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| == Discussion on formula attribute ==
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| {{discussion
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| |Dispute= Is 'formula' an attribute of a variable or of a process that links different variables?
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| |Outcome= Under discussion (to be changed when a conclusion is found)
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| |Argumentation =
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| This issue has been discussed before, but I am not sure I agree with the fact that each variable has the attribute 'formula' in the description. I see it as follows (see also [[Full chain | the full chain approach diagram]]):
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| There are variables that describe reality, for example 'air pollution levels' or 'number of cardiovascular disease cases'. These variables have as attributes all the ones listed on the article page, but (as I see it) NOT a formula. Because there is not "one formula" for a variable. For example, transport can emit various pollutants as well as to noise. All of those pollutants as well as noise can lead to cardiovascular disease. Each pathway (from the exposure to cardiovascular disease, arrows in the diagram) has a different formula. This can never all be included in the definition of 'cardiovascular disease'. As I see it, a variable is more or less fixed, how to get there is not.
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| Instead, the processes linking the variables should be separately defined, with a different set of attributes. You could also call these processes 'variables' if you want (although I think this makes it complex), but then they are different types of variables with different attributes. The processes are where to put the models and the formulas leading to the variables.
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| Conclusion: I think it makes it a lot clearer to separate variables and processes.
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| What do you think?
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| (Anne)
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| {{comment|#1: |Variable is probably generally primarily perceived as an object of ''non-event'' type. Reality also includes objects of ''event'' type. These are phenomena that mediate the changes in the context (exterior) to the non-event(s) and manifest themselves as changes in the state of the non-event(s). The ''event'' and ''non-event'' type objects could be seen as different sides of the same coin, the other type not existing without the other. Or in other words, the ''non-event'' is a manifestation of the effect that the ''event'' causes in the prevailing context. The ''event'' and ''non-event'' objects can also be handled as ''composite'' objects that are composed of both ''event'' and ''non-event'' type objects. What is meant with the word '''variable''' in this approach is a composite object. It has attributes that mainly define the identity of the variable specifying its relations with its context(exterior), the result attribute, is an expression of the ''state'' of the variable, given the context and its relations of the variable, and the definition attribute describes the event(s) that manipulate the variable in ways that are then manifested in the state of the variable, i.e. its result. Whether a description of reality (e.g. a risk assessment) should be based on describing objects as composites or events and non-events separately is an interesting question and should be further considered.|--[[User:Mikko Pohjola|Mikko]] 13:44, 30 July 2007 (EEST)}}
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| {{attack|#2: |After some reading and thinking, here is an attempt to clarify and correct the previous comment and to take the consideration a bit further. There are two primitive universal classes of objects: ''event'' and ''medium'' (I referred to the latter as '' non-event'' in previous comment). Events are phenomena that take place in the media, provided that the structures and the states of the media are favourable for the phenomena to occur, and whose realization can be recognized as changes in the structures and the states of the media. Events can be (hierarchically, ''vertically'') divided into sub-events and similarly media as sub-media. Events and media can also be perceived as event-medium composites, where the event and medium are interlinked (''horizontally'', across the same level of hierarchy) by causal relations. Several sub-events can occur in a single medium and a single event can occur in several sub-media. Events and media compose chains or networks of phenomena, where events interact with their media, which further interact with other events which again interact with other media. An event and its media are inherently bound and the effect of an event can only be observed through changes in (the structure and state of) its media, so these chains are probably most comfortably perceived as comprising of event-medium composites which are linked to each other causally ([event-medium]→[event-medium] etc.). What is referred to as '''variable''' in the approach described on the article page, is actually an object of event-medium composite kind. Its attribute ''name'' is an identifier of the object, attributes ''scope'' and ''definition'' describe its structure (hierarchical and horizontal relations), and to some extent its purpose, while the attribute ''result'' describes its state with the help of the attribute ''unit''. The descriptions of a variable thus include both descriptions of the medium and the event(s) that are defined to be included within the boundary (scope) of the variable. I suggest that variable, as an object of even-medium composite type, is chosen as the abstraction level of observation, but that the structure descriptions of the variables be made more explicit in what events and media are included within the variable and what are the causal relations between them as well as the causal relations to other variables. Note: These considerations are strongly influenced by a universally applicable PSSP ontology, described in e.g. Pohjola V.J.: Ontological Approach to Formalize Waste Management, http://www.springerlink.com/content/r1n10r828nt57622/.|--[[User:Mikko Pohjola|Mikko]] 16:36, 31 July 2007 (EEST)}}
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| {{comment|#(number): |Mikko, could you "translate" this to the example made by Anne? I admit, I don't really understand what you want to say. Or, maybe, I am not able to transfer the abstract into usability. Anne has asked what happens if you have a variable "number of cardiovascular disease cases" which is cause by several pollutants/stressors. Would "number of cardiovascular disease cases" be something like a class containing variables like "number of cardiovascular disease cases due to PM" and "number of cardiovascular disease cases due to noise"? How would that take into account the combined effect of PM and noise? (if we have an ERF for noise AND PM e.g.?|--[[User:Alexandra Kuhn|Alexandra Kuhn]] 09:22, 7 March 2008 (EET)}}
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