Talk:Kuopio Risk Assessment Workshop 2008

Post your questions and comments here

If you have any questions and or comments regarding anything related to the workshop, please post them here and we will try to sort them out. -- Mikko Pohjola 10:10, 5 February 2008 (EET)

Draft Lecture outline

Lecture 1: Introduction to Open Risk Assessment (ORA) and the workshop Jouni

--#1: : Should the first lecture purely concentrate on preparing, inspiring and guiding the people to follow up and adopt what will be presented during following days and save the whole general assessment framework overview to the second lecture, or should the general assessment framework overview be more clearly divided between lectures 1 and 2? --Mikko Pohjola 11:26, 7 February 2008 (EET)

• Forget everything you knew about risk assessment
• During this week, we will describe a new approach to risk assessment. It has new developments from the theoretical foundation all the way to practical computer tools.
  • a new ontological foundation
  • strictly object-oriented approach
  • a new structure for objects
  • traditional methods for processing information, but organised in a more systematic way
  • tools that enable open collaboration
  • data sources that are directly available and applicable
• ORA is about information processing. The information is about the real world.
• A major aim of the system is to make the work systematic, reuse existing pieces of information, and save time and resources.
• What is the most efficient way of doing ORA?
• Practical way: short discussions only; all questions put into wiki and answered by the following day.
• critical scientific disciplines you should be aware of
  • decision analysis
  • probability theory
  • graph theory
  • pragma-dialectical argumentation theory

Lecture 2: General assessment framework (Mikko)

--#2: : This lecture should provide an overview of things coming up during the workshop and (perhaps?) an overview of most important things that will not be covered during the workshop. --Mikko Pohjola 11:26, 7 February 2008 (EET)

• purpose of assessments
  • to describe reality ( variables)
  • to serve a specific need (assessments + variable scope)
• properties of good assessments
  • quality of content, applicability, efficiency
• societal context of assessments
  • process, product and use
• general assessment processes
  • observation
  • information collection, manipulation and synthesis
  • management of assessment process
• universal products
  • assessment, variable, context, (class), causal diagram
  • falsifiability → information against a hypothesis
• open participation
  • why open participation?
    • acceptability, efficiency and relevance
  • implications of allowing open participation
• other relevant related concepts? → Glossary

Lecture 3: Information structure of ORA: object internal structure (Jouni)

• name, scope, definition, result
  • data, causality, unit, formula
• data connections vs. causal connections
• content, description and discussion

Lecture 4: Information structure of ORA: relations between objects (Mikko)

• variable, assessment, context, (class)
• presenting assessments as causal diagrams

Lecture 5: participating in assessments: argumentation (Mikko)

• dealing with disputes: discussion, commenting and argumentation
• argumentation theory (pragma-dialectics)
  • argument is always about a statement
  • validity of an argument
  • attack
  • defend
  • signature
  • comment

Lecture 6: participating in assessments: moderation and quality control (Jouni)

• principles of open participation
• reader, contributor, moderator, board of moderators
• different levels of protection
  • openly available page
  • page closed; discussion available
  • discussion managed by moderator, contributions via nuggets

Lecture 7: Evaluating assessment performance (Mikko)

• properties of good assessments
  • quality of content: informativeness, calibration and relevance
  • applicability: availability, usability and acceptability
  • efficiency: intra-assessment and inter-assessment efficiency
• relations between properties and information structure
• evaluation as an inherent part of the process

Lecture 8: addressing uncertainties (Jouni)

• probabilistic (real) uncertainties: informativeness, calibration about result
• model "uncertainties": about definition
• relevance: about scope
• variability vs uncertainty