Networks and Data Visualisation

These readings provided some useful information for working with data, connecting that data into networks, and also visualising those networks using different kinds of graphics. We’ve already begun to do much of this in class, for example with Voyant tools. I think the point in Tooling Up about accountability is an important one; graphs and other visualisations present data in such a shiny, appealing way (if done correctly) that they can also be used to misdirect. This is because the veneer of the graph creates the impression that the data behind the graph is objective and collected without any bias–however, as we’ve seen, data selection and manipulation is a highly subjective process. The graph or visualisation offers another degree of separation from the data, so one must be even more aware of the fact that the original data is not necessarily infallible.

I had one question about data networks– in what situation would one use a self-loop?


26 February 2017