Variables - evolving interpretations of reality

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Variables - evolving interpretations of reality is a lecture about what variables are and how they are developed.

Scope

Purpose: To describe what variables are, what do they describe and why, and how variables are developed and used.

Intended audience: Researchers (especially at doctoral student level) in any field of science (mainly natural, not social scientists).

Duration: 2 x 1 hour 15 minutes

Definition

The lecture consists of two parts: the first discussing what variables are and what are they for, the second part discusses how variables are developed and used.

In order to understand this lecture it is recommended to first acquaint oneself with the following lectures:

Objectives:

  • Learn the basic structure of an information object.
  • Learn what variables are: independent, eternally developing descriptions of reality.
  • Learn that the ultimate criterion of a variable is the truth.
  • Learn the differences and similarities of a variable, assessment, study, and encyclopedia article.
  • Learn how to use the variable definition as your information storage.
  • Learn how to make a new synthesis when new information comes up (in Bayesian language: to update your prior).
  • Learn how to handle variables that are partially or totally overlapping.

Result

Presentation Open assessment - variables.ppt.

Part I:

  • Variable:
    • evolving descriptions
    • descriptions of reality
    • interpretations based on synthesized information
  • Variable structure
    • scope - research question determined by practical need
    • definition - how to answer the question most truthlikely
    • result - answer to the question, outcome of executing definition

Part II:

  • collection of information %rarr; data
  • synthesis of information → formula → result
  • organization of information &rarr: information structure, assessment

Exercises:

Variable Task Examples of available data sources
PM2.5 exposure-response function Developing the contents of the variable. Acquaint yourself with the variable concept and the structure of a variable. With the purpose of the case assessment in mind, first determine the scope of the variable and then consequently definition and result based on both the provided existing variables as data sources and your own expertise. Specific things to consider: a) how to synthesize data from different sources? b) what additional data sources could be used to improve the variable? c)why could not either of the available existing variables be used instead of creating a new variable? d) what do you think about the quality of your variable (as the best estimate for the phenomenon it describes)? Prepare to present your variable to other groups and explain how your thinking evolved in the process of developing the variable.
Emission factors for burning processes Developing the contents of the variable. Acquaint yourself with the variable concept and the structure of a variable and consider the role of this variable in the case assessment. Dig out the necessary pieces of information from the provided FIRE database according to the needs of the assessment. Needed indexes and locations include:
  • Fuel: coal (assumed to be all anthracite), natural gas (assumed to be all buthane), residual oil (assumed to be all grade 6), distillate oil (assumed to be all grade 4), process gas, landfill gas
  • Burning processes: pulverized (coal), tangentially fired (natural gas), normal firing (oils),
  • Emissions: CO2, PM2.5
  • Emission control mechanism: <50 MW nothing, 50-100 MW multi-cyclone, 100-300 MW electrical precipitator + scrubber, >300 MW multi-cyclone + fiber filter

Having done the above, consider possible other data sources that could be used to improve the variable, e.g. in terms of making the variable more suitable also for other assessments. Prepare to present your variable to other groups and explain how your thinking evolved in the process of developing the variable.

  • Emission factor data from U.S.EPA: FIRE database (assume external combustion and electric generation for all fuels)
  • List of heat production installations in Helsinki metropolitan area
  • Analytica model File:CarbonTrade city-level.ANA
Population of Helsinki metropolitan area Developing the contents of the variable. With the purpose of the case assessment in mind, first determine the scope of the variable and then consequently consider definition and result. Check the available population data from different sources, consider their differences and make a synthesis out of them. Specific things to consider include:
  • How and why include different data sources in a variable (what is the difference between a variable and data)?
  • How to operationalize the synthesis (data → formula → result)?
  • How can coherence be obtained/retained with other fully or partly overlapping variables (e.g. population of Finland, population of Europe).

Prepare to present your variable to other groups and explain how your thinking evolved in the process of developing the variable.

DALY weights Developing the contents of the variable. Acquaint yourself with DALY concept, in particular regarding how the weights are estimated. Consider how the existing variable could be improved by including uncertainties in the weight estimates, e.g. making a shift from point estimates to distributions. Improve the variable accordingly if possible. Prepare to present your variable to other groups and explain DALY weights, their role in estimating DALYs, and how including uncertainty in DALY weights affects DALY estimates. WHO Global Burden of Disease website
Cardiopulmonary mortality in Helsinki metropolitan area Developing the contents of the variable. With the purpose of the case assessment in mind, first determine the scope of the variable and then consequently consider definition and result. Search for the needed information from WHO website and apply it in developing the variable.
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