You are here

The GLISA Problem Solving Environment

TitleThe GLISA Problem Solving Environment
Publication Type
Community Notes

The GLISA (Great Lakes Integrated Science and Applications) Problem Solving Environment

Purpose: This document introduces and describes the initial implementation of the problem-solving environment being developed for the Great Lakes Integrated Science and Applications Center (GLISA).  

Background: The primary goal of the GLISA Center is climate-change problem solving; that is, the incorporation of knowledge about our changing climate into our management of natural resources and our planning for the future.  It is our goal to develop an information-technology assisted environment in which all vested parties can participate in the development of solution strategies.  Co-development has proven to be an effective way of using science-generated knowledge of climate change.  With such an environment, we strive to leave a footprint from one effort that will accelerate the success of the next effort. 

Structured Problem Solving: In order to achieve our goal we pose that climate-change problem solving can be structured into four steps; inventory, analysis, evaluation, and synthesis. 

Inventory is the collection of the necessary information to address the problem.

Analysis is the consideration of the nature of the information:  deconstruction - breaking down the information, identifying relationships, determination of information gaps …

Evaluation is the determination of the quality and value of the information:  accuracy, relevancy, defensibility, validation …

Synthesis is the fitting together of the information resulting from the above problem solving processes to address a specific problem: reconstruction, integration, creation of new knowledge …

Analysis_Inventory_Synthesis.pngWhile we recognize that each problem to be addressed has the potential to be unique, we know that there are certain pieces of information that are common to many problems.  For example, consider a number of cities in the same state.  First, downscaled climate-model simulations are naturally shared across a region, and it is often desirable that each municipality start from the same standard of information.  Second, locally relevant interpretations of that information for one city could, likely, be shared by another city 50 miles away.  The cities are likely to share similar vulnerabilities.  Finally, if one city develops a good storm drainage plan or planning tool, then it might serve as a template for another city.   

A schematic of this environment is illustrated in the figure.  Also implied in this figure are elements of process.  There is the identification of knowledge gaps, or more generally an evaluation of the uncertainty associated with the knowledge.  Also identified is a process of validation to judge the quality of information and the synthesis of that information for the solution strategy.  This validation might follow from peer review or some other form of editorial policy or external review.  Again, if these processes are shared and emerge as successful strategies, then we can accelerate the incorporation of climate knowledge into these strategies.  

The first part of our implementation is the development of an environment to support the inventory phase and assist the analysis phase.  Technologically, we rely on the concepts of faceted search.  Faceted search is a technique for accessing a collection of information from a classification system that allows the assignment of multiple classifications to a piece of information.  This allows a piece of information to be identified in several ways; that is, it is not a hierarchical taxonomy.  Therefore, a piece of information that has proven of value to, for example, both mitigating the impact of urban heat and storm water management can be exposed in the search.  Sociologically, as a group of individuals work on a problem they tag pieces of information of value; they are encouraged to write narratives on the information and to identify linkages.  Essential to the success of the problem solving environment is the collection of the intellectual contributions of those participating in the solution of the problem.  A prototype experimental environment can be found at http://glisadownscaling.org/ .