I was fortunate enough to attend the NESCI Winter School over the past couple of weeks in Cambridge, MA in the U.S. It was a very informative and productive 2 weeks as well as being a lot of fun! The way I've seen it for some time now the number of systems which interrelate when one considers Sustainable Development leads to a great deal of complexity. Complexity Science therefore, we may assume, would give us some handle on how to deal with this complexity.So, it turns out, the science of Complexity does indeed provide a number of tools and methods of analysis. Examples of the former would include modelling and examples of the latter would include networks. To illustrate, aside from the classes at NECSI from 9 to 5 each day every evening was spent on group work.
Our group in week 1 investigated issues concerning social capital and intervention strategies to alleviate 'social exclusion' (another interest of mine and also of some interest to this project). We developed a model and wrote a paper on the theoretical background.
However, of more relevance here, our group in week 2 investigated Global Warming. So, getting back to Complexity Science methods:
Firstly we realised that it is important to manage knowledge in Education for Sustainable Development. Hence, we developed a semantic network (as a form of ontology) of the knowledge we were researching and integrating into the NECSI Wiki. It is called Global Warming Ecosystem Brain or G-WEB.
Secondly, we developed a model, named atmosmodel, which helped us to develop our theories resulting from our newly researched knowledge of Global Warming. I likened this to the process of acquisition, argumentation and application I talk about in my PhD thesis.
We did not have long at all to carry out this work so it is all in its early stages. However, the whole course proved to be useful for 'Science for Sustainability'. In fact, as a means of developing the game tool kit which we are proposing will be the centrepiece of this project, I would like to explore the development of a simple model.
All in all this was two weeks well spent with a whole host of ideas gained in a very short space of time. Furthermore, some intelligent and quite dedicated people got to cross-fertilise their varying ideas about Complexity Science which in itself made the whole trip incredibly worthwhile.
