Visualisation of Relationships

by Maestoso on Monday 22 November, 2010 - 11:02 GMT

Posted in ModellingSystems Thinking

Tags: berlowcausal loopcomplexityrelationshipsystems thinkingvideovisualise

This is a recurring theme. Systems-thinking, systems engineering and architecture description are primarily concerned with identifying and managing the important relationships with other things in the world. They are relationship-centric rather than object-centric.

It is often hard for folks used to using flat 2D diagrams produced in PowerPoint or Visio to appreciate the potential power behind relationships. Flat diagrams don't make it easy to explore nearby related things and because they're limited in terms of the parameters you can apply, for example weightings to indicate proximity or importance, you often need many versions or different cut-sets of the bigger one.

Having a means to store objects and relationships and represent them allows you to explore beyond the immediate vicinity to assess impacts and dependencies. There is a very nice example on TED.com of the use of relationships by ecologist Eric Berlow which is helped by the ability to visualise them in a nice way. This could be achieved using a architecture description repository although the visualisation is probably not as good. There are bound also to be other tools that are good at representing and filtering relationships - possibly harking back to the thoughts for visualisations of information sources using Resource Description Format (RDF). With Linked Data gaining ground you need only to be able to see that relationships or dependencies exist but to be able to see what affect the strength of that relationship has. The Mk1 Human Being is highly adapted to visual input and stimulus so it is perhaps not surprising that being able to see and manipulate visually is a powerful tool in identifying context and assessing impact.

It is also a nice example of someone providing simple routes through the complex - which is what systems-thinking should be about. If we're making things harder, more complex or more complicated then we aren't doing a very good job.

This is why sticking to the flat-land isn't adequate to understanding where things sit and how dependent each is on others. The world isn't flat!

Anybody used visualisation software for this sort of thing? What works best? Any good case studies where this has helped to either save the day or revealed something unexpected? What tools are useful? Any good non-traditional uses of tools normally sued for other purposes?

References

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