Difference between revisions of "Class"

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'''New thoughts about Classes:
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[[Category:Universal object]]
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[[Category:Glossary term]]
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{{Guidebook}}
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<section begin=glossary />
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:'''Class''' is a [[:en:Set theory|set]] of items ([[object]]s) that share the same property or properties. The membership in a class is determined by an inclusion criterion. The property is utilised as a part of all objects that fulfill the criterion. Classes can be used in describing general information that is shared by more than one object. Class efficiently reduces the redundancy of information in the [[open assessment]] system. This improves the inter-assessment efficiency of the assessment work.
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<section end=glossary />
  
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A  class is a set of objects that share a common property or properties. The basic structure of a class is the same as for other objects: name, scope, definition, result.
 
  
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;Name: Name is the identifier of the object. It also describes the class in a general level.
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; Research question about the class structure: What is a structure for a class such that it
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:* unambiguously describes the common property,
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:* unambiguously describes the inclusion criterion, i.e. the rule to find out whether an object has the property and belongs to the class or not,
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:* inherits the main structure from [[universal object]]s,
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:* complies with the [[:en:Set theory|Set theory]],
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:* complies with the [[PSSP]] ontology.
  
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;Scope: A class is created for a practical purpose to act as a storage of a particular property (i.e., a piece  of information) that is shared by several objects. Therefore, the scope is driven by this practical purpose. The scope describes the purpose, and consequently defines the particular property in a general level.
 
  
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;Definition: The definition describes the piece(s) of information in full detail and it such a way that its actual content is directly quotable from the other objects (in Mediawiki, as templates). Each piece of actual content may be accompanied by narrative descriptions and discussions. A single piece of information may also be the result of a variable. In such a case, all data and discussions about the variable goes to the variable itself, and only the result is quoted in the definition of the class, together with a discussion why the result is indeed shared by all objects in the class.
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The attributes of a class{{disclink|Set &rarr; set?}} closely resemble those of a variable. However, the interpretation is slightly different, as can be seen from the table. In addition, the usage of data is not clear at the moment.
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;Result: The result lists all objects that belong to this class, i.e., share all the properties described in the definition. Therefore, the membership is a secondary thing and is determined by the properties (i.e. the definition) of the class. The class is NOT built around a particular set of objects, describing their common properties, but the other way round. The result contains the discussion about whether a particular object belong to the class or not. This applies also to the objects that were found out not to belong to the class. These discussions are stored and kept available so that there is not a need to have a new discussion if the question arises again.
 
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'''[[:en:Class (set theory)|Class]]''' is a specific [[:en:Set theory|set]], where the set contains all things as items that fulfil a defined criterion. The purpose of a class{{disclink|Set &rarr; set?}} in risk assessment is that general knowledge may be attributed to a class, and then it can be utilised in the description of any item (variable) that fulfils the inclusion criterion. This improves the inter-assessment efficiency of risk assessment work.
 
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A class may contain information about e.g. a good function that should be used to calculate the result, or a range of plausible values for a certain type of variable. Examples of these are given below.
 
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'''A general dose-response function''' can be a class. For example, the multi-stage model for cancer dose-responses can be defined as
 
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  P(d) = 1-exp(-q<sub>0</sub> -q<sub>1</sub>d -q<sub>2</sub>d<sup>2</sup>)
 
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This function has four parameters: q<sub>0</sub> (the "background"), q<sub>1</sub> (the "slope" at low doses), q<sub>2</sub> (the "curvature" parameter) and d (lifetime daily dose of the chemical of interest). The function can be applied to a particular chemical among a wide range of chemical carcinogens, if the chemical-specific parameters q<sub>0</sub>, q<sub>1</sub>, and q<sub>2</sub> are known. The result attribute of this class is equal to the general form of the multi-stage function. The function is used in the definition/formula attribute of a dose-response variable of a particular chemical, together with the chemical-specific parameters. The result attribute of this variable is the dose-response of the particular chemical, with one parameter, d. This variable can then be applied in a case-specific risk assessment, when the parameter d is replaced by the dose in an exposure scenario in that assessment.
 
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This is an efficient way of organising information: all discussion about the plausibility of the multi-stage model in general is located in the class. Therefore, this discussion is held only once, for all chemicals and all assessments. Also the discussion whether the multi-stage function applies to a particular chemical is located there. The resolution of that discussion applies to all risk assessments on that chemical. The chemical-specific dose-response variable contains the discussion about the best estimates of the chemical-specific parameters. And again, the variable is applicable to all risk assessments on that chemical. A particular risk assessment can focus on estimating the exposures. The whole dose-response part of the assessment is ready-made.
 
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'''Prior values for variables''' can also be located in classes. For example, imagine a class "Plausible range of PM<sub>2.5</sub> annual average mass concentrations in ambient air." This is a uniform probability distribution of concentrations ranging possibly from 3 µg/m<sup>3</sup> (in Antarctic) to 300 µg/m<sup>3</sup> (in downtown Delhi). This can be applied in PM<sub>2.5</sub> variables for checking for implausible values. The range (i.e., the value of the result attribute of the class) can be located in the definition/data attribute of e.g. a variable "PM<sub>2.5</sub> annual average concentration in downtown Kuopio." If we do have measurements from Kuopio, we can do Bayesian updating using the range as the prior. This way, we can operationalise the use of both the case-specific measurements and the general knowledge from the class.
 
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In practice, when new variables are created, they can partly be described using the results of existing classes, as long as the variable belongs to these classes. Possibly there should be a possibility to overrule the class information with case-specific information, if this is explicitly mentioned. However, deviations from the general rule should be defended.
 
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The attributes of a class closely resemble those of a variable. However, the interpretation is slightly different, as can be seen from the table. In addition, the usage of data is not clear at the moment.
 
  
 
{|{{prettytable}}
 
{|{{prettytable}}
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|+ Table 5. The attributes of a class.
 
! Attribute
 
! Attribute
 
! Subattributes
 
! Subattributes
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| Name
 
| Name
 
|  
 
|  
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| Identifier for the class
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| Identifier for the class.
 
|-----
 
|-----
 
| Scope
 
| Scope
 
|  
 
|  
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| What defines the items of the class, i.e. the inclusion criterion
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| Description of a property or properties, which are shared by all the items in the class.
 
|-----
 
|-----
 
| Definition
 
| Definition
 
|  
 
|  
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| List of items (i.e. variables, assessments or classes) belonging to the class
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| An inclusion criterion that unambiguously distinguishes whether a particular object has the defined properties or not. In other words, definition separates objects that belong to the class from those that do not belong. The definition also contains the discussion about memberships.
 
|-----
 
|-----
 
| Result
 
| Result
 
|  
 
|  
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| Common properties that are shared by all items in the class. The common properties may be any parts of variable, assessment or class descriptions.
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| List of items (formally structured objects) that belong to the class.
 
|}
 
|}
  
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{{disclink|Class criteria}}
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====Examples of use====
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A class may contain information about e.g. a good function that should be used to calculate the result, or a range of plausible values for a certain type of variable. Examples of these are given below.
 +
 +
'''A general dose-response function''' can be a class. For example, the multi-stage model for cancer dose-responses can be defined as
 +
 +
  P(d) = 1-exp(-q<sub>0</sub> -q<sub>1</sub>d -q<sub>2</sub>d<sup>2</sup>)
  
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This function has four parameters: q<sub>0</sub> (the "background"), q<sub>1</sub> (the "slope" at low doses), q<sub>2</sub> (the "curvature" parameter) and d (lifetime daily dose of the chemical of interest). The function can be applied to a particular chemical among a wide range of chemical carcinogens, if the chemical-specific parameters q<sub>0</sub>, q<sub>1</sub>, and q<sub>2</sub> are known. The result attribute of this class is equal to the general form of the multi-stage function. The function is used in the definition/formula attribute of a dose-response variable of a particular chemical, together with the chemical-specific parameters. The result attribute of this variable is the dose-response of the particular chemical, with one parameter, d. This variable can then be applied in a case-specific risk assessment, when the parameter d is replaced by the dose in an exposure scenario in that assessment.
  
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'''Technical issues about classes in Mediawiki'''
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This is an efficient way of organising information: all discussion about the plausibility of the multi-stage model in general is located in the class. Therefore, this discussion is held only once, for all chemicals and all assessments. Also the discussion whether the multi-stage function applies to a particular chemical is located there. The resolution of that discussion applies to all risk assessments on that chemical. The chemical-specific dose-response variable contains the discussion about the best estimates of the chemical-specific parameters. And again, the variable is applicable to all risk assessments on that chemical. A particular risk assessment can focus on estimating the exposures. The whole dose-response part of the assessment is ready-made.
  
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When we want to describe a general property, we must create a Class category. The class is a set of items that all share this general property. All variables that belong to this class or its subclass are allowed to inherit the property. I say 'are allowed' because this does not happen automatically in Mediawiki: the editor must create the link.
 
  
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You need two things: a template and a category. The template contains the general property (i.e., the ''result'' attribute of the class), and the category defines, which variables or classes belong to this class. All templates that apply to a given class are listed in the category page. In this way, it is easy to find all templates that apply to a variable that belongs to the class. Just define the relevant category, and then go through the descriptions of the category to see whether they contain properties that should be used in the variable or class. Actually, an editor should take a position to '''all''' properties applicable to the variable under edition. Not all properties have to be used, but reasons should be given why some were selected and some not. If there is a dispute whether a variable or class belongs to a particular class, this argumentation is located on the Talk page of the particular class, not on the Talk page of the item.
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'''Prior values for variables''' can also be located in classes. For example, imagine a class "Plausible range of PM<sub>2.5</sub> annual average mass concentrations in ambient air." This is a uniform probability distribution of concentrations ranging possibly from 3 µg/m<sup>3</sup> (in Antarctic) to 300 µg/m<sup>3</sup> (in downtown Delhi). This can be applied in PM<sub>2.5</sub> variables for checking for implausible values. The range (i.e., the value of the result attribute of the class) can be located in the definition/data attribute of e.g. a variable "PM<sub>2.5</sub> annual average concentration in downtown Kuopio." If we do have measurements from Kuopio, we can do Bayesian updating using the range as the prior. This way, we can operationalise the use of both the case-specific measurements and the general knowledge from the class.
  
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Often there may be several templates describing the same property. They may just be alternative approximations of the actual thing (which is not known perfectly, or it may be impractical to calculate it perfectly), and the choice between them is a matter of practice or convention. However, if there is a true conflict between two properties so that they cannot be true at the same time (not even as approximations), a discussion must be created on the Talk page.
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In practice, when new variables are created, they can partly be described using the results of existing classes, as long as the variable belongs to these classes. Possibly there should be a possibility to overrule the class information with case-specific information, if this is explicitly mentioned. However, deviations from the general rule should be defended.

Latest revision as of 21:18, 13 June 2008

<section begin=glossary />

Class is a set of items (objects) that share the same property or properties. The membership in a class is determined by an inclusion criterion. The property is utilised as a part of all objects that fulfill the criterion. Classes can be used in describing general information that is shared by more than one object. Class efficiently reduces the redundancy of information in the open assessment system. This improves the inter-assessment efficiency of the assessment work.

<section end=glossary />


Research question about the class structure
What is a structure for a class such that it
  • unambiguously describes the common property,
  • unambiguously describes the inclusion criterion, i.e. the rule to find out whether an object has the property and belongs to the class or not,
  • inherits the main structure from universal objects,
  • complies with the Set theory,
  • complies with the PSSP ontology.


The attributes of a classD↷ closely resemble those of a variable. However, the interpretation is slightly different, as can be seen from the table. In addition, the usage of data is not clear at the moment.

Table 5. The attributes of a class.
Attribute Subattributes Comments
Name Identifier for the class.
Scope Description of a property or properties, which are shared by all the items in the class.
Definition An inclusion criterion that unambiguously distinguishes whether a particular object has the defined properties or not. In other words, definition separates objects that belong to the class from those that do not belong. The definition also contains the discussion about memberships.
Result List of items (formally structured objects) that belong to the class.

D↷

Examples of use

A class may contain information about e.g. a good function that should be used to calculate the result, or a range of plausible values for a certain type of variable. Examples of these are given below.

A general dose-response function can be a class. For example, the multi-stage model for cancer dose-responses can be defined as 

  P(d) = 1-exp(-q0 -q1d -q2d2)

This function has four parameters: q0 (the "background"), q1 (the "slope" at low doses), q2 (the "curvature" parameter) and d (lifetime daily dose of the chemical of interest). The function can be applied to a particular chemical among a wide range of chemical carcinogens, if the chemical-specific parameters q0, q1, and q2 are known. The result attribute of this class is equal to the general form of the multi-stage function. The function is used in the definition/formula attribute of a dose-response variable of a particular chemical, together with the chemical-specific parameters. The result attribute of this variable is the dose-response of the particular chemical, with one parameter, d. This variable can then be applied in a case-specific risk assessment, when the parameter d is replaced by the dose in an exposure scenario in that assessment.

This is an efficient way of organising information: all discussion about the plausibility of the multi-stage model in general is located in the class. Therefore, this discussion is held only once, for all chemicals and all assessments. Also the discussion whether the multi-stage function applies to a particular chemical is located there. The resolution of that discussion applies to all risk assessments on that chemical. The chemical-specific dose-response variable contains the discussion about the best estimates of the chemical-specific parameters. And again, the variable is applicable to all risk assessments on that chemical. A particular risk assessment can focus on estimating the exposures. The whole dose-response part of the assessment is ready-made.


Prior values for variables can also be located in classes. For example, imagine a class "Plausible range of PM2.5 annual average mass concentrations in ambient air." This is a uniform probability distribution of concentrations ranging possibly from 3 µg/m3 (in Antarctic) to 300 µg/m3 (in downtown Delhi). This can be applied in PM2.5 variables for checking for implausible values. The range (i.e., the value of the result attribute of the class) can be located in the definition/data attribute of e.g. a variable "PM2.5 annual average concentration in downtown Kuopio." If we do have measurements from Kuopio, we can do Bayesian updating using the range as the prior. This way, we can operationalise the use of both the case-specific measurements and the general knowledge from the class.

In practice, when new variables are created, they can partly be described using the results of existing classes, as long as the variable belongs to these classes. Possibly there should be a possibility to overrule the class information with case-specific information, if this is explicitly mentioned. However, deviations from the general rule should be defended.

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