Network analysis is very useful for showing relationships between objects/agents/people and does not require some of the more formal geographic foundations. The result is the formation and growth of informal and natural linkages to create complex systems which can model how things are connected to each other. It essentially provides an alternative to geographic datum for locating points in space through their relationships to other points. A good example are social media networks: the connections that individuals make online forms a global network of information about people and their relationships with each other.
An interesting topic highlighted in this article is the contrast between topological and non-topological data models. This distinction is interesting for me as a geography student since it seems ridiculous to exclude topology when thinking about networks. the paper makes a similar statement by explaining how these models were effectively useless as the are simply points and lines with no substantial information available for analysis. I would have appreciated a bit more explanation fro non-topological data models such as an example of how it may be used and why that might be advantageous over topological models in some uses.
The article makes one particularly large claim: Network GIS is the only sub-discipline to have redefined the spatial reference system on which locations are specified. Im not going to agree or disagree with this statement but I think the paper could’ve done a better job at supporting this argument and contrasting against potential sub-disciplines.