Stanford University Protegee.
As soon as we are going to find a free host our ontology would be accessible for free on this support.
The specialists that are willing to cooperate in the development of this ontology- are gladly expected.


DEFINITIONS

We have considered some main start-up definitions as main pillars in the development of the ontology.
1. HAZARD- A hazard is any source of potential damage, harm or adverse health effects on something or someone under certain conditions at work.
Basically, a hazard can cause harm or adverse effects (to individuals as health effects or to organizations as property or equipment losses).
2.RISK – is the umbrella under which all occupational risks can exist.
3.INHERENT/INCIDENTAL RISKS – contain all risks that can either exist or be created by controllable actions (incidental), or exist due to uncontrollable circumstances (inherent)
4.EXTERNAL/OPERATIONAL RISKS – external risks can only represent external financial risks to an enterprise. External risks can be members of all other risks and must be a part of any discoverable risk set. Operational risks can only represent internal financial risks to an enterprise. Operational risks can be members of all other risks and must be a part of any discoverable risk set.
5.RISK FACTORS- Factors that  describe specific risks. Other definitions are following. We will try to use EOSH and NIOSH definitions.


STEPS IN DEVELOPING THE ONTOLOGY

We have started with three main classes:
1. Risk;
2. Risk factors;
3. Personal factors that are affecting risk;
We have added subclasses to these main classes.
We have defined instances where we were thinking that such instances are appropriate.


THE DEVELOPMENT PROCESS

The development process is actually underway. 
Some images from the development process are presented below.

Figure 1. The class browser of Protegee

Figure 2. Sub-class definition 


Figure 3. Vertical arborescent image

Figure 4. Spring image 

Figure 5. Horizontal arborescent image


CONCLUSIONS

At this moment we were not able to find something very useful by developing such an ontology- as it has very little space to document the terms, it is not accepting links and has a somehow rigid format. In this respect we are going to link the ontology with knowledge maps in order to obtain a better learning instrument. 
Some images from the running of the ontology are presented below.
Figure 6. Main screen


Figure 7. Risk factors


On a larger scale it is interesting that such an ontology could be exported as CLIPS code or as a Java code, being able to be embedded in such programs. 



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