Example Topic Map

My first example topic map was too granular. The structural elements were correct but the specific expression too small to convey the value of that structure for larger ideas. This project would create another example topic map in federated wiki to connect deeper ideas.

This page is a 🌱 Seedling Project.

In chapter 3 Joint Cognitive Systems: Patterns in Cognitive Systems Engineering, Dr. Richard Cook described how to use the jargon (the paper uses the word "argot") of an Intensive Care Unit (ICU) combined with an analysis of an incident in order to learn and describe the normal adaptations at work in a specific complex system.

To explain the jargon to an uninitiated reader, the author must explain the complexities of the system where that jargon makes sense. Next, the author shows the reader how experts in that context apply that jargon to manage a specific surprise. In the end, the reader is left with a deep understanding of the complexity of that system and the challenges faced by the experts within.

Chapter 3 Being Bumpable: Consequences of Resource Saturation and Near-Saturation for Cognitive Demands on ICU Practitioners. Joint Cognitive Systems: Patterns in Cognitive Systems Engineering. Richard Cook, David D Woods. researchgate

In the Going Solid paper, Dr. Richard Cook applies a jargon from nuclear power to clarify an aspect of healthcare and ICUs. The specific term "going solid" is jargon that featured prominently in the partial meltdown at Three Mile Island. The metaphor of "going solid" is made to cross the chasm between completely different disciplines.

"Going solid": A model of system dynamics and consequences for patient safety. Richard Cook, Jens Rasmussen. Quality and Safety in Health Care. May 2005. dx.doi.org/10.1136/qshc.2003.009530 researchgate

In that bridge in the Going Solid paper, we can see the example that would connect the language domain of nuclear power and the language domain of healthcare. I believe this will make a much more compelling illustration for the value of topic maps as a data abstraction to connect disparate domains.

In so doing, we hope to enable patterns discovered in one domain to more easily transfer to other domains.