Introducing EMont with help of a case

EM_ont describes and assesses knowing-how knowledge (expertise, behavior and (non-)human activities) and worldviews. The ontology consists of eight modeling elements, which will be introduced shortly with help of the fictitious and simplified situation of people counteracting a flooding disaster.

Capturing activities with the PQR formula

In EMM human behavior is defined as 'human activity systems’. Human activity systems, as well as activities of other kinds of actors (e.g. machinery), can be modeled with help of the PQR formula. This formula originates from the Soft Systems Methodology, and has to be applied as a root definition: a statement written in a few sentences capturing the intention of someone’s worldview. It concisely captures (human) activities executed to deal with particular circumstances which are motivated by the actors' worldview. The PQR formula is pivotal to EM_ont. The letters P, Q and R do not resemble anything, except for being subsequent letters in the alphabet. A specific meaning, however, is attached to these letters:

PQR	Meaning
P	What?	Activity	What activity are we going to do, perform, execute or what process is going to happen?
Q	How?	Sub-activity	In what way are we going to do it?
R	Why?	Goal	What goal do we want to achieve?

The PQR formula reads like a sentence:

Do P by a Q in order to achieve R.

Applying the PQR formula touches upon the expertise or knowing-how knowledge of an expert, who, based on his experience, intuitively knows what to do in specific situations. In other words, an expert applies the right activity patterns almost without consciously thinking. The PQR formula in the case of counteracting a disaster (see figure 1) looks like:

You can counteract the disaster (P - what) by, depending on the circumstances, fighting it (Q1 - how) or evacuating (Q2 - how) in order to save your and your relatives' lives (R - why).

Figure 1. Counteracting a disaster.

The PQR formula can be applied recursively. A How (Q) can be decomposed in more specific or diverse How's (Q's). To continue from the example in figure 1: the evacuation activity can be subdivided into evacuation by car (Q2,1) or by public transport (Q2,2). Hence, the evacuation activity (Q2) gets the status of an activity (P) for its constituents.

Generalizing from the example in figure 1: by applying the PQR formula recursively, we can model an experts’ knowledge, that is, his behavioral patterns, at any desired level of detail. The main activity (P) and main goal (R) address what should be done in a situation, they however do not yet specify how (Q) it can be done. Therefor, activities usually consist of more specific sub-activities (Q's), which altogether contribute to the main activity (P). Just like activities, goals can be decomposed into sub-goals as well.

Activities in specific situations

A situation is a network of actors, whether human or not, brought together to accomplishing shared or non-shared goals. These situations can also be called 'nested cognitive patterns of human activity systems'. In the situation “Community resilience” (figure 2) a community tries to cope with disturbances (main activity - what) by minimizing the effect of disturbances (main goal - why), including the more specific and nested situation "Flooding". Technically, the situation is modeled as a context, usually built up from different sub-contexts. The sub-context always has at least one 'super context'. Subsequently, roles or responsibilities of actors in situations are modeled as (sub-)contexts as well. Specific roles apply to specific situations. For example, the role “Civilian:Civilian dealing with flooding” shows that the role “Civilian dealing with flooding” is a sub-context of the situation “Flooding” and at the same time it is a sub-context of the role “Civilian”. Thus, a sub-context can be derived from more than one super context.

Figure 2. The situation "Community resilience" consisting of sub-contexts like "Flooding" (sub-situation) and "Civilian" (role).

To conclude, it can be observed that a context is used to model situations comprising of sub-situations and roles. In turn, a role may be regarded as a situation for its constituents. That is, a role can be seen as a situation made up of sub-roles and sub-situations. Another typical example of a context presented as a role is an organization with its specific objective or responsibility where its employees are engaged in specific activities. From the perspective of an employee however, the organization may appear as a situation to operate in rather than a role. So it is a matter of perspective from which we can abstract away by using the general concept of nested contexts.

Conditions defining interdependencies

A situation is characterized by one or more conditions. Conditions determine how and how well the actors in a situation interact, but they can also be influenced by the behavior of actors. A condition is often defined in a qualified way, e.g. “the availability of rescue workers”, or “ sufficient supply of evacuation resources”. Therefor, a condition can also be regarded as an internal system indicator.

Typically, a goal and condition are related, expressed in the interdependency “contributes to”: a goal contributes to a condition. In figure 3, the goal “Right resources in the right place in time” contributes positively to the condition “Evacuation resources”. In other words, the condition is an indication of the extent to which the goal has been achieved. Note, a goal and a condition are deliberately modeled as different elements, because in real situations it frequently occurs that achieving one goal (contributing to a condition) is undermined by achieving another goal (contributing to the same condition).

Figure 3. Goals contributing to conditions.

Type and quality of relations

Examples 3 and 4 are used to describe the type and quality of relations between activities, goals and conditions.

Dependency: Activities may depend on a condition, as is the case in example 3: evacuation with public transport. Dependency between an activity and condition states the extent to which an activity can be performed depending on how well this activity is facilitated by other activities expressed in terms of one or more conditions.
Contribution: A goal contributes to a condition. The relation “contributes to” is not as strong as the relation “depends on”. A dependency can be expressed as “contributes to” for modeling situations in which the relation between an activity and a condition is weaker.

Example 4: Interacting elements

Note regarding the general pattern of relations (example 4): by applying a condition a relation is established between Activity A and Activity B. This is an implicit relation, as by means of the condition the relation between Activity A and B is (already) established. There is no need to make the relation between A and B (as indicated by the dotted lines in example 4) explicit.

Worldview and beliefs

Up to now we have focused on a single person who, depending on the situation, carried out certain activities. However, not everyone will carry out this particular activity in the same way. These different approaches originate from the different worldviews people have. And vice-versa: the worldview of a single person may vary depending on the situation he is engaged in. Therefore, different worldviews will have to be considered, which can be included in the model similarly to how contexts were used to model roles in specific situations. Example 5 illustrates different worldviews: a Civilian can deal with flooding by helping his neighbors or deal with the disaster on his own.

A belief is considered a fixed idea, which defines a worldview. A belief is similar to a condition, but in contrast, a belief cannot be changed within the system itself. In example 5 the context “Civilian dealing with flooding on its own” includes the belief “Do not trust the government”: this particular civilian does not expect anything positive from the government, no matter how hard the government tries.

Example 5: Worldviews and beliefs

Refining and creating clarity in the complex model

Creating clarity in a complex model can be done firstly by developing a main scheme presenting the big picture which includes only the most important situations (sub-contexts). Details of the different situations are provided only when “zooming in” to these, thus by developing separate schemes that only describe the situation selected. The main scheme therefore provides a more generic basis (or the so-called ‘hooks’) for deriving sub-contexts to which, depending on the type of situation you are interested to have a detailed look at, information can be added.

To the sub-contexts generated in examples 2 and 3 information can be added and removed (see example 5). For instance: specialized roles, such as “Civilian dealing with flooding on its own” and “Civilian leading the neighborhood to deal with flooding” are derived from the role “Civilian dealing with flooding”. Modeling elements can be discarded when they are not of use or add value to a particular sub-context. For instance, the context “Civilian dealing with flooding on its own”, the activity “Fight” has been removed.

The octagonal shape indicates that this modeling element happens to be used in other contexts too. In example 5 “Evacuate” is an activity occurring elsewhere in het context “Flooding” as well.

All EMont modeling elements, as discussed in the previous paragraphs, brought together in one scheme:

All in one

Concluding remarks

The strength of modeling complex situations with EMont lies in putting patterns of human/non-human (actors) behavior (PQR’s) in a context and applying these recursively. A context or situation is key to modeling roles and interactions of actors, including their different worldviews, in that particular context. The example of a flooding disaster is a simplified and incomplete illustration of a real situation. Modeling real situations can reflect reality in a comprehensive manner, but the models can also become very large. Applying contexts supports separating the main situation or processes from more detailed descriptions of the individual situations.

Subjects not discussed in this introduction to modeling with EMont include documenting good and bad practices, a sequence of activities (‘composed activities’), and modeling conceptual knowledge and its connection to PQR’s in a context. These subjects makes modeling with EMont more comprehensive, yet does not imply the introduction of significantly different elements to EMont.

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Onderdeel van:
Expertise Management ontology
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Expertise Management ontology
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