In parallel with the work on individual data elements in the strategies and problems files (described above), UIA advanced its explorations of feedback loops (both self-reinforcing and self-damping), specifically for this project in the fields of environment and conservation.
The notion of "loops", and its relevance to this project, requires some explanation. The purpose of detecting feedback loops is to raise the level of analysis of individual issues to a higher, systematic level. It is a technique which has the potential to add extra meaning to basic data, particularly relevant for policy makers and others concerned with understanding the interrelationships and root causes of environmental problems.
A self-reinforcing ("vicious") problem loop is a chain of problems, each aggravating the next, and with the last looping back to aggravate the first in the chain. An example is: Man-made disasters ® Vulnerability of ecosystem niches ® Natural environment degradation ® Shortage of natural resources ® Unbridled competition for scarce resources ® Man-made disasters. Such cycles are "vicious" because they are self-sustaining. Organizational strategies and programmes that focus on only one problem in a chain tend to fail because the cycle has the capacity to regenerate itself. Individual "vicious problem cycles" also tend to interlock, forming tangled skeins of interlinked global problems which implicate single environmental problems in chains and complexes of multi-sectoral issues. Without the means to untangle the relationships, the response to a conservation challenge may be ineffective, self-defeating or, even, harmful.
The pre-existing data file on problem loops was critically reviewed. The programme that analyses aggravating pathways in the data and identifies loops was re-run. Loops were identified for selected groups of problems only (since chain searching requires extensive computing time even with 133 MHz PCs). Two weeks of judicious editing of aggravating links between problem entries reduced the size of the file from 19,000 problem loops (maximum 7 problems per loop) to around 7,000. A preliminary analysis was also made for cycles of facilitating strategies.
As the work was left at the completion of the Definition Phase, there are 200 loops containing environmental issues relevant to this project. It is expected that this number could increase significantly following the editing work on content and hyperlinks anticipated for the Implementation Phase of the project. The loops detected as part of this Definition Phase of the project have been presented on the prototype CD. Work was also done in improving the display of loops, using popups, from single data records.
Future work on loops would benefit from selection on a faster machine (to avoid having to segment the data). The selection algorithm should also be reviewed by a person with mathematical skills to determine whether it could be done more efficiently. Consideration could also be given to activating other search facilities to detect various types of redundancy in the pattern of links, and notably potentially erroneous link patterns. Further work should also advance the visualization in 3-D of loops and loop interlocks (Section 3.8 Visualization (VRML 3-D displays).